* feat: refine ruleset from a full-project field review
A reviewer ran ponytail across a 9-phase rewrite (protocol, PC app, simulator,
RPi daemon, ESP32 firmware) and flagged three gaps. All three land in SKILL.md
and propagate to AGENTS.md + the rule copies:
- Promote the one-runnable-check rule to a headline ("Lazy code without its
check is unfinished"), enforced as a check-rule-copies invariant.
- Hardware carve-out in "When NOT to be lazy": a real device is never the spec
ideal (clock drift, sensor offset), leave the calibration knob.
- Clarify the Output rule: explanation the user explicitly asked for is not
debt, only unrequested prose is.
Fallback instructions kept in sync. Rule-copy check + tests green.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test: add a behavior gate proving the refinements actually fire
The refinements were verified as injected text, but injected != behavioral.
This adds a behavior eval that probes each refined rule on a task that should
trigger it:
- hardware -> does the output leave a calibration knob?
- explanation -> when a write-up is explicitly requested, is it given in full?
- onecheck -> is a runnable check left behind?
benchmarks/behavior.yaml runs the probes (baseline vs ponytail arm); the
grader benchmarks/behavior.js is proven by tests/behavior.test.js (8 cases,
RED/GREEN, no API key, runs in CI). Live-confirmed: the model under the
current ruