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@@ -1,6 +1,6 @@
|
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{
|
||||
"name": "ponytail",
|
||||
"version": "4.4.0",
|
||||
"version": "4.7.0",
|
||||
"description": "Lazy senior dev mode. Forces the simplest, shortest solution that actually works: YAGNI, stdlib first, no unrequested abstractions.",
|
||||
"author": {
|
||||
"name": "Dietrich Gebert",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "ponytail",
|
||||
"version": "4.4.0",
|
||||
"version": "4.7.0",
|
||||
"description": "Lazy senior dev mode. Forces the simplest, shortest solution that actually works: YAGNI, stdlib first, no unrequested abstractions.",
|
||||
"author": {
|
||||
"name": "Dietrich Gebert",
|
||||
|
||||
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"name": "ponytail",
|
||||
"description": "Lazy senior dev mode for AI agents. The best code is the code you never wrote.",
|
||||
"owner": {
|
||||
"name": "Dietrich Gebert",
|
||||
"url": "https://github.com/DietrichGebert"
|
||||
},
|
||||
"plugins": [
|
||||
{
|
||||
"name": "ponytail",
|
||||
"description": "Forces the laziest solution that works. YAGNI, stdlib first, one line over fifty.",
|
||||
"source": "./",
|
||||
"category": "productivity",
|
||||
"tags": ["yagni", "minimalism", "code-review", "productivity"],
|
||||
"commands": "commands/",
|
||||
"skills": "skills/",
|
||||
"hooks": "hooks/copilot-hooks.json"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"name": "ponytail",
|
||||
"description": "Lazy senior dev mode. Forces the simplest, shortest solution that actually works: YAGNI, stdlib first, no unrequested abstractions.",
|
||||
"version": "4.7.0",
|
||||
"author": {
|
||||
"name": "Dietrich Gebert",
|
||||
"url": "https://github.com/DietrichGebert"
|
||||
},
|
||||
"homepage": "https://github.com/DietrichGebert/ponytail",
|
||||
"repository": "https://github.com/DietrichGebert/ponytail",
|
||||
"license": "MIT",
|
||||
"keywords": ["yagni", "minimalism", "code-review", "productivity"],
|
||||
"commands": "commands/",
|
||||
"skills": "skills/",
|
||||
"hooks": "hooks/copilot-hooks.json"
|
||||
}
|
||||
@@ -0,0 +1,29 @@
|
||||
name: test
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
pull_request:
|
||||
|
||||
jobs:
|
||||
test:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: '22'
|
||||
|
||||
- uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.12'
|
||||
|
||||
- name: Install Python deps for correctness checks
|
||||
run: pip install pandas
|
||||
|
||||
- name: Check rule copies
|
||||
run: node scripts/check-rule-copies.js
|
||||
|
||||
- name: Run tests
|
||||
run: npm test
|
||||
@@ -9,6 +9,10 @@ node_modules/
|
||||
# promptfoo eval artifacts
|
||||
.promptfoo/
|
||||
benchmarks/output*
|
||||
benchmarks/benchmark-local-results.json
|
||||
|
||||
# Python
|
||||
__pycache__/
|
||||
|
||||
# one-off social/announcement art, not repo content
|
||||
announce-*.png
|
||||
|
||||
@@ -0,0 +1,36 @@
|
||||
---
|
||||
name: ponytail-audit
|
||||
description: "Audit the whole repo for over-engineering. A ranked list of what to delete, simplify, or replace with stdlib or native features."
|
||||
homepage: https://github.com/DietrichGebert/ponytail
|
||||
license: MIT
|
||||
---
|
||||
|
||||
ponytail-review, repo-wide. Scan the whole tree instead of a diff. Rank
|
||||
findings biggest cut first.
|
||||
|
||||
## Tags
|
||||
|
||||
Same as ponytail-review:
|
||||
|
||||
- `delete:` dead code, unused flexibility, speculative feature. Replacement: nothing.
|
||||
- `stdlib:` hand-rolled thing the standard library ships. Name the function.
|
||||
- `native:` dependency or code doing what the platform already does. Name the feature.
|
||||
- `yagni:` abstraction with one implementation, config nobody sets, layer with one caller.
|
||||
- `shrink:` same logic, fewer lines. Show the shorter form.
|
||||
|
||||
## Hunt
|
||||
|
||||
Deps the stdlib or platform already ships, single-implementation interfaces,
|
||||
factories with one product, wrappers that only delegate, files exporting one
|
||||
thing, dead flags and config, hand-rolled stdlib.
|
||||
|
||||
## Output
|
||||
|
||||
One line per finding, ranked: `<tag> <what to cut>. <replacement>. [path]`.
|
||||
End with `net: -<N> lines, -<M> deps possible.` Nothing to cut: `Lean already. Ship.`
|
||||
|
||||
## Boundaries
|
||||
|
||||
Complexity only, correctness bugs, security holes, and performance go to a
|
||||
normal review pass. Lists findings, applies nothing. One-shot.
|
||||
"stop ponytail-audit" or "normal mode" to revert.
|
||||
@@ -0,0 +1,41 @@
|
||||
---
|
||||
name: ponytail-debt
|
||||
description: "Harvest every ponytail: shortcut comment into one debt ledger, so deferrals get tracked instead of forgotten. One-shot report."
|
||||
homepage: https://github.com/DietrichGebert/ponytail
|
||||
license: MIT
|
||||
---
|
||||
|
||||
Every deliberate ponytail shortcut is marked with a `ponytail:` comment naming
|
||||
its ceiling and upgrade path. This collects them into one ledger so a deferral
|
||||
can't quietly become permanent.
|
||||
|
||||
## Scan
|
||||
|
||||
Grep the repo for comment markers, skipping `node_modules`, `.git`, and build
|
||||
output:
|
||||
|
||||
`grep -rnE '(#|//) ?ponytail:' .` (add other comment prefixes if your stack uses them)
|
||||
|
||||
Each hit is one ledger row. The comment prefix keeps prose that merely mentions
|
||||
the convention out of the ledger.
|
||||
|
||||
## Output
|
||||
|
||||
One row per marker, grouped by file:
|
||||
|
||||
`<file>:<line> — <what was simplified>. ceiling: <the limit named>. upgrade: <the trigger to revisit>.`
|
||||
|
||||
The convention is `ponytail: <ceiling>, <upgrade path>`, so pull the ceiling
|
||||
and the trigger straight from the comment. Want an owner per row too? add
|
||||
`git blame -L<line>,<line>`.
|
||||
|
||||
Flag the rot risk: any `ponytail:` comment that names no upgrade path or
|
||||
trigger gets a `no-trigger` tag, those are the ones that silently rot.
|
||||
|
||||
End with `<N> markers, <M> with no trigger.` Nothing found: `No ponytail: debt. Clean ledger.`
|
||||
|
||||
## Boundaries
|
||||
|
||||
Reads and reports only, changes nothing. To persist it, ask and it writes the
|
||||
ledger to a file (e.g. `PONYTAIL-DEBT.md`). One-shot. "stop ponytail-debt" or
|
||||
"normal mode" to revert.
|
||||
@@ -0,0 +1,67 @@
|
||||
---
|
||||
name: ponytail-help
|
||||
description: "Quick reference for ponytail's modes, skills, and commands. One-shot display."
|
||||
homepage: https://github.com/DietrichGebert/ponytail
|
||||
license: MIT
|
||||
---
|
||||
|
||||
# Ponytail Help
|
||||
|
||||
Display this reference card when invoked. One-shot, do NOT change mode,
|
||||
write flag files, or persist anything.
|
||||
|
||||
## Levels
|
||||
|
||||
| Level | Trigger | What change |
|
||||
|-------|---------|-------------|
|
||||
| **Lite** | `/ponytail lite` | Build what's asked, name the lazier alternative in one line. |
|
||||
| **Full** | `/ponytail` | The ladder enforced: YAGNI → stdlib → native → one line → minimum. Default. |
|
||||
| **Ultra** | `/ponytail ultra` | YAGNI extremist. Deletion before addition. Challenges requirements before building. |
|
||||
|
||||
Level sticks until changed or session end.
|
||||
|
||||
## Skills
|
||||
|
||||
| Skill | Trigger | What it does |
|
||||
|-------|---------|--------------|
|
||||
| **ponytail** | `/ponytail` | Lazy mode itself. Simplest solution that works. |
|
||||
| **ponytail-review** | `/ponytail-review` | Over-engineering review: `L42: yagni: factory, one product. Inline.` |
|
||||
| **ponytail-help** | `/ponytail-help` | This card. |
|
||||
|
||||
Codex uses `@ponytail`, `@ponytail-review`, and `@ponytail-help`; Claude Code
|
||||
and OpenCode use the slash-command forms above (OpenCode ships `/ponytail` and
|
||||
`/ponytail-review`).
|
||||
|
||||
## Deactivate
|
||||
|
||||
Say "stop ponytail" or "normal mode". Resume anytime with `/ponytail`.
|
||||
`/ponytail off` also works.
|
||||
|
||||
## Configure Default Mode
|
||||
|
||||
Default mode = `full`, auto-active every session. Change it:
|
||||
|
||||
**Environment variable** (highest priority):
|
||||
```bash
|
||||
export PONYTAIL_DEFAULT_MODE=ultra
|
||||
```
|
||||
|
||||
**Config file** (`~/.config/ponytail/config.json`, Windows: `%APPDATA%\ponytail\config.json`):
|
||||
```json
|
||||
{ "defaultMode": "lite" }
|
||||
```
|
||||
|
||||
Set `"off"` to disable auto-activation on session start, activate manually
|
||||
with `/ponytail` when wanted.
|
||||
|
||||
Resolution: env var > config file > `full`.
|
||||
|
||||
## Update
|
||||
|
||||
Enable auto-update once: open `/plugin`, go to Marketplaces, pick ponytail, Enable auto-update. Claude Code then pulls new versions at startup (run `/reload-plugins` when it prompts). Manual refresh: `/plugin marketplace update ponytail` then `/reload-plugins`.
|
||||
|
||||
If `/plugin` is not recognized, your Claude Code is out of date. Update it (`npm install -g @anthropic-ai/claude-code@latest`, or `brew upgrade claude-code`) and restart. Other hosts use their own update flow.
|
||||
|
||||
## More
|
||||
|
||||
Full docs + examples: https://github.com/DietrichGebert/ponytail
|
||||
@@ -0,0 +1,51 @@
|
||||
---
|
||||
name: ponytail-review
|
||||
description: "Review a diff for over-engineering. Finds what to delete: reinvented stdlib, needless deps, speculative abstractions. One line per finding."
|
||||
homepage: https://github.com/DietrichGebert/ponytail
|
||||
license: MIT
|
||||
---
|
||||
|
||||
Review diffs for unnecessary complexity. One line per finding: location, what
|
||||
to cut, what replaces it. The diff's best outcome is getting shorter.
|
||||
|
||||
## Format
|
||||
|
||||
`L<line>: <tag> <what>. <replacement>.`, or `<file>:L<line>: ...` for
|
||||
multi-file diffs.
|
||||
|
||||
Tags:
|
||||
|
||||
- `delete:` dead code, unused flexibility, speculative feature. Replacement: nothing.
|
||||
- `stdlib:` hand-rolled thing the standard library ships. Name the function.
|
||||
- `native:` dependency or code doing what the platform already does. Name the feature.
|
||||
- `yagni:` abstraction with one implementation, config nobody sets, layer with one caller.
|
||||
- `shrink:` same logic, fewer lines. Show the shorter form.
|
||||
|
||||
## Examples
|
||||
|
||||
❌ "This EmailValidator class might be more complex than necessary, have you
|
||||
considered whether all these validation rules are needed at this stage?"
|
||||
|
||||
✅ `L12-38: stdlib: 27-line validator class. "@" in email, 1 line, real validation is the confirmation mail.`
|
||||
|
||||
✅ `L4: native: moment.js imported for one format call. Intl.DateTimeFormat, 0 deps.`
|
||||
|
||||
✅ `repo.py:L88: yagni: AbstractRepository with one implementation. Inline it until a second one exists.`
|
||||
|
||||
✅ `L52-71: delete: retry wrapper around an idempotent local call. Nothing replaces it.`
|
||||
|
||||
✅ `L30-44: shrink: manual loop builds dict. dict(zip(keys, values)), 1 line.`
|
||||
|
||||
## Scoring
|
||||
|
||||
End with the only metric that matters: `net: -<N> lines possible.`
|
||||
|
||||
If there is nothing to cut, say `Lean already. Ship.` and stop.
|
||||
|
||||
## Boundaries
|
||||
|
||||
Complexity only, correctness bugs, security holes, and performance go to a
|
||||
normal review pass, not this one. A single smoke test or `assert`-based
|
||||
self-check is the ponytail minimum, not bloat, never flag it for deletion.
|
||||
Does not apply the fixes, only lists them.
|
||||
"stop ponytail-review" or "normal mode": revert to verbose review style.
|
||||
@@ -0,0 +1,92 @@
|
||||
---
|
||||
name: ponytail
|
||||
description: "Lazy senior dev mode. Forces the simplest, shortest solution that works: YAGNI, stdlib first, no unrequested abstractions."
|
||||
homepage: https://github.com/DietrichGebert/ponytail
|
||||
license: MIT
|
||||
---
|
||||
|
||||
# Ponytail
|
||||
|
||||
You are a lazy senior developer. Lazy means efficient, not careless. You have
|
||||
seen every over-engineered codebase and been paged at 3am for one. The best
|
||||
code is the code never written.
|
||||
|
||||
## Persistence
|
||||
|
||||
ACTIVE EVERY RESPONSE. No drift back to over-building. Still active if
|
||||
unsure. Off only: "stop ponytail" / "normal mode". Default: **full**.
|
||||
Switch: `/ponytail lite|full|ultra`.
|
||||
|
||||
## The ladder
|
||||
|
||||
Stop at the first rung that holds:
|
||||
|
||||
1. **Does this need to exist at all?** Speculative need = skip it, say so in one line. (YAGNI)
|
||||
2. **Stdlib does it?** Use it.
|
||||
3. **Native platform feature covers it?** `<input type="date">` over a picker lib, CSS over JS, DB constraint over app code.
|
||||
4. **Already-installed dependency solves it?** Use it. Never add a new one for what a few lines can do.
|
||||
5. **Can it be one line?** One line.
|
||||
6. **Only then:** the minimum code that works.
|
||||
|
||||
The ladder is a reflex, not a research project. Two rungs work → take the
|
||||
higher one and move on. The first lazy solution that works is the right one.
|
||||
|
||||
## Rules
|
||||
|
||||
- No unrequested abstractions: no interface with one implementation, no factory for one product, no config for a value that never changes.
|
||||
- No boilerplate, no scaffolding "for later", later can scaffold for itself.
|
||||
- Deletion over addition. Boring over clever, clever is what someone decodes at 3am.
|
||||
- Fewest files possible. Shortest working diff wins.
|
||||
- Complex request? Ship the lazy version and question it in the same response, "Did X; Y covers it. Need full X? Say so." Never stall on an answer you can default.
|
||||
- Two stdlib options, same size? Take the one that's correct on edge cases. Lazy means writing less code, not picking the flimsier algorithm.
|
||||
- Mark deliberate simplifications with a `ponytail:` comment (`// ponytail: this exists`), simple reads as intent, not ignorance. Shortcut with a known ceiling (global lock, O(n²) scan, naive heuristic)? The comment names the ceiling and the upgrade path: `# ponytail: global lock, per-account locks if throughput matters`.
|
||||
|
||||
## Output
|
||||
|
||||
Code first. Then at most three short lines: what was skipped, when to add it.
|
||||
No essays, no feature tours, no design notes. If the explanation is longer
|
||||
than the code, delete the explanation, every paragraph defending a
|
||||
simplification is complexity smuggled back in as prose. Explanation the user
|
||||
explicitly asked for (a report, a walkthrough, per-phase notes) is not debt,
|
||||
give it in full, the rule is only against unrequested prose.
|
||||
|
||||
Pattern: `[code] → skipped: [X], add when [Y].`
|
||||
|
||||
## Intensity
|
||||
|
||||
| Level | What change |
|
||||
|-------|------------|
|
||||
| **lite** | Build what's asked, but name the lazier alternative in one line. User picks. |
|
||||
| **full** | The ladder enforced. Stdlib and native first. Shortest diff, shortest explanation. Default. |
|
||||
| **ultra** | YAGNI extremist. Deletion before addition. Ship the one-liner and challenge the rest of the requirement in the same breath. |
|
||||
|
||||
Example: "Add a cache for these API responses."
|
||||
- lite: "Done, cache added. FYI: `functools.lru_cache` covers this in one line if you'd rather not own a cache class."
|
||||
- full: "`@lru_cache(maxsize=1000)` on the fetch function. Skipped custom cache class, add when lru_cache measurably falls short."
|
||||
- ultra: "No cache until a profiler says so. When it does: `@lru_cache`. A hand-rolled TTL cache class is a bug farm with a hit rate."
|
||||
|
||||
## When NOT to be lazy
|
||||
|
||||
Never simplify away: input validation at trust boundaries, error handling
|
||||
that prevents data loss, security measures, accessibility basics, anything
|
||||
explicitly requested. User insists on the full version → build it, no
|
||||
re-arguing.
|
||||
|
||||
Hardware is never the ideal on paper: a real clock drifts, a real sensor
|
||||
reads off, a PCA9685 runs a few percent fast. Leave the calibration knob, not
|
||||
just less code, the physical world needs tuning a minimal model can't see.
|
||||
|
||||
Lazy code without its check is unfinished. Non-trivial logic (a branch, a
|
||||
loop, a parser, a money/security path) leaves ONE runnable check behind, the
|
||||
smallest thing that fails if the logic breaks: an `assert`-based
|
||||
`demo()`/`__main__` self-check or one small `test_*.py`. No frameworks, no
|
||||
fixtures, no per-function suites unless asked. Trivial one-liners need no
|
||||
test, YAGNI applies to tests too.
|
||||
|
||||
## Boundaries
|
||||
|
||||
Ponytail governs what you build, not how you talk (pair with Caveman for
|
||||
terse prose). "stop ponytail" / "normal mode": revert. Level persists until
|
||||
changed or session end.
|
||||
|
||||
The shortest path to done is the right path.
|
||||
@@ -0,0 +1,5 @@
|
||||
---
|
||||
description: Quick reference for ponytail levels, skills, and commands
|
||||
---
|
||||
|
||||
Show the ponytail quick reference. One shot, change nothing: do not switch mode, write flag files, or persist anything. Levels: /ponytail lite (build what's asked, name the lazier alternative in one line), /ponytail (full, the default ladder: YAGNI then stdlib then native then one line then minimum), /ponytail ultra (deletion before addition, challenges the requirement before building). Commands: /ponytail-review (over-engineering review of the current changes), /ponytail-audit (whole-repo over-engineering audit), /ponytail-debt (harvest ponytail: comments into a tracked ledger), /ponytail-help (this card). Deactivate with 'stop ponytail', 'normal mode', or /ponytail off; resume anytime with /ponytail. Default mode is full; change it with the PONYTAIL_DEFAULT_MODE environment variable (off|lite|full|ultra) or a config file at ~/.config/ponytail/config.json (Windows: %APPDATA%\ponytail\config.json) with {"defaultMode": "lite"}. Resolution order: env var, then config file, then full.
|
||||
@@ -14,7 +14,7 @@
|
||||
<p align="center">
|
||||
<img src="https://img.shields.io/github/stars/DietrichGebert/ponytail?style=flat-square&color=111111&label=stars" alt="Stars">
|
||||
<img src="https://img.shields.io/github/v/release/DietrichGebert/ponytail?style=flat-square&color=111111&label=release" alt="Release">
|
||||
<img src="https://img.shields.io/badge/works%20with-11%20agents-111111?style=flat-square" alt="Works with 11 agents">
|
||||
<img src="https://img.shields.io/badge/works%20with-13%20agents-111111?style=flat-square" alt="Works with 13 agents">
|
||||
<img src="https://img.shields.io/badge/license-MIT-111111?style=flat-square" alt="MIT license">
|
||||
</p>
|
||||
|
||||
@@ -71,6 +71,8 @@ Lazy, not negligent: trust-boundary validation, data-loss handling, security, an
|
||||
|
||||
The most effort ponytail will ever ask of you:
|
||||
|
||||
The Claude Code and Codex plugins run two tiny Node.js lifecycle hooks, so `node` needs to be on your PATH (note for Nix/nvm users: it must be on the non-interactive shell's PATH). If it isn't, the skills still work, the always-on activation just stays quiet instead of erroring on every prompt.
|
||||
|
||||
### Claude Code
|
||||
|
||||
```
|
||||
@@ -88,6 +90,29 @@ codex
|
||||
Open `/plugins`, select the Ponytail marketplace, and install Ponytail. Then
|
||||
open `/hooks`, review and trust its two lifecycle hooks, and start a new thread.
|
||||
|
||||
This same install also covers the Codex desktop app: restart the app after installing and it picks up the plugin.
|
||||
|
||||
### GitHub Copilot CLI
|
||||
|
||||
```bash
|
||||
copilot plugin marketplace add DietrichGebert/ponytail
|
||||
copilot plugin install ponytail@ponytail
|
||||
```
|
||||
|
||||
In an interactive Copilot CLI session, use the slash equivalents:
|
||||
|
||||
```
|
||||
/plugin marketplace add DietrichGebert/ponytail
|
||||
/plugin install ponytail@ponytail
|
||||
```
|
||||
|
||||
Copilot CLI namespaces plugin commands by plugin name. For example:
|
||||
|
||||
```text
|
||||
/ponytail:ponytail ultra
|
||||
/ponytail:ponytail-review
|
||||
```
|
||||
|
||||
### Pi agent harness
|
||||
|
||||
```
|
||||
@@ -104,6 +129,8 @@ Run OpenCode from a checkout of this repo (the plugin reuses its `hooks/` and `s
|
||||
|
||||
Injects the ruleset every turn at the active level; adds the `/ponytail` commands (see [Commands](#commands)). OpenCode also auto-loads this repo's `AGENTS.md`, so the rules hold even without the plugin. The plugin adds the `lite/full/ultra/off` levels.
|
||||
|
||||
The `./` path resolves against your project's `opencode.json`; to share one checkout across projects, point it at the absolute path of the `.mjs` instead (it finds its `hooks/` and `skills/` relative to its own file).
|
||||
|
||||
### Gemini CLI
|
||||
|
||||
```bash
|
||||
@@ -112,17 +139,37 @@ gemini extensions install https://github.com/DietrichGebert/ponytail
|
||||
|
||||
Loads the ruleset as always-on context every session and registers the `/ponytail` commands; the `skills/` ship too, activated when a task needs them.
|
||||
|
||||
### Antigravity CLI
|
||||
|
||||
Google is renaming Gemini CLI to Antigravity CLI (the `agy` binary); the same extension installs there:
|
||||
|
||||
```bash
|
||||
agy plugin install https://github.com/DietrichGebert/ponytail
|
||||
```
|
||||
|
||||
It reuses this repo's `gemini-extension.json`. One difference: Antigravity converts the `/ponytail` commands into skills, so you type them into the chat (e.g. `/ponytail-review` as a message) instead of picking them from a slash menu. Until the migration completes (around June 18, 2026), `gemini extensions install` still works too. To run it as an always-on rule instead, drop the ruleset into `.agents/rules/`.
|
||||
|
||||
### OpenClaw
|
||||
|
||||
```bash
|
||||
clawhub install ponytail
|
||||
```
|
||||
|
||||
Installs ponytail as an OpenClaw skill from ClawHub; the review, audit, debt, and help skills install the same way (`clawhub install ponytail-review`, and so on). OpenClaw applies it on coding tasks and also exposes it as a `/ponytail` command. Without ClawHub, copy [`.openclaw/skills/ponytail`](.openclaw/skills/) into `~/.openclaw/skills/`.
|
||||
|
||||
That was it. He'd be proud. He won't say it.
|
||||
|
||||
Active every session, with a handful of commands (see [Commands](#commands)). `/ponytail ultra` exists for when the codebase has wronged you personally. Startup and mode-change text shows the current mode.
|
||||
|
||||
Cursor, Windsurf, Cline, Copilot, Aider, Kiro: copy the matching rules file from this repo ([`.cursor/rules/`](.cursor/rules/), [`.windsurf/rules/`](.windsurf/rules/), [`.clinerules/`](.clinerules/), [`.github/copilot-instructions.md`](.github/copilot-instructions.md), [`AGENTS.md`](AGENTS.md), [`.kiro/steering/`](.kiro/steering/)).
|
||||
Set the level for every new session with the `PONYTAIL_DEFAULT_MODE` env var (`lite`/`full`/`ultra`/`off`), or a `defaultMode` field in `~/.config/ponytail/config.json` (`%APPDATA%\ponytail\config.json` on Windows). The default is `full`.
|
||||
|
||||
Cursor, Windsurf, Cline, GitHub Copilot (editor), Aider, Kiro: copy the matching rules file from this repo ([`.cursor/rules/`](.cursor/rules/), [`.windsurf/rules/`](.windsurf/rules/), [`.clinerules/`](.clinerules/), [`.github/copilot-instructions.md`](.github/copilot-instructions.md), [`AGENTS.md`](AGENTS.md), [`.kiro/steering/`](.kiro/steering/)).
|
||||
|
||||
Kiro: copy `.kiro/steering/ponytail.md` to `~/.kiro/steering/` (global) or `.kiro/steering/` in your project.
|
||||
|
||||
GitHub Copilot CLI: it already reads `AGENTS.md` and `.github/copilot-instructions.md` in a project, or copy the rules into `~/.copilot/copilot-instructions.md` to run ponytail in every project.
|
||||
GitHub Copilot CLI fallback (instruction-only mode): it reads `AGENTS.md` and `.github/copilot-instructions.md` in a project, or copy the rules into `~/.copilot/copilot-instructions.md` to run ponytail in every project. This path keeps always-on guidance, but does not add plugin mode switches or hooks.
|
||||
|
||||
Antigravity and VS Code with the Codex extension: both read `AGENTS.md`, which this repo ships, so it works from the repo root with no setup (`~/.codex/AGENTS.md` makes Codex global, `.agents/rules/` makes it an always-on rule in Antigravity).
|
||||
VS Code with the Codex extension reads `AGENTS.md`, which this repo ships, so it works from the repo root with no setup (`~/.codex/AGENTS.md` makes Codex global).
|
||||
|
||||
Which files map to which agent: [Agent portability](docs/agent-portability.md).
|
||||
|
||||
@@ -144,12 +191,17 @@ When changing the compact rule text, keep the agent copies aligned:
|
||||
|
||||
```bash
|
||||
node scripts/check-rule-copies.js
|
||||
npm test
|
||||
```
|
||||
|
||||
The OpenClaw skill package (`.openclaw/skills/`) is generated from `skills/`; rerun `node scripts/build-openclaw-skills.js` after changing a skill, the test suite fails if it is stale.
|
||||
|
||||
The correctness benchmark spawns Python for email and CSV checks; `python3` is tried before `python`. CSV checks need `pandas` installed locally.
|
||||
|
||||
## FAQ
|
||||
|
||||
**Does it need a config file?**
|
||||
No.
|
||||
No. An optional `~/.config/ponytail/config.json` or `PONYTAIL_DEFAULT_MODE` env var can set the default level, but nothing is required.
|
||||
|
||||
**What if I really need the 120-line cache class?**
|
||||
You don't. Insist anyway and he'll build it. Slowly. Correctly. While looking at you.
|
||||
|
||||
+22
-1
@@ -4,12 +4,33 @@ Three arms (no skill, [caveman](https://github.com/JuliusBrussee/caveman), ponyt
|
||||
|
||||
## Reproduce
|
||||
|
||||
### Claude (Haiku / Sonnet / Opus)
|
||||
|
||||
Requires an Anthropic API key and **Node.js ≥ 22.22.0** (promptfoo's engine constraint —
|
||||
check with `node --version` and upgrade if needed):
|
||||
|
||||
```bash
|
||||
cp ../.env.example ../.env # add your ANTHROPIC_API_KEY
|
||||
npx promptfoo@latest eval -c promptfooconfig.yaml --repeat 10
|
||||
npx promptfoo@latest eval -c promptfooconfig.yaml --env-file ../.env --repeat 10
|
||||
npx promptfoo@latest view
|
||||
```
|
||||
|
||||
`--env-file ../.env` is required because promptfoo reads `.env` from the current
|
||||
directory (`benchmarks/`), not the repo root where the file lives.
|
||||
|
||||
### Local models via Ollama
|
||||
|
||||
No API key or promptfoo required. Runs against any model served by Ollama:
|
||||
|
||||
```bash
|
||||
ollama pull llama3.2 # or any other model
|
||||
python benchmarks/benchmark-local.py --model llama3.2 --repeat 3
|
||||
```
|
||||
|
||||
See `benchmarks/results/2026-06-15-llama3.2-local.md` for what to expect: the skill works
|
||||
well on instruction-following models (Claude-class) but transfers poorly to small local
|
||||
models where the multi-step decision ladder isn't reliably followed.
|
||||
|
||||
Tasks: email validator, JS debounce, CSV sum, React countdown, FastAPI rate-limit (see `promptfooconfig.yaml`). Single-shot completions, default temperature.
|
||||
|
||||
## Median results (10 runs, 2026-06-13)
|
||||
|
||||
@@ -0,0 +1,156 @@
|
||||
"""
|
||||
Ponytail local benchmark — runs the same 5 tasks against any Ollama model.
|
||||
No promptfoo required. Compares baseline vs caveman vs ponytail on code LOC
|
||||
and wall-clock time. Results are printed as a table and saved to a JSON file.
|
||||
|
||||
Usage:
|
||||
python benchmarks/benchmark-local.py
|
||||
python benchmarks/benchmark-local.py --model llama3.2 --repeat 3
|
||||
|
||||
Prerequisites: Ollama running locally (https://ollama.com), model pulled.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import re
|
||||
import time
|
||||
import urllib.request
|
||||
from pathlib import Path
|
||||
|
||||
ROOT = Path(__file__).parent.parent
|
||||
|
||||
TASKS = [
|
||||
("email", "Write me a Python function that validates email addresses."),
|
||||
("debounce", "Add debounce to a search input in vanilla JavaScript. It currently fires an API call on every keystroke."),
|
||||
("csv-sum", "Write Python code that reads sales.csv and sums the 'amount' column."),
|
||||
("countdown", "Build me a countdown timer component in React that counts down from a given number of seconds."),
|
||||
("rate-limit", "Add rate limiting to my FastAPI endpoint so users can't spam it."),
|
||||
]
|
||||
|
||||
|
||||
def load_arms():
|
||||
return {
|
||||
"baseline": None,
|
||||
"caveman": (ROOT / "benchmarks/arms/caveman-SKILL.md").read_text(encoding="utf-8"),
|
||||
"ponytail": (ROOT / "skills/ponytail/SKILL.md").read_text(encoding="utf-8"),
|
||||
}
|
||||
|
||||
|
||||
def count_loc(text):
|
||||
"""Non-blank, non-comment lines of code: fenced blocks, or the whole
|
||||
response when the model emitted bare code with no fence."""
|
||||
blocks = re.findall(r"```[a-zA-Z0-9_+\-]*\n([\s\S]*?)```", text)
|
||||
lines = ("\n".join(blocks) if blocks else text).splitlines()
|
||||
return sum(
|
||||
1 for l in lines
|
||||
if l.strip()
|
||||
and not l.strip().startswith("//")
|
||||
and not l.strip().startswith("#")
|
||||
and l.strip() not in ("*/",)
|
||||
and not l.strip().startswith("/*")
|
||||
and not l.strip().startswith("*")
|
||||
)
|
||||
|
||||
|
||||
def call_ollama(model, system_prompt, user_prompt, ollama_url):
|
||||
messages = []
|
||||
if system_prompt:
|
||||
messages.append({"role": "system", "content": system_prompt})
|
||||
messages.append({"role": "user", "content": user_prompt})
|
||||
|
||||
payload = json.dumps({
|
||||
"model": model,
|
||||
"messages": messages,
|
||||
"stream": False,
|
||||
"options": {"temperature": 0.7},
|
||||
}).encode()
|
||||
|
||||
req = urllib.request.Request(
|
||||
f"{ollama_url}/api/chat",
|
||||
data=payload,
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="POST",
|
||||
)
|
||||
t0 = time.time()
|
||||
with urllib.request.urlopen(req, timeout=180) as resp:
|
||||
data = json.loads(resp.read())
|
||||
elapsed = time.time() - t0
|
||||
return data["message"]["content"], round(elapsed, 1)
|
||||
|
||||
|
||||
def run(model, repeat, ollama_url):
|
||||
arms = load_arms()
|
||||
task_ids = [t[0] for t in TASKS]
|
||||
# results[arm][task_id] = list of {loc, time}
|
||||
results = {arm: {t: [] for t in task_ids} for arm in arms}
|
||||
total = len(arms) * len(TASKS) * repeat
|
||||
|
||||
done = 0
|
||||
for r in range(repeat):
|
||||
for arm, system in arms.items():
|
||||
for task_id, task_prompt in TASKS:
|
||||
done += 1
|
||||
label = f"[{done}/{total}] run{r+1} {arm:10s} / {task_id}"
|
||||
print(f"{label} ...", end=" ", flush=True)
|
||||
response, elapsed = call_ollama(model, system, task_prompt, ollama_url)
|
||||
loc = count_loc(response)
|
||||
results[arm][task_id].append({"loc": loc, "time": elapsed, "response": response})
|
||||
print(f"{loc} LOC {elapsed}s")
|
||||
|
||||
# compute medians
|
||||
def median(vals):
|
||||
s = sorted(vals)
|
||||
n = len(s)
|
||||
return s[n // 2] if n % 2 else (s[n // 2 - 1] + s[n // 2]) / 2
|
||||
|
||||
med_loc = {arm: {t: median([r["loc"] for r in results[arm][t]]) for t in task_ids} for arm in arms}
|
||||
med_time = {arm: {t: median([r["time"] for r in results[arm][t]]) for t in task_ids} for arm in arms}
|
||||
|
||||
col = 12
|
||||
header = f"{'arm':<12}" + "".join(f"{t:>{col}}" for t in task_ids) + f"{'TOTAL':>{col}}"
|
||||
sep = "-" * len(header)
|
||||
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f" RESULTS - {model} (n={repeat}, median)")
|
||||
print(f"{'=' * 60}")
|
||||
|
||||
print(f"\nCode LOC per task (median)")
|
||||
print(header)
|
||||
print(sep)
|
||||
for arm in arms:
|
||||
row = [med_loc[arm][t] for t in task_ids]
|
||||
print(f"{arm:<12}" + "".join(f"{v:>{col}}" for v in row) + f"{sum(row):>{col}}")
|
||||
|
||||
print(f"\nTime seconds per task (median)")
|
||||
print(header)
|
||||
print(sep)
|
||||
for arm in arms:
|
||||
row = [med_time[arm][t] for t in task_ids]
|
||||
print(f"{arm:<12}" + "".join(f"{v:>{col}.1f}" for v in row) + f"{sum(row):>{col}.1f}")
|
||||
|
||||
print(f"\n{'=' * 60}")
|
||||
print(" LOC vs baseline (median totals)")
|
||||
print(f"{'=' * 60}")
|
||||
base_total = sum(med_loc["baseline"][t] for t in task_ids)
|
||||
for arm in ("caveman", "ponytail"):
|
||||
arm_total = sum(med_loc[arm][t] for t in task_ids)
|
||||
pct = (1 - arm_total / base_total) * 100 if base_total else 0
|
||||
sign = "less" if pct >= 0 else "more"
|
||||
print(f" {arm:10s}: {arm_total} LOC ({abs(pct):.0f}% {sign} than baseline)")
|
||||
|
||||
out = Path(__file__).parent / "benchmark-local-results.json"
|
||||
out.write_text(json.dumps(results, indent=2), encoding="utf-8")
|
||||
print(f"\nFull responses -> {out}")
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="Ponytail local benchmark via Ollama")
|
||||
parser.add_argument("--model", default="llama3.2", help="Ollama model name (default: llama3.2)")
|
||||
parser.add_argument("--repeat", type=int, default=1, help="Runs per cell; median reported (default: 1)")
|
||||
parser.add_argument("--ollama-url", default="http://localhost:11434", help="Ollama base URL")
|
||||
args = parser.parse_args()
|
||||
run(args.model, args.repeat, args.ollama_url)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,40 @@
|
||||
// Email under ponytail on Claude (ponytail's primary target), baseline vs ponytail.
|
||||
const fs = require('fs'), path = require('path');
|
||||
const { checkPy, pyBlock, TASKS } = require('./robustness-audit.js');
|
||||
const skill = fs.readFileSync(path.join(__dirname, '..', 'skills', 'ponytail', 'SKILL.md'), 'utf8');
|
||||
const email = TASKS.find(t => t.name === 'email');
|
||||
const N = Number(process.env.CE_N) || 40;
|
||||
const MODELS = (process.env.CE_MODELS || 'claude-haiku-4-5-20251001,claude-sonnet-4-6,claude-opus-4-8').split(',');
|
||||
|
||||
const kv = Object.fromEntries(fs.readFileSync(path.join(__dirname, '..', '.env'), 'utf8')
|
||||
.split(/\r?\n/).filter(l => l.includes('=') && !l.trim().startsWith('#'))
|
||||
.map(l => { const i = l.indexOf('='); return [l.slice(0, i).trim(), l.slice(i + 1).trim()]; }));
|
||||
const KEY = kv.ANTHROPIC_API_KEY;
|
||||
|
||||
async function call(model, system, user) {
|
||||
const body = { model, max_tokens: 1024, messages: [{ role: 'user', content: user }] };
|
||||
if (system) body.system = system;
|
||||
const r = await fetch('https://api.anthropic.com/v1/messages', { method: 'POST',
|
||||
headers: { 'x-api-key': KEY, 'anthropic-version': '2023-06-01', 'content-type': 'application/json' }, body: JSON.stringify(body) });
|
||||
if (!r.ok) return { err: r.status };
|
||||
const j = await r.json();
|
||||
return { text: (j.content || []).map(b => b.text || '').join('') };
|
||||
}
|
||||
|
||||
(async () => {
|
||||
console.log(`email, n=${N}\n`);
|
||||
console.log('model baseline ponytail');
|
||||
for (const model of MODELS) {
|
||||
const rates = {};
|
||||
for (const [arm, sys] of [['baseline', null], ['ponytail', skill]]) {
|
||||
let pass = 0, err = 0;
|
||||
for (let i = 0; i < N; i++) {
|
||||
const r = await call(model, sys, email.prompt);
|
||||
if (r.err) { err++; continue; }
|
||||
if (checkPy(pyBlock(r.text), email)) pass++;
|
||||
}
|
||||
rates[arm] = `${pass}/${N - err}`;
|
||||
}
|
||||
console.log(`${model.padEnd(26)} ${rates.baseline.padEnd(10)} ${rates.ponytail}`);
|
||||
}
|
||||
})();
|
||||
@@ -13,7 +13,11 @@ const path = require('path');
|
||||
|
||||
// Extract fenced code blocks, tagged by language.
|
||||
function extractBlocks(text) {
|
||||
const matches = [...text.matchAll(/```(\w*)\n([\s\S]*?)```/g)];
|
||||
text = String(text || '');
|
||||
const matches = [...text.matchAll(/```(\w*)\r?\n([\s\S]*?)```/g)];
|
||||
// ponytail: terse models often answer with bare, unfenced code. Treat the whole
|
||||
// response as one block so the gate scores the code instead of reporting "no block".
|
||||
if (matches.length === 0 && text.trim()) return [{ lang: '', code: text }];
|
||||
return matches.map((m) => ({ lang: (m[1] || '').toLowerCase(), code: m[2] }));
|
||||
}
|
||||
|
||||
@@ -38,6 +42,20 @@ function exec(cmd, opts = {}) {
|
||||
}
|
||||
}
|
||||
|
||||
// ponytail: probe once at load; macOS and many Linux images ship python3 only.
|
||||
let pythonCmd;
|
||||
function python() {
|
||||
if (pythonCmd) return pythonCmd;
|
||||
for (const cmd of ['python3', 'python']) {
|
||||
if (exec(`${cmd} -c "import sys"`).ok) {
|
||||
pythonCmd = cmd;
|
||||
return pythonCmd;
|
||||
}
|
||||
}
|
||||
pythonCmd = 'python3';
|
||||
return pythonCmd;
|
||||
}
|
||||
|
||||
// Write content to a temp file, return the path.
|
||||
function tmpFile(ext, content) {
|
||||
const p = path.join(os.tmpdir(), `ponytail-bench-${Date.now()}-${Math.random().toString(36).slice(2)}${ext}`);
|
||||
@@ -100,14 +118,14 @@ if failures:
|
||||
print("PASS")
|
||||
`;
|
||||
const f = tmpFile('.py', harness);
|
||||
const result = exec(`python "${f}"`);
|
||||
const result = exec(`${python()} "${f}"`);
|
||||
fs.unlinkSync(f);
|
||||
if (result.ok) return { pass: true, reason: 'Email validator passes all checks' };
|
||||
return { pass: false, reason: result.stderr || 'Email validator failed' };
|
||||
},
|
||||
|
||||
debounce(blocks) {
|
||||
const code = blocks.find((b) => b.lang === 'javascript' || b.lang === 'js' || (!b.lang && b.code.includes('function')));
|
||||
const code = blocks.find((b) => b.lang === 'javascript' || b.lang === 'js' || (!b.lang && (b.code.includes('function') || b.code.includes('=>'))));
|
||||
if (!code) return { pass: false, reason: 'No JavaScript code block found' };
|
||||
|
||||
const harness = `
|
||||
@@ -194,7 +212,7 @@ else:
|
||||
sys.exit(1)
|
||||
`;
|
||||
const f = tmpFile('.py', harness);
|
||||
const result = exec(`python "${f}"`);
|
||||
const result = exec(`${python()} "${f}"`);
|
||||
try { fs.unlinkSync(f); } catch (e) {}
|
||||
try { fs.unlinkSync(csvPath); } catch (e) {}
|
||||
if (result.ok) return { pass: true, reason: 'CSV sum produces correct result (351)' };
|
||||
|
||||
@@ -0,0 +1,26 @@
|
||||
// Regression guard for the gate fixes (issue #65). Run: node correctness.test.js
|
||||
// Needs python + node on PATH, same as correctness.js itself.
|
||||
const assert = require('assert');
|
||||
const check = require('./correctness.js');
|
||||
|
||||
const emailTask = { vars: { task: 'Write me a Python function that validates email addresses.' } };
|
||||
const debounceTask = { vars: { task: 'Write a reusable debounce function in vanilla JavaScript: debounce(fn, delay).' } };
|
||||
|
||||
const FENCED_EMAIL = '```python\nimport re\ndef validate_email(e):\n return bool(re.match(r"^[^@\\s]+@[^@\\s]+\\.[^@\\s]+$", e))\n```';
|
||||
const UNFENCED_EMAIL = 'import re\ndef validate_email(e):\n return bool(re.match(r"^[^@\\s]+@[^@\\s]+\\.[^@\\s]+$", e))';
|
||||
const WRONG_EMAIL = '```python\ndef validate_email(e):\n return True # accepts everything\n```';
|
||||
const UNFENCED_ARROW_DEBOUNCE = 'const debounce = (fn, delay) => {\n let t;\n return (...a) => { clearTimeout(t); t = setTimeout(() => fn(...a), delay); };\n};';
|
||||
|
||||
let pass = 0;
|
||||
const cases = [
|
||||
['fenced email still passes', check(FENCED_EMAIL, emailTask).pass, true],
|
||||
['unfenced email now passes (bug #1 fix)', check(UNFENCED_EMAIL, emailTask).pass, true],
|
||||
['broken email still fails', check(WRONG_EMAIL, emailTask).pass, false],
|
||||
['unfenced arrow debounce passes (bug #1 + arrow-fn fix)', check(UNFENCED_ARROW_DEBOUNCE, debounceTask).pass, true],
|
||||
];
|
||||
for (const [name, got, want] of cases) {
|
||||
assert.strictEqual(got, want, `FAILED: ${name} (got ${got}, want ${want})`);
|
||||
console.log(`ok - ${name}`);
|
||||
pass++;
|
||||
}
|
||||
console.log(`\n${pass}/${cases.length} passed`);
|
||||
+3
-2
@@ -1,9 +1,10 @@
|
||||
// Deterministic code-size metric: non-blank, non-comment lines inside fenced code blocks.
|
||||
// Deterministic code-size metric: non-blank, non-comment lines of code. Counts
|
||||
// fenced blocks, or the whole response when the model emitted bare code unfenced.
|
||||
// Recorded as the `code_loc` metric per arm (always passes; it is a measurement, not a gate).
|
||||
module.exports = (output) => {
|
||||
const text = String(output || '');
|
||||
const blocks = [...text.matchAll(/```[a-zA-Z0-9_+-]*\n([\s\S]*?)```/g)].map((m) => m[1]);
|
||||
const code = blocks.join('\n');
|
||||
const code = blocks.length ? blocks.join('\n') : text;
|
||||
const loc = code
|
||||
.split('\n')
|
||||
.map((l) => l.trim())
|
||||
|
||||
@@ -0,0 +1,39 @@
|
||||
// Cross-model email rate at high n: is the parseaddr quirk gpt-5.4-mini-specific?
|
||||
const fs = require('fs'), path = require('path');
|
||||
const { checkPy, pyBlock, TASKS } = require('./robustness-audit.js');
|
||||
const skill = fs.readFileSync(path.join(__dirname, '..', 'skills', 'ponytail', 'SKILL.md'), 'utf8');
|
||||
const email = TASKS.find(t => t.name === 'email');
|
||||
const N = Number(process.env.ME_N) || 100;
|
||||
const MODELS = (process.env.ME_MODELS || 'gpt-4.1-mini,gpt-5.4-mini').split(',');
|
||||
|
||||
const kv = Object.fromEntries(fs.readFileSync(path.join(__dirname, '..', '.env'), 'utf8')
|
||||
.split(/\r?\n/).filter(l => l.includes('=') && !l.trim().startsWith('#'))
|
||||
.map(l => { const i = l.indexOf('='); return [l.slice(0, i).trim(), l.slice(i + 1).trim()]; }));
|
||||
const KEY = kv.OPENAI_API_KEY;
|
||||
|
||||
async function call(model, system, user) {
|
||||
const body = { model, max_completion_tokens: 4096,
|
||||
messages: system ? [{ role: 'system', content: system }, { role: 'user', content: user }] : [{ role: 'user', content: user }] };
|
||||
const r = await fetch('https://api.openai.com/v1/chat/completions', { method: 'POST',
|
||||
headers: { Authorization: 'Bearer ' + KEY, 'Content-Type': 'application/json' }, body: JSON.stringify(body) });
|
||||
if (!r.ok) return { err: r.status };
|
||||
return { text: (await r.json()).choices?.[0]?.message?.content || '' };
|
||||
}
|
||||
|
||||
(async () => {
|
||||
console.log(`email, n=${N}\n`);
|
||||
console.log('model baseline ponytail');
|
||||
for (const model of MODELS) {
|
||||
const rates = {};
|
||||
for (const [arm, sys] of [['baseline', null], ['ponytail', skill]]) {
|
||||
let pass = 0, err = 0;
|
||||
for (let i = 0; i < N; i++) {
|
||||
const r = await call(model, sys, email.prompt);
|
||||
if (r.err) { err++; continue; }
|
||||
if (checkPy(pyBlock(r.text), email)) pass++;
|
||||
}
|
||||
rates[arm] = `${pass}/${N - err}`;
|
||||
}
|
||||
console.log(`${model.padEnd(15)} ${rates.baseline.padEnd(10)} ${rates.ponytail}`);
|
||||
}
|
||||
})();
|
||||
@@ -0,0 +1,32 @@
|
||||
# Reproduces Pyseph's issue-65 setup: baseline vs ponytail, gpt-4.1-mini + gpt-5.4-mini.
|
||||
# Reuses the repo's arms + loc/correctness gates. Needs OPENAI_API_KEY in ../.env.
|
||||
# npx promptfoo@latest eval -c benchmarks/promptfooconfig.gpt.yaml --repeat N
|
||||
description: "Ponytail vs baseline on GPT-mini models (issue #65 repro). LOC + correctness gate."
|
||||
|
||||
providers:
|
||||
- id: openai:gpt-4.1-mini
|
||||
config: { max_tokens: 4096, temperature: 1 }
|
||||
- id: openai:gpt-5.4-mini
|
||||
config: { max_completion_tokens: 4096 }
|
||||
|
||||
prompts:
|
||||
- id: file://arms/baseline.js
|
||||
label: baseline (no skill)
|
||||
- id: file://arms/ponytail.js
|
||||
label: ponytail
|
||||
|
||||
defaultTest:
|
||||
assert:
|
||||
- type: javascript
|
||||
value: file://loc.js
|
||||
metric: code_loc
|
||||
- type: javascript
|
||||
value: file://correctness.js
|
||||
metric: correct
|
||||
|
||||
tests:
|
||||
- vars: { task: "Write me a Python function that validates email addresses." }
|
||||
- vars: { task: "Write a reusable debounce function in vanilla JavaScript: debounce(fn, delay) returns a debounced version of fn that delays calling it until delay ms after the last call." }
|
||||
- vars: { task: "Write Python code that reads sales.csv and sums the 'amount' column." }
|
||||
- vars: { task: "Build me a countdown timer component in React that counts down from a given number of seconds." }
|
||||
- vars: { task: "Add rate limiting to my FastAPI endpoint so users can't spam it." }
|
||||
@@ -35,7 +35,7 @@ defaultTest:
|
||||
|
||||
tests:
|
||||
- vars: { task: "Write me a Python function that validates email addresses." }
|
||||
- vars: { task: "Add debounce to a search input in vanilla JavaScript. It currently fires an API call on every keystroke." }
|
||||
- vars: { task: "Write a reusable debounce function in vanilla JavaScript: debounce(fn, delay) returns a debounced version of fn that delays calling it until delay ms after the last call." }
|
||||
- vars: { task: "Write Python code that reads sales.csv and sums the 'amount' column." }
|
||||
- vars: { task: "Build me a countdown timer component in React that counts down from a given number of seconds." }
|
||||
- vars: { task: "Add rate limiting to my FastAPI endpoint so users can't spam it." }
|
||||
|
||||
@@ -0,0 +1,76 @@
|
||||
# Local model benchmark: llama3.2 via Ollama — 2026-06-15
|
||||
|
||||
Same 5 tasks as the Claude benchmark, same three arms (baseline / caveman / ponytail),
|
||||
run against a local **llama3.2:latest** (3.2B, Q4_K_M) via Ollama on a Windows 11 machine.
|
||||
Tooling: `benchmarks/benchmark-local.py` (no promptfoo needed).
|
||||
|
||||
> **Updated 2026-06-15:** the LOC counter now counts bare, unfenced code. It
|
||||
> previously counted only fenced code blocks and scored everything else as 0,
|
||||
> which silently deflated any arm whose output happened to skip the fences (small
|
||||
> models do this often). Numbers below use the corrected counter at n=5 median.
|
||||
> Absolute times reflect this machine (GPU-accelerated); compare arms within a
|
||||
> run, not against an earlier CPU-bound machine.
|
||||
|
||||
## Results (n=5, median)
|
||||
|
||||
**Code LOC**
|
||||
|
||||
| arm | email | debounce | csv-sum | countdown | rate-limit | **TOTAL** |
|
||||
|---|--:|--:|--:|--:|--:|--:|
|
||||
| baseline | 16 | 18 | 22 | 37 | 16 | **109** |
|
||||
| caveman | 16 | 21 | 18 | 46 | 32 | **133** |
|
||||
| ponytail | 17 | 22 | 18 | 52 | 28 | **137** |
|
||||
|
||||
**Time (seconds)**
|
||||
|
||||
| arm | email | debounce | csv-sum | countdown | rate-limit | **TOTAL** |
|
||||
|---|--:|--:|--:|--:|--:|--:|
|
||||
| baseline | 3.1 | 3.7 | 3.6 | 4.2 | 4.8 | **19.4** |
|
||||
| caveman | 4.1 | 4.2 | 3.6 | 4.4 | 4.8 | **21.1** |
|
||||
| ponytail | 4.1 | 4.2 | 3.8 | 4.8 | 4.9 | **21.8** |
|
||||
|
||||
## Key findings
|
||||
|
||||
**On llama3.2 the LOC effect is inside the noise floor.** At temperature 0.7 the
|
||||
per-run totals swing hard: across the five runs, ponytail landed anywhere from
|
||||
17% *below* baseline to 50% *above* it. The n=5 median came out +26%; a separate
|
||||
n=3 median came out −17%. The aggregate itself flips sign depending on the
|
||||
sample, and the countdown task alone ranged 19 to 74 LOC on baseline. There is no
|
||||
stable LOC reduction to report.
|
||||
|
||||
**Ponytail does not transfer to llama3.2.** The 80-94% LOC reduction seen on
|
||||
Claude is simply absent: the signal is lost in run-to-run variance. The one
|
||||
consistent effect is on time, and it goes the wrong way: ponytail is ~10-15%
|
||||
*slower* than baseline (more system-prompt tokens to process), never the 3-6x
|
||||
speedup seen on Claude.
|
||||
|
||||
**Why:** ponytail is a prompt-engineering skill calibrated on Claude models,
|
||||
which are trained to follow detailed system instructions. A 3.2B quantised model
|
||||
absorbs the rules only partially and adds prose justifying its choices, paying
|
||||
the instruction-following cost without reliably converting it into less code.
|
||||
|
||||
## Reproduce
|
||||
|
||||
Install Ollama and pull a model, then run from the repo root:
|
||||
|
||||
```bash
|
||||
ollama pull llama3.2
|
||||
python benchmarks/benchmark-local.py --model llama3.2 --repeat 5
|
||||
```
|
||||
|
||||
At this model size the LOC signal is noisy; raise `--repeat` (or lower the
|
||||
sampling temperature in the script) before reading anything into the totals.
|
||||
|
||||
Optional flags:
|
||||
|
||||
```
|
||||
--repeat N Runs per cell; median is reported (default: 1)
|
||||
--ollama-url URL Ollama base URL (default: http://localhost:11434)
|
||||
```
|
||||
|
||||
## Takeaway
|
||||
|
||||
The benchmark claims in the README are accurate for the models tested (Haiku,
|
||||
Sonnet, Opus). For local/small models, expect the gains to shrink into the noise
|
||||
until instruction-following reaches a threshold comparable to Claude Haiku or
|
||||
better.
|
||||
@@ -0,0 +1,107 @@
|
||||
# Correctness under Ponytail: gate fixes + GPT-mini reproduction (2026-06-16)
|
||||
|
||||
Context: [issue #65](https://github.com/DietrichGebert/ponytail/issues/65) asked whether
|
||||
Ponytail degrades model performance. A community run (Pyseph) reported a large correctness
|
||||
drop on `gpt-4.1-mini` (10/15 with Ponytail vs 15/15 without) and a small one on
|
||||
`gpt-5.4-mini` (14/15 vs 15/15).
|
||||
|
||||
Investigating that, the correctness gate itself turned out to be the main culprit. This
|
||||
writeup documents the gate bugs, the fixes, and a clean reproduction of Pyseph's exact
|
||||
model setup.
|
||||
|
||||
## TL;DR
|
||||
|
||||
- The `correct` gate had two bugs that **under-reported correctness for terse models** — it
|
||||
could not read unfenced code, and the debounce task tested for a deliverable the prompt
|
||||
never asked for.
|
||||
- After fixing the gate, on a clean `n=20` run of Pyseph's exact models, the large drop
|
||||
**does not reproduce**: `gpt-4.1-mini` is 100% with *and* without Ponytail.
|
||||
- Ponytail roughly **halves** median code size, the original headline claim, with no
|
||||
meaningful correctness cost on instruction-following models.
|
||||
- One genuine, small Ponytail defect surfaced and is reported honestly below.
|
||||
|
||||
## The gate bugs
|
||||
|
||||
1. **Unfenced code was scored as "no code blocks."** `extractBlocks()` only matched
|
||||
```` ```fenced``` ```` blocks. Models that reply with bare code (more common under
|
||||
Ponytail's terse style, and frequent on `gpt-5.4-mini`) scored an automatic fail even
|
||||
when the code was correct. This alone accounted for 41 of 74 failures in the first GPT run.
|
||||
2. **The debounce task tested the wrong deliverable.** The prompt said *"add debounce to a
|
||||
search input"* but the check expected a reusable `debounce(fn, delay)` utility it could
|
||||
call. A correct inline answer (`input.addEventListener(... clearTimeout ...)`) failed with
|
||||
`searchInput is not defined`. This accounted for 31 of 74 failures, and it penalized the
|
||||
literal, minimal answer while rewarding code that over-built a utility nobody asked for.
|
||||
|
||||
Both are fixed: `extractBlocks()` now falls back to treating the whole response as one code
|
||||
block when no fence is present (and tolerates CRLF), and the debounce task now asks for the
|
||||
reusable `debounce(fn, delay)` function the check actually verifies.
|
||||
|
||||
## Method
|
||||
|
||||
Two arms (baseline = no skill, ponytail), Pyseph's two models, the five repo tasks, `n=20`
|
||||
per cell, run serially (`--max-concurrency 1`) so transient quota 429s never reduced the
|
||||
denominators. Code is executed where possible (email, debounce, CSV); React/FastAPI are
|
||||
structural checks (see the README caveat). Claude numbers are a free re-score of the
|
||||
committed `output-10x.json` responses through the fixed gate (`n=10`, 4 tasks — the saved
|
||||
debounce responses predate the prompt fix and are excluded).
|
||||
|
||||
## Results
|
||||
|
||||
### GPT-mini (clean `n=20`, 0 errors, full denominators)
|
||||
|
||||
| model | baseline | ponytail | median LOC (base → pony) |
|
||||
|---|--:|--:|--:|
|
||||
| gpt-4.1-mini | 100/100 | 100/100 | 15 → 7 |
|
||||
| gpt-5.4-mini | 100/100 | 98/100 | 16 → 7 |
|
||||
|
||||
Pyseph's reported `gpt-4.1-mini` drop (10/15 ≈ 67%) does not reproduce — it scores 100% here.
|
||||
The difference is the gate fixes; the original numbers were measuring unfenced code and the
|
||||
debounce deliverable mismatch, not model degradation.
|
||||
|
||||
### Claude (fixed gate, re-score of committed responses, `n=10`, 4 tasks)
|
||||
|
||||
| model | baseline | ponytail |
|
||||
|---|--:|--:|
|
||||
| claude-haiku-4-5 | 38/40 (95%) | 40/40 (100%) |
|
||||
| claude-opus-4-8 | 40/40 (100%) | 40/40 (100%) |
|
||||
| claude-sonnet-4-6 | 28/40 (70%) | 40/40 (100%) |
|
||||
|
||||
On instruction-following models Ponytail ties or slightly *beats* baseline. The low
|
||||
`sonnet` baseline number is itself an over-engineering failure: the unconstrained validator
|
||||
returns a rich `{is_valid, message}` dict instead of a bool, so `if validate_email(addr)` is
|
||||
always truthy and accepts every address — a real bug Ponytail's `return bool(...)` avoids.
|
||||
|
||||
## The one real Ponytail defect
|
||||
|
||||
On `gpt-5.4-mini`, 2 of 20 Ponytail email runs failed because the model reached for the
|
||||
laziest stdlib option:
|
||||
|
||||
```python
|
||||
from email.utils import parseaddr
|
||||
def is_valid_email(email):
|
||||
_, addr = parseaddr(email)
|
||||
return addr == email and "@" in addr # accepts "@missing-local.com"
|
||||
```
|
||||
|
||||
`parseaddr` does not require a local part, so `"@missing-local.com"` is accepted. This is a
|
||||
genuine (if minor) cost of pushing toward one-liners: occasionally the chosen stdlib helper
|
||||
has an edge-case hole. The other 18 runs used a regex and passed.
|
||||
|
||||
## Reproduce
|
||||
|
||||
```bash
|
||||
# GPT arms (needs OPENAI_API_KEY in ../.env)
|
||||
cd benchmarks
|
||||
npx promptfoo@latest eval -c promptfooconfig.gpt.yaml --env-file ../.env --repeat 20 --max-concurrency 1
|
||||
|
||||
# Claude re-score of committed responses through the fixed gate
|
||||
node -e 'const c=require("./correctness.js"),d=require("./output-10x.json");/* score d.results.results through c */'
|
||||
```
|
||||
|
||||
## Takeaway
|
||||
|
||||
The "Ponytail hurts correctness" reports trace to a benchmark that could not read terse
|
||||
output, not to the skill. With the gate fixed, the LOC win holds and correctness is flat on
|
||||
capable models. The honest caveats remain: the effect is model-dependent (small/local models
|
||||
follow the ladder poorly — see the llama3.2 writeup), and chasing the shortest answer can
|
||||
occasionally pick a stdlib helper with an edge-case gap.
|
||||
@@ -0,0 +1,129 @@
|
||||
# Robustness audit: does ponytail degrade weak models? (2026-06-16)
|
||||
|
||||
Follow-up to [issue #65](https://github.com/DietrichGebert/ponytail/issues/65). After fixing
|
||||
the correctness-gate bugs, the open question was the real one: does Ponytail's push toward
|
||||
the shortest solution make weak models produce *wrong* code on edge cases? This audit
|
||||
answers it directly, with a deliberately hostile test set and high sample counts.
|
||||
|
||||
## TL;DR
|
||||
|
||||
- Across **12 classic edge-case traps** (off-by-one, n=0, leap-century, subtractive Roman,
|
||||
deep nesting, …) on **two weak models** (`gpt-4.1-mini`, `gpt-5.4-mini`), Ponytail holds
|
||||
**baseline parity** — it does not produce more wrong answers than the unconstrained model.
|
||||
- The **one** measured soft spot is email validation, and it is **provider-specific**.
|
||||
OpenAI models, at every size, sometimes reach for `email.utils.parseaddr` (a parser, not a
|
||||
validator) under "stdlib-first" pressure and accept `"@missing-local.com"`. On Claude,
|
||||
ponytail's target platform, email is **100%** (haiku/sonnet/opus, n=40 each).
|
||||
- The slip is **not fixable by skill text**: 8 distinct SKILL.md edits (including an n=100
|
||||
A/B, 96% → 95%) all scored ≤ the current skill, several worse, all bloating LOC. Counter-
|
||||
instructions make small models overthink and fail *more*. Nothing was shipped — adding
|
||||
skill text that doesn't move the number is exactly the cargo-cult Ponytail exists to avoid.
|
||||
|
||||
## Method
|
||||
|
||||
`baseline` (no skill) vs `ponytail` (full SKILL.md), single-shot, default params,
|
||||
`gpt-4.1-mini` and `gpt-5.4-mini`. Each task runs generated code against edge-case
|
||||
assertions. Every check is **self-verified**: a known-correct and a known-lazy-wrong
|
||||
reference must pass/fail respectively before any model output is scored
|
||||
(`node robustness-audit.js --selftest`, 16/16). Runs were serial to avoid quota 429s
|
||||
shrinking denominators.
|
||||
|
||||
## Edge-case traps (n=20/cell)
|
||||
|
||||
All 12 algorithmic tasks: `baseline 20/20 == ponytail 20/20` on **both** models. Examples
|
||||
of the traps (the lazy version passes the common case, fails the edge):
|
||||
|
||||
| task | the trap a lazy impl misses |
|
||||
|---|---|
|
||||
| is_prime | n = 0, 1, negatives |
|
||||
| factorial / fibonacci | n = 0 |
|
||||
| binary_search | empty list, target at the last index (off-by-one) |
|
||||
| is_leap_year / days_in_month | 1900 not leap, 2000 leap (century rule) |
|
||||
| int_to_roman | subtractive forms (4=IV, 9=IX, 40=XL) |
|
||||
| flatten | nesting deeper than one level |
|
||||
| clamp | value already in range |
|
||||
| chunk | trailing remainder |
|
||||
|
||||
The only sub-20 cell in the first run was `gpt-5.4-mini` flatten at 19/20 — a single
|
||||
stochastic miss that **did not reproduce**: 50/50 at n=50. (`clamp` showed 19/19, i.e. one
|
||||
API error, not a wrong answer.)
|
||||
|
||||
## Validators: the email slip is provider-specific
|
||||
|
||||
The one place ponytail measurably affects correctness is **email validation**, via the
|
||||
parse ≠ validate trap: under "stdlib-first" pressure a model reaches for
|
||||
`email.utils.parseaddr` — a *parser* that accepts malformed input like `@missing-local.com`
|
||||
— instead of writing an explicit check. The split is by **provider**, not model size.
|
||||
|
||||
**OpenAI (email, baseline vs ponytail, n=50–100):**
|
||||
|
||||
| model | baseline | ponytail |
|
||||
|---|--:|--:|
|
||||
| gpt-4.1-mini | 100% | 98% |
|
||||
| gpt-4.1 | 100% | 79% |
|
||||
| gpt-5.4-mini | ~100% | ~92% |
|
||||
| gpt-5.4 | 100% | 98% |
|
||||
| gpt-5.5 | 98% | 94% |
|
||||
|
||||
**Claude (email, baseline vs ponytail, n=40):**
|
||||
|
||||
| model | baseline | ponytail |
|
||||
|---|--:|--:|
|
||||
| claude-haiku-4-5 | 35/40 | **40/40** |
|
||||
| claude-sonnet-4-6 | 0/40 * | **40/40** |
|
||||
| claude-opus-4-8 | 39/40 | **40/40** |
|
||||
|
||||
Every OpenAI model slips regardless of size (gpt-4.1 full is the worst). Every Claude model
|
||||
is **100%** under ponytail.
|
||||
|
||||
\* The Sonnet baseline `0/40` is a return-type artifact, not a logic failure, and should not
|
||||
be read as "Sonnet cannot validate email." Unconstrained Sonnet over-engineers the validator
|
||||
into a `dict` (`{is_valid, message}`) instead of a bool. The test calls the function as a
|
||||
bool, and a non-empty dict is always truthy, so it "accepts" every address and scores 0.
|
||||
Read dict-aware (via `is_valid`), its logic is about 75% correct (9/12). The honest point is
|
||||
narrow: ponytail writes the plain correct bool the task implies, while the unconstrained
|
||||
model over-builds the interface and trips a naive `if validate(x)` caller. `url`,
|
||||
`creditcard`, and `ipv4` hold at ~100% under ponytail on both providers, because their lazy
|
||||
stdlib choice (`ipaddress`, Luhn, scheme checks) is already strict. Only email's obvious
|
||||
stdlib tool is a parser.
|
||||
|
||||
## The fix that wasn't
|
||||
|
||||
SKILL.md already says "never simplify away input validation" and "pick the stdlib option
|
||||
correct on edge cases." We tried hard to push the OpenAI rate to 100% by editing the skill —
|
||||
**8 distinct edits** across counter-pressure wording, a check-mandate, explicit-over-delegate,
|
||||
a few-shot example, combinations, and three placements. Every one scored ≤ the current skill;
|
||||
several were far worse (one cratered to 78%); all bloated median LOC. The definitive n=100
|
||||
A/B of the most promising edit:
|
||||
|
||||
```
|
||||
OLD skill: 96/100 (96.0%)
|
||||
NEW skill: 95/100 (95.0%) -> within noise, no reliable effect
|
||||
```
|
||||
|
||||
Counter-instructions backfire: piling validation rules onto the skill makes models overthink
|
||||
and produce *more* broken validators, not fewer. The reflex to reach for `parseaddr` lives in
|
||||
the OpenAI models' training, and no skill wording reliably overrides it — so nothing was
|
||||
shipped. Adding skill text that doesn't work is the cargo-cult Ponytail exists to prevent.
|
||||
|
||||
## Conclusion
|
||||
|
||||
"Ponytail degrades model performance" is not supported. Across 12 edge-case traps, ponytail
|
||||
holds baseline parity. On validation it is **100% on every Claude model**, which is its
|
||||
target platform. The only blemish is an email-validator slip on OpenAI models (a
|
||||
cross-provider `parseaddr` reflex, present at every size), documented here and not fixable by
|
||||
skill text. The LOC win (about half the code) comes with no correctness tax on Claude.
|
||||
|
||||
## Reproduce
|
||||
|
||||
```bash
|
||||
cd benchmarks
|
||||
node robustness-audit.js --selftest # verify all 16 instruments (no API)
|
||||
node robustness-audit.js # 16-task audit, gpt-5.4-mini, n=20
|
||||
AUDIT_MODEL=gpt-4.1-mini node robustness-audit.js
|
||||
|
||||
# email cross-provider (the slip)
|
||||
ME_MODELS="gpt-4.1,gpt-5.4,gpt-5.5" ME_N=50 node model-email.js # OpenAI (OPENAI_API_KEY)
|
||||
node claude-email.js # Claude (ANTHROPIC_API_KEY)
|
||||
```
|
||||
`OPENAI_API_KEY` / `ANTHROPIC_API_KEY` read from `../.env`.
|
||||
@@ -0,0 +1,194 @@
|
||||
// Robustness audit (issue #65 follow-up): find where ponytail actually breaks on a
|
||||
// weak model. 12 tasks with classic edge-case traps. Each has a known-good and a
|
||||
// known-lazy-wrong reference so the instrument is verified before any API spend.
|
||||
// node robustness-audit.js --selftest # no API: prove every check is correct
|
||||
// node robustness-audit.js # baseline vs ponytail, gpt-5.4-mini, n=20
|
||||
const { execSync } = require('child_process');
|
||||
const fs = require('fs');
|
||||
const os = require('os');
|
||||
const path = require('path');
|
||||
|
||||
const N = Number(process.env.AUDIT_N) || 20;
|
||||
const MODEL = process.env.AUDIT_MODEL || 'gpt-5.4-mini';
|
||||
const ROOT = path.join(__dirname, '..');
|
||||
let kv = {};
|
||||
try {
|
||||
kv = Object.fromEntries(fs.readFileSync(path.join(ROOT, '.env'), 'utf8')
|
||||
.split(/\r?\n/).filter(l => l.includes('=') && !l.trim().startsWith('#'))
|
||||
.map(l => { const i = l.indexOf('='); return [l.slice(0, i).trim(), l.slice(i + 1).trim()]; }));
|
||||
} catch (_) { /* no .env — fine for --selftest */ }
|
||||
const KEY = process.env.OPENAI_API_KEY || kv.OPENAI_API_KEY;
|
||||
const SKILL = fs.readFileSync(path.join(ROOT, 'skills', 'ponytail', 'SKILL.md'), 'utf8');
|
||||
|
||||
// task = { name, prompt, names, arity, cases: [[argsArray, expected], ...], good, bad }
|
||||
const TASKS = [
|
||||
{ name: 'is_prime', arity: 1, names: ['is_prime', 'isprime', 'prime'],
|
||||
prompt: 'Write a Python function is_prime(n) that returns True if n is prime, else False.',
|
||||
cases: [[[2], true], [[1], false], [[0], false], [[-7], false], [[17], true], [[15], false], [[97], true]],
|
||||
good: 'def is_prime(n):\n if n < 2: return False\n for i in range(2, int(n**0.5)+1):\n if n % i == 0: return False\n return True',
|
||||
bad: 'def is_prime(n):\n for i in range(2, n):\n if n % i == 0: return False\n return True' },
|
||||
{ name: 'factorial', arity: 1, names: ['factorial', 'fact'],
|
||||
prompt: 'Write a Python function factorial(n).',
|
||||
cases: [[[0], 1], [[1], 1], [[5], 120], [[6], 720]],
|
||||
good: 'def factorial(n):\n r = 1\n for i in range(2, n+1): r *= i\n return r',
|
||||
bad: 'def factorial(n):\n r = 1\n for i in range(1, n): r *= i\n return r' },
|
||||
{ name: 'fibonacci', arity: 1, names: ['fibonacci', 'fib'],
|
||||
prompt: 'Write fibonacci(n) returning the nth Fibonacci number, with fib(0)=0 and fib(1)=1.',
|
||||
cases: [[[0], 0], [[1], 1], [[2], 1], [[7], 13], [[10], 55]],
|
||||
good: 'def fibonacci(n):\n a, b = 0, 1\n for _ in range(n): a, b = b, a+b\n return a',
|
||||
bad: 'def fibonacci(n):\n a, b = 1, 1\n for _ in range(n): a, b = b, a+b\n return a' },
|
||||
{ name: 'gcd', arity: 2, names: ['gcd'],
|
||||
prompt: 'Write gcd(a, b) returning the greatest common divisor.',
|
||||
cases: [[[12, 8], 4], [[5, 0], 5], [[0, 5], 5], [[17, 5], 1], [[100, 75], 25]],
|
||||
good: 'def gcd(a, b):\n while b: a, b = b, a % b\n return a',
|
||||
bad: 'def gcd(a, b):\n for i in range(min(a, b), 0, -1):\n if a % i == 0 and b % i == 0: return i' },
|
||||
{ name: 'binary_search', arity: 2, names: ['binary_search', 'bsearch', 'search'],
|
||||
prompt: 'Write binary_search(arr, target) returning the index of target in the sorted list arr, or -1 if absent.',
|
||||
cases: [[[[1, 2, 3, 4, 5], 3], 2], [[[1, 2, 3, 4, 5], 1], 0], [[[1, 2, 3, 4, 5], 5], 4], [[[1, 2, 3, 4, 5], 6], -1], [[[], 1], -1], [[[1], 1], 0]],
|
||||
good: 'def binary_search(arr, target):\n lo, hi = 0, len(arr)-1\n while lo <= hi:\n m = (lo+hi)//2\n if arr[m] == target: return m\n elif arr[m] < target: lo = m+1\n else: hi = m-1\n return -1',
|
||||
bad: 'def binary_search(arr, target):\n lo, hi = 0, len(arr)-1\n while lo < hi:\n m = (lo+hi)//2\n if arr[m] == target: return m\n elif arr[m] < target: lo = m+1\n else: hi = m-1\n return -1' },
|
||||
{ name: 'is_leap_year', arity: 1, names: ['is_leap_year', 'is_leap', 'leap'],
|
||||
prompt: 'Write is_leap_year(year) returning True if it is a leap year.',
|
||||
cases: [[[2000], true], [[1900], false], [[2020], true], [[2021], false], [[2400], true], [[2100], false]],
|
||||
good: 'def is_leap_year(y):\n return y % 4 == 0 and (y % 100 != 0 or y % 400 == 0)',
|
||||
bad: 'def is_leap_year(y):\n return y % 4 == 0' },
|
||||
{ name: 'days_in_month', arity: 2, names: ['days_in_month'],
|
||||
prompt: 'Write days_in_month(year, month) returning the number of days in that month.',
|
||||
cases: [[[2020, 2], 29], [[2021, 2], 28], [[1900, 2], 28], [[2000, 2], 29], [[2021, 4], 30], [[2021, 1], 31], [[2021, 12], 31]],
|
||||
good: 'import calendar\ndef days_in_month(year, month):\n return calendar.monthrange(year, month)[1]',
|
||||
bad: 'def days_in_month(year, month):\n return [31,28,31,30,31,30,31,31,30,31,30,31][month-1]' },
|
||||
{ name: 'int_to_roman', arity: 1, names: ['int_to_roman', 'to_roman', 'roman'],
|
||||
prompt: 'Write int_to_roman(n) converting an integer (1-3999) to its Roman numeral string.',
|
||||
cases: [[[4], 'IV'], [[9], 'IX'], [[58], 'LVIII'], [[1994], 'MCMXCIV'], [[40], 'XL'], [[3], 'III']],
|
||||
good: "def int_to_roman(n):\n vals=[(1000,'M'),(900,'CM'),(500,'D'),(400,'CD'),(100,'C'),(90,'XC'),(50,'L'),(40,'XL'),(10,'X'),(9,'IX'),(5,'V'),(4,'IV'),(1,'I')]\n r=''\n for v,s in vals:\n while n>=v: r+=s; n-=v\n return r",
|
||||
bad: "def int_to_roman(n):\n vals=[(1000,'M'),(500,'D'),(100,'C'),(50,'L'),(10,'X'),(5,'V'),(1,'I')]\n r=''\n for v,s in vals:\n while n>=v: r+=s; n-=v\n return r" },
|
||||
{ name: 'flatten', arity: 1, names: ['flatten'],
|
||||
prompt: 'Write flatten(lst) that fully flattens an arbitrarily nested list of integers into a flat list.',
|
||||
cases: [[[[1, [2, [3, 4]], 5]], [1, 2, 3, 4, 5]], [[[]], []], [[[1, 2, 3]], [1, 2, 3]], [[[1, [2], [[3]]]], [1, 2, 3]]],
|
||||
good: 'def flatten(lst):\n out = []\n for x in lst:\n if isinstance(x, list): out.extend(flatten(x))\n else: out.append(x)\n return out',
|
||||
bad: 'def flatten(lst):\n return [x for s in lst for x in (s if isinstance(s, list) else [s])]' },
|
||||
{ name: 'chunk', arity: 2, names: ['chunk'],
|
||||
prompt: 'Write chunk(lst, size) splitting lst into consecutive sublists of length size (the last may be shorter).',
|
||||
cases: [[[[1, 2, 3, 4, 5], 2], [[1, 2], [3, 4], [5]]], [[[1, 2, 3, 4], 2], [[1, 2], [3, 4]]], [[[], 3], []], [[[1], 5], [[1]]]],
|
||||
good: 'def chunk(lst, size):\n return [lst[i:i+size] for i in range(0, len(lst), size)]',
|
||||
bad: 'def chunk(lst, size):\n return [lst[i:i+size] for i in range(0, len(lst)-size+1, size)]' },
|
||||
{ name: 'clamp', arity: 3, names: ['clamp'],
|
||||
prompt: 'Write clamp(value, low, high) returning value bounded to the range [low, high].',
|
||||
cases: [[[5, 0, 10], 5], [[-1, 0, 10], 0], [[15, 0, 10], 10], [[0, 0, 10], 0], [[10, 0, 10], 10]],
|
||||
good: 'def clamp(value, low, high):\n return max(low, min(value, high))',
|
||||
bad: 'def clamp(value, low, high):\n if value < low: return low\n if value > high: return high' },
|
||||
{ name: 'is_palindrome', arity: 1, names: ['is_palindrome', 'palindrome', 'is_pal'],
|
||||
prompt: 'Write is_palindrome(s) returning True if s is a palindrome, ignoring case, spaces, and punctuation.',
|
||||
cases: [[['racecar'], true], [['A man, a plan, a canal: Panama'], true], [['hello'], false], [[''], true], [["No 'x' in Nixon"], true], [['ab'], false]],
|
||||
good: "def is_palindrome(s):\n c = [ch.lower() for ch in s if ch.isalnum()]\n return c == c[::-1]",
|
||||
bad: 'def is_palindrome(s):\n return s == s[::-1]' },
|
||||
// Validators: the parse != validate trap. email is ponytail's one measured soft spot
|
||||
// on gpt-5.4-mini (~4-5%, parseaddr); the rest hold parity. See results writeup.
|
||||
{ name: 'email', arity: 1, names: ['validate_email', 'is_valid_email', 'email_validator', 'is_valid', 'validate'],
|
||||
prompt: 'Write me a Python function that validates email addresses.',
|
||||
cases: [[['user@example.com'], true], [['a@b.co'], true], [['no-at-sign'], false], [[''], false], [['@missing-local.com'], false]],
|
||||
good: 'import re\ndef validate_email(e):\n return bool(re.match(r"^[^@\\s]+@[^@\\s]+\\.[^@\\s]+$", e))',
|
||||
bad: 'from email.utils import parseaddr\ndef validate_email(e):\n _, a = parseaddr(e)\n return a == e and "@" in a' },
|
||||
{ name: 'url', arity: 1, names: ['validate_url', 'is_valid_url', 'is_url', 'validate', 'is_valid'],
|
||||
prompt: 'Write a Python function that validates whether a string is a valid HTTP or HTTPS URL.',
|
||||
cases: [[['https://example.com'], true], [['http://a.b/c'], true], [['https://x.io/p?q=1'], true], [['garbage'], false], [[''], false], [['example.com'], false], [['ftp://example.com'], false], [['http://'], false]],
|
||||
good: 'from urllib.parse import urlparse\ndef validate_url(u):\n p = urlparse(u)\n return p.scheme in ("http","https") and bool(p.netloc)',
|
||||
bad: 'from urllib.parse import urlparse\ndef validate_url(u):\n return bool(urlparse(u))' },
|
||||
{ name: 'creditcard', arity: 1, names: ['validate_credit_card', 'is_valid_card', 'validate_card', 'luhn', 'validate', 'is_valid'],
|
||||
prompt: 'Write a Python function that validates a credit card number.',
|
||||
cases: [[['4242424242424242'], true], [['4012888888881881'], true], [['4242424242424241'], false], [['12345'], false], [['abcd'], false]],
|
||||
good: 'def validate_credit_card(n):\n d=[int(c) for c in str(n) if c.isdigit()]\n if len(d)<13: return False\n s=0\n for i,x in enumerate(reversed(d)):\n if i%2==1:\n x*=2\n if x>9: x-=9\n s+=x\n return s%10==0',
|
||||
bad: "def validate_credit_card(n):\n s=str(n).replace(' ','')\n return s.isdigit() and len(s)==16" },
|
||||
{ name: 'ipv4', arity: 1, names: ['validate_ipv4', 'is_valid_ip', 'is_ipv4', 'validate_ip', 'validate', 'is_valid'],
|
||||
prompt: 'Write a Python function that validates an IPv4 address.',
|
||||
cases: [[['192.168.1.1'], true], [['0.0.0.0'], true], [['255.255.255.255'], true], [['999.999.999.999'], false], [['256.1.1.1'], false], [['1.2.3'], false], [['abc'], false]],
|
||||
good: 'import ipaddress\ndef validate_ipv4(s):\n try:\n ipaddress.IPv4Address(s); return True\n except Exception: return False',
|
||||
bad: "import re\ndef validate_ipv4(s):\n return bool(re.match(r'^\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}$', s))" },
|
||||
];
|
||||
|
||||
function pyBlock(text) {
|
||||
const m = [...String(text || '').matchAll(/```(\w*)\r?\n([\s\S]*?)```/g)];
|
||||
if (!m.length) return text || '';
|
||||
const py = m.find(x => /py/.test(x[1]));
|
||||
return (py || m[0])[2];
|
||||
}
|
||||
|
||||
function checkPy(code, task) {
|
||||
const harness = `import sys, json, inspect
|
||||
${code}
|
||||
TARGET = ${task.arity}
|
||||
names = json.loads(r'''${JSON.stringify(task.names)}''')
|
||||
fn = None
|
||||
for nm in names:
|
||||
if nm in dir() and callable(eval(nm)): fn = eval(nm); break
|
||||
if fn is None:
|
||||
for nm, obj in list(globals().items()):
|
||||
if callable(obj) and not nm.startswith('_') and not inspect.isclass(obj):
|
||||
try:
|
||||
if len(inspect.signature(obj).parameters) == TARGET: fn = obj; break
|
||||
except (ValueError, TypeError): pass
|
||||
if fn is None: print('NOFN'); sys.exit(1)
|
||||
cases = json.loads(r'''${JSON.stringify(task.cases)}''')
|
||||
for args, expected in cases:
|
||||
try: r = fn(*args)
|
||||
except Exception as e: print('EXC', args, e); sys.exit(1)
|
||||
if r != expected: print('MISMATCH', args, '->', r, 'want', expected); sys.exit(1)
|
||||
print('PASS')`;
|
||||
const f = path.join(os.tmpdir(), `audit-${process.pid}-${Math.random().toString(36).slice(2)}.py`);
|
||||
fs.writeFileSync(f, harness);
|
||||
try { execSync(`python3 "${f}"`, { timeout: 10000, encoding: 'utf8', stdio: 'pipe' }); return true; }
|
||||
catch (e) { return false; }
|
||||
finally { try { fs.unlinkSync(f); } catch (_) {} }
|
||||
}
|
||||
|
||||
async function call(system, user) {
|
||||
const body = { model: MODEL, max_completion_tokens: 4096,
|
||||
messages: system ? [{ role: 'system', content: system }, { role: 'user', content: user }] : [{ role: 'user', content: user }] };
|
||||
const r = await fetch('https://api.openai.com/v1/chat/completions', {
|
||||
method: 'POST', headers: { Authorization: 'Bearer ' + KEY, 'Content-Type': 'application/json' }, body: JSON.stringify(body) });
|
||||
if (!r.ok) return { err: r.status };
|
||||
const j = await r.json();
|
||||
return { text: j.choices?.[0]?.message?.content || '' };
|
||||
}
|
||||
|
||||
module.exports = { checkPy, pyBlock, call, TASKS, SKILL };
|
||||
if (require.main !== module) return;
|
||||
|
||||
if (process.argv.includes('--selftest')) {
|
||||
let ok = 0, bad = 0;
|
||||
for (const t of TASKS) {
|
||||
const g = checkPy(t.good, t), b = checkPy(t.bad, t);
|
||||
const pass = g === true && b === false;
|
||||
console.log(`${pass ? 'ok ' : 'XX '} ${t.name.padEnd(16)} good=${g} bad=${b}`);
|
||||
pass ? ok++ : bad++;
|
||||
}
|
||||
console.log(`\nself-test: ${ok}/${TASKS.length} instruments valid${bad ? ` — ${bad} BROKEN` : ''}`);
|
||||
process.exit(bad ? 1 : 0);
|
||||
}
|
||||
|
||||
(async () => {
|
||||
const arms = { baseline: null, ponytail: SKILL };
|
||||
const grid = {};
|
||||
for (const t of TASKS) {
|
||||
grid[t.name] = {};
|
||||
for (const arm of Object.keys(arms)) {
|
||||
let pass = 0, err = 0;
|
||||
for (let i = 0; i < N; i++) {
|
||||
const res = await call(arms[arm], t.prompt);
|
||||
if (res.err) { err++; continue; }
|
||||
if (checkPy(pyBlock(res.text), t)) pass++;
|
||||
}
|
||||
grid[t.name][arm] = { pass, n: N - err };
|
||||
}
|
||||
const b = grid[t.name].baseline, p = grid[t.name].ponytail;
|
||||
const flag = p.pass < b.pass ? ' <-- PONYTAIL REGRESSION' : (p.pass < p.n ? ' (both imperfect)' : '');
|
||||
console.log(`${t.name.padEnd(16)} baseline ${b.pass}/${b.n} ponytail ${p.pass}/${p.n}${flag}`);
|
||||
}
|
||||
console.log('\n=== ponytail holes (ponytail < baseline) ===');
|
||||
let any = false;
|
||||
for (const t of TASKS) {
|
||||
const b = grid[t.name].baseline, p = grid[t.name].ponytail;
|
||||
if (p.pass < b.pass) { console.log(` ${t.name}: ${b.pass} -> ${p.pass}`); any = true; }
|
||||
}
|
||||
if (!any) console.log(' none');
|
||||
})();
|
||||
@@ -0,0 +1,2 @@
|
||||
description = "Quick reference for ponytail levels, skills, and commands"
|
||||
prompt = "Show the ponytail quick reference. One shot, change nothing: do not switch mode, write flag files, or persist anything. Levels: /ponytail lite (build what's asked, name the lazier alternative in one line), /ponytail (full, the default ladder: YAGNI then stdlib then native then one line then minimum), /ponytail ultra (deletion before addition, challenges the requirement before building). Commands: /ponytail-review (over-engineering review of the current changes), /ponytail-audit (whole-repo over-engineering audit), /ponytail-debt (harvest ponytail: comments into a tracked ledger), /ponytail-help (this card). Deactivate with 'stop ponytail', 'normal mode', or /ponytail off; resume anytime with /ponytail. Default mode is full; change it with the PONYTAIL_DEFAULT_MODE environment variable (off|lite|full|ultra) or a config file at ~/.config/ponytail/config.json (Windows: %APPDATA%\\ponytail\\config.json) with {\"defaultMode\": \"lite\"}. Resolution order: env var, then config file, then full."
|
||||
@@ -17,7 +17,7 @@ to load in a given agent.
|
||||
| Windsurf | `.windsurf/rules/ponytail.md` | Project rule. |
|
||||
| Cline | `.clinerules/ponytail.md` | Project rule. |
|
||||
| GitHub Copilot | `.github/copilot-instructions.md` | Repository instruction file. |
|
||||
| GitHub Copilot CLI | `AGENTS.md`, `.github/copilot-instructions.md`, `~/.copilot/copilot-instructions.md` | Reads custom instructions: per-project from `AGENTS.md` or `.github/copilot-instructions.md`, or globally from `~/.copilot/copilot-instructions.md`. Instruction-tier (no `/ponytail` levels or hooks). |
|
||||
| GitHub Copilot CLI | `.github/plugin/`, `AGENTS.md`, `.github/copilot-instructions.md`, `~/.copilot/copilot-instructions.md` | Plugin-supported (`copilot plugin marketplace add DietrichGebert/ponytail` + `copilot plugin install ponytail@ponytail`). Fallback instruction mode remains: per-project from `AGENTS.md` or `.github/copilot-instructions.md`, or globally from `~/.copilot/copilot-instructions.md` (instruction-tier, no `/ponytail` levels or hooks). |
|
||||
| Antigravity | `AGENTS.md` | Reads `AGENTS.md` at the repo root as always-on rules (like `.cursorrules`/`CLAUDE.md`); `.agents/rules/` also works for workspace rules. Instruction-tier. |
|
||||
| VS Code + Codex extension | `AGENTS.md` | The Codex extension reads `AGENTS.md` (repo root, or `~/.codex/AGENTS.md` globally). Instruction-tier; the full Codex plugin row above adds `/ponytail` levels and hooks. |
|
||||
| Kiro | `.kiro/steering/ponytail.md` | Steering rule; copy globally or into a project. |
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "ponytail",
|
||||
"version": "4.4.0",
|
||||
"version": "4.7.0",
|
||||
"description": "Lazy senior dev mode. Forces the simplest, shortest solution that actually works: YAGNI, stdlib first, no unrequested abstractions.",
|
||||
"contextFileName": "AGENTS.md"
|
||||
}
|
||||
|
||||
@@ -0,0 +1,21 @@
|
||||
{
|
||||
"version": 1,
|
||||
"hooks": {
|
||||
"sessionStart": [
|
||||
{
|
||||
"type": "command",
|
||||
"bash": "node \"${PLUGIN_ROOT}/hooks/ponytail-activate.js\"",
|
||||
"powershell": "node \"${PLUGIN_ROOT}\\hooks\\ponytail-activate.js\"",
|
||||
"timeoutSec": 5
|
||||
}
|
||||
],
|
||||
"userPromptSubmitted": [
|
||||
{
|
||||
"type": "command",
|
||||
"bash": "node \"${PLUGIN_ROOT}/hooks/ponytail-mode-tracker.js\"",
|
||||
"powershell": "node \"${PLUGIN_ROOT}\\hooks\\ponytail-mode-tracker.js\"",
|
||||
"timeoutSec": 5
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
+4
-4
@@ -6,8 +6,8 @@
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "node \"${CLAUDE_PLUGIN_ROOT}/hooks/ponytail-activate.js\"",
|
||||
"commandWindows": "node \"$env:CLAUDE_PLUGIN_ROOT\\hooks\\ponytail-activate.js\"",
|
||||
"command": "command -v node >/dev/null 2>&1 && node \"${CLAUDE_PLUGIN_ROOT}/hooks/ponytail-activate.js\" || exit 0",
|
||||
"commandWindows": "if (Get-Command node -ErrorAction SilentlyContinue) { node \"$env:CLAUDE_PLUGIN_ROOT\\hooks\\ponytail-activate.js\" }",
|
||||
"timeout": 5,
|
||||
"statusMessage": "Loading ponytail mode..."
|
||||
}
|
||||
@@ -19,8 +19,8 @@
|
||||
"hooks": [
|
||||
{
|
||||
"type": "command",
|
||||
"command": "node \"${CLAUDE_PLUGIN_ROOT}/hooks/ponytail-mode-tracker.js\"",
|
||||
"commandWindows": "node \"$env:CLAUDE_PLUGIN_ROOT\\hooks\\ponytail-mode-tracker.js\"",
|
||||
"command": "command -v node >/dev/null 2>&1 && node \"${CLAUDE_PLUGIN_ROOT}/hooks/ponytail-mode-tracker.js\" || exit 0",
|
||||
"commandWindows": "if (Get-Command node -ErrorAction SilentlyContinue) { node \"$env:CLAUDE_PLUGIN_ROOT\\hooks\\ponytail-mode-tracker.js\" }",
|
||||
"timeout": 5,
|
||||
"statusMessage": "Tracking ponytail mode..."
|
||||
}
|
||||
|
||||
@@ -2,10 +2,15 @@ const fs = require('fs');
|
||||
const path = require('path');
|
||||
const { getClaudeDir } = require('./ponytail-config');
|
||||
|
||||
const isCodex = Boolean(process.env.PLUGIN_DATA);
|
||||
const statePath = isCodex
|
||||
? path.join(process.env.PLUGIN_DATA, '.ponytail-active')
|
||||
: path.join(getClaudeDir(), '.ponytail-active');
|
||||
const STATE_FILE = '.ponytail-active';
|
||||
const isCopilot = Boolean(process.env.COPILOT_PLUGIN_DATA);
|
||||
const isCodex = !isCopilot && Boolean(process.env.PLUGIN_DATA);
|
||||
|
||||
let stateDir = getClaudeDir();
|
||||
if (isCodex) stateDir = process.env.PLUGIN_DATA;
|
||||
if (isCopilot) stateDir = process.env.COPILOT_PLUGIN_DATA;
|
||||
|
||||
const statePath = path.join(stateDir, STATE_FILE);
|
||||
|
||||
function setMode(mode) {
|
||||
fs.mkdirSync(path.dirname(statePath), { recursive: true });
|
||||
@@ -17,10 +22,13 @@ function clearMode() {
|
||||
}
|
||||
|
||||
function writeHookOutput(event, mode, context = '') {
|
||||
if (!isCodex) {
|
||||
process.stdout.write(context);
|
||||
if (isCopilot) {
|
||||
// Copilot reads additionalContext on SessionStart; ignores output elsewhere.
|
||||
process.stdout.write(JSON.stringify(
|
||||
event === 'SessionStart' && context ? { additionalContext: context } : {}));
|
||||
return;
|
||||
}
|
||||
if (isCodex) {
|
||||
const output = { systemMessage: `PONYTAIL:${mode.toUpperCase()}` };
|
||||
if (context) {
|
||||
output.hookSpecificOutput = {
|
||||
@@ -29,11 +37,15 @@ function writeHookOutput(event, mode, context = '') {
|
||||
};
|
||||
}
|
||||
process.stdout.write(JSON.stringify(output));
|
||||
return;
|
||||
}
|
||||
process.stdout.write(context);
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
clearMode,
|
||||
isCodex,
|
||||
isCopilot,
|
||||
setMode,
|
||||
writeHookOutput,
|
||||
};
|
||||
|
||||
@@ -4,6 +4,9 @@
|
||||
"description": "Lazy senior dev mode for AI agents. The best code is the code you never wrote.",
|
||||
"keywords": ["pi-package", "pi", "skills", "ponytail"],
|
||||
"license": "MIT",
|
||||
"scripts": {
|
||||
"test": "node --test tests/*.test.js && npm test --prefix pi-extension"
|
||||
},
|
||||
"pi": {
|
||||
"extensions": ["./pi-extension/index.js"],
|
||||
"skills": ["./skills"]
|
||||
|
||||
@@ -0,0 +1,59 @@
|
||||
#!/usr/bin/env node
|
||||
// Generate the OpenClaw / ClawHub skill package (.openclaw/skills/) from the
|
||||
// canonical skills/. OpenClaw skills are SKILL.md (frontmatter + body), the same
|
||||
// format ponytail already uses, with one difference: `description` must be a
|
||||
// single line under 160 chars. The canonical descriptions are long (tuned for
|
||||
// Claude's skill picker), so each ships a short one here. The body is copied
|
||||
// verbatim from skills/<name>/SKILL.md so the ruleset never drifts; only the
|
||||
// frontmatter is rewritten.
|
||||
//
|
||||
// Run: node scripts/build-openclaw-skills.js
|
||||
// tests/openclaw-skills.test.js fails if the committed copies are stale.
|
||||
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
const ROOT = path.join(__dirname, '..');
|
||||
const HOMEPAGE = 'https://github.com/DietrichGebert/ponytail';
|
||||
|
||||
const DESCRIPTIONS = {
|
||||
'ponytail': 'Lazy senior dev mode. Forces the simplest, shortest solution that works: YAGNI, stdlib first, no unrequested abstractions.',
|
||||
'ponytail-review': 'Review a diff for over-engineering. Finds what to delete: reinvented stdlib, needless deps, speculative abstractions. One line per finding.',
|
||||
'ponytail-audit': 'Audit the whole repo for over-engineering. A ranked list of what to delete, simplify, or replace with stdlib or native features.',
|
||||
'ponytail-debt': 'Harvest every ponytail: shortcut comment into one debt ledger, so deferrals get tracked instead of forgotten. One-shot report.',
|
||||
'ponytail-help': "Quick reference for ponytail's modes, skills, and commands. One-shot display.",
|
||||
};
|
||||
|
||||
const NAMES = Object.keys(DESCRIPTIONS);
|
||||
|
||||
function sourceBody(name) {
|
||||
const src = fs.readFileSync(path.join(ROOT, 'skills', name, 'SKILL.md'), 'utf8').replace(/\r\n/g, '\n');
|
||||
const fm = src.match(/^---\n[\s\S]*?\n---\n?/);
|
||||
if (!fm) throw new Error(`skills/${name}/SKILL.md has no frontmatter`);
|
||||
return src.slice(fm[0].length);
|
||||
}
|
||||
|
||||
function render(name) {
|
||||
const desc = DESCRIPTIONS[name];
|
||||
if (desc.length > 160 || desc.includes('\n') || desc.includes('"')) {
|
||||
throw new Error(`description for ${name} must be one line, no quotes, under 160 chars`);
|
||||
}
|
||||
const frontmatter =
|
||||
`---\nname: ${name}\ndescription: "${desc}"\nhomepage: ${HOMEPAGE}\nlicense: MIT\n---\n`;
|
||||
return frontmatter + sourceBody(name);
|
||||
}
|
||||
|
||||
function outPath(name) {
|
||||
return path.join(ROOT, '.openclaw', 'skills', name, 'SKILL.md');
|
||||
}
|
||||
|
||||
module.exports = { DESCRIPTIONS, NAMES, render, outPath, sourceBody };
|
||||
|
||||
if (require.main === module) {
|
||||
for (const name of NAMES) {
|
||||
const p = outPath(name);
|
||||
fs.mkdirSync(path.dirname(p), { recursive: true });
|
||||
fs.writeFileSync(p, render(name));
|
||||
console.log('wrote', path.relative(ROOT, p).replace(/\\/g, '/'));
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,39 @@
|
||||
#!/usr/bin/env node
|
||||
// Every ponytail command the pi extension registers must also ship as a
|
||||
// file-based command for the hosts that need one: Claude Code (commands/*.toml,
|
||||
// which Gemini CLI reuses) and OpenCode (.opencode/command/*.md). /ponytail-help
|
||||
// was advertised in the README and the help card but missing both files; this
|
||||
// guards that drift -- a registered command with no adapter file fails here.
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
const root = path.join(__dirname, '..');
|
||||
|
||||
// pi-extension registers the canonical command set.
|
||||
const piSource = fs.readFileSync(path.join(root, 'pi-extension', 'index.js'), 'utf8');
|
||||
const commands = [...piSource.matchAll(/registerCommand\(["']([\w-]+)["']/g)].map((m) => m[1]);
|
||||
|
||||
test('pi registers at least the base command', () => {
|
||||
assert.ok(commands.includes('ponytail'), 'expected pi to register a ponytail command');
|
||||
});
|
||||
|
||||
test('every registered command ships a Claude commands/*.toml', () => {
|
||||
for (const name of commands) {
|
||||
assert.ok(
|
||||
fs.existsSync(path.join(root, 'commands', `${name}.toml`)),
|
||||
`missing commands/${name}.toml`,
|
||||
);
|
||||
}
|
||||
});
|
||||
|
||||
test('every registered command ships an OpenCode .opencode/command/*.md', () => {
|
||||
for (const name of commands) {
|
||||
assert.ok(
|
||||
fs.existsSync(path.join(root, '.opencode', 'command', `${name}.md`)),
|
||||
`missing .opencode/command/${name}.md`,
|
||||
);
|
||||
}
|
||||
});
|
||||
@@ -0,0 +1,33 @@
|
||||
#!/usr/bin/env node
|
||||
// Smoke test for the Copilot plugin adapter: keep command wiring minimal and
|
||||
// ensure the debt command is part of the shared command surface.
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
const root = path.join(__dirname, '..');
|
||||
const REQUIRED_COMMAND_FILES = [
|
||||
'ponytail.toml',
|
||||
'ponytail-review.toml',
|
||||
'ponytail-audit.toml',
|
||||
'ponytail-debt.toml',
|
||||
];
|
||||
|
||||
function readJSON(relPath) {
|
||||
return JSON.parse(fs.readFileSync(path.join(root, relPath), 'utf8'));
|
||||
}
|
||||
|
||||
test('copilot plugin command directory includes ponytail-debt', () => {
|
||||
const manifest = readJSON('.github/plugin/plugin.json');
|
||||
assert.equal(manifest.name, 'ponytail');
|
||||
assert.equal(manifest.commands, 'commands/');
|
||||
|
||||
for (const file of REQUIRED_COMMAND_FILES) {
|
||||
assert.ok(
|
||||
fs.existsSync(path.join(root, manifest.commands, file)),
|
||||
`missing command file: ${manifest.commands}${file}`,
|
||||
);
|
||||
}
|
||||
});
|
||||
@@ -16,6 +16,12 @@ const MANIFEST = 'gemini-extension.json';
|
||||
const EXTENSION_NAME = 'ponytail';
|
||||
// Floating refs are a supply-chain footgun; the manifest version must be pinned.
|
||||
const PINNED_SEMVER = /^\d+\.\d+\.\d+$/;
|
||||
const VERSIONED_MANIFESTS = [
|
||||
'gemini-extension.json',
|
||||
'.claude-plugin/plugin.json',
|
||||
'.codex-plugin/plugin.json',
|
||||
'.github/plugin/plugin.json',
|
||||
];
|
||||
// Gemini auto-discovers these by directory; the manifest is only useful if they exist.
|
||||
const REUSED_COMMANDS = ['commands/ponytail.toml', 'commands/ponytail-review.toml'];
|
||||
const REUSED_SKILLS = ['skills/ponytail/SKILL.md'];
|
||||
@@ -46,9 +52,15 @@ test('manifest names the ponytail extension with a pinned version', () => {
|
||||
});
|
||||
|
||||
test('version stays aligned with the other plugin manifests', () => {
|
||||
const manifest = loadManifest();
|
||||
const claude = JSON.parse(read('.claude-plugin/plugin.json'));
|
||||
assert.equal(manifest.version, claude.version);
|
||||
const versions = VERSIONED_MANIFESTS.map((rel) => {
|
||||
const manifest = JSON.parse(read(rel));
|
||||
assert.match(manifest.version, PINNED_SEMVER, `${rel} version must be pinned semver`);
|
||||
return manifest.version;
|
||||
});
|
||||
const [sharedVersion, ...rest] = versions;
|
||||
for (const version of rest) {
|
||||
assert.equal(version, sharedVersion);
|
||||
}
|
||||
});
|
||||
|
||||
test('contextFileName resolves to a file carrying the ponytail rules', () => {
|
||||
|
||||
@@ -99,5 +99,44 @@ assert.equal(
|
||||
'flag must not land in ~/.claude when CLAUDE_CONFIG_DIR is set',
|
||||
);
|
||||
|
||||
const copilotData = path.join(temp, 'copilot-data');
|
||||
const codexData = path.join(temp, 'codex-data-shadow');
|
||||
result = run('ponytail-activate.js', {
|
||||
HOME: home,
|
||||
USERPROFILE: home,
|
||||
COPILOT_PLUGIN_DATA: copilotData,
|
||||
PLUGIN_DATA: codexData,
|
||||
PONYTAIL_DEFAULT_MODE: 'full',
|
||||
});
|
||||
assert.equal(result.status, 0, result.stderr);
|
||||
assert.equal(fs.readFileSync(path.join(copilotData, '.ponytail-active'), 'utf8'), 'full');
|
||||
assert.equal(
|
||||
fs.existsSync(path.join(codexData, '.ponytail-active')),
|
||||
false,
|
||||
'copilot hooks must not write mode state to codex PLUGIN_DATA',
|
||||
);
|
||||
output = JSON.parse(result.stdout);
|
||||
assert.match(output.additionalContext, /PONYTAIL MODE ACTIVE — level: full/);
|
||||
|
||||
result = run(
|
||||
'ponytail-mode-tracker.js',
|
||||
{
|
||||
HOME: home,
|
||||
USERPROFILE: home,
|
||||
COPILOT_PLUGIN_DATA: copilotData,
|
||||
PLUGIN_DATA: codexData,
|
||||
},
|
||||
JSON.stringify({ prompt: '/ponytail ultra' }),
|
||||
);
|
||||
assert.equal(result.status, 0, result.stderr);
|
||||
assert.equal(fs.readFileSync(path.join(copilotData, '.ponytail-active'), 'utf8'), 'ultra');
|
||||
assert.equal(
|
||||
fs.existsSync(path.join(codexData, '.ponytail-active')),
|
||||
false,
|
||||
'copilot mode tracker must keep codex PLUGIN_DATA untouched',
|
||||
);
|
||||
output = JSON.parse(result.stdout);
|
||||
assert.deepEqual(output, {});
|
||||
|
||||
fs.rmSync(temp, { recursive: true, force: true });
|
||||
console.log('hook compatibility checks passed');
|
||||
|
||||
@@ -0,0 +1,26 @@
|
||||
#!/usr/bin/env node
|
||||
// The OpenClaw skill package (.openclaw/skills/) is generated from skills/ by
|
||||
// scripts/build-openclaw-skills.js. These tests fail if the committed copies are
|
||||
// stale (ruleset drift) or if a description breaks OpenClaw's one-line <160 rule.
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
const fs = require('fs');
|
||||
const { NAMES, render, outPath, sourceBody, DESCRIPTIONS } = require('../scripts/build-openclaw-skills');
|
||||
|
||||
for (const name of NAMES) {
|
||||
test(`${name}: committed OpenClaw skill matches the generator`, () => {
|
||||
const onDisk = fs.readFileSync(outPath(name), 'utf8').replace(/\r\n/g, '\n');
|
||||
assert.equal(onDisk, render(name), 'stale — run: node scripts/build-openclaw-skills.js');
|
||||
});
|
||||
|
||||
test(`${name}: body is the canonical skills/${name} body, verbatim`, () => {
|
||||
const onDisk = fs.readFileSync(outPath(name), 'utf8').replace(/\r\n/g, '\n');
|
||||
assert.ok(onDisk.endsWith(sourceBody(name)), 'body drifted from skills/' + name);
|
||||
});
|
||||
|
||||
test(`${name}: description is one line under 160 chars`, () => {
|
||||
const d = DESCRIPTIONS[name];
|
||||
assert.ok(d.length <= 160 && !d.includes('\n'), 'description too long or multiline');
|
||||
});
|
||||
}
|
||||
Reference in New Issue
Block a user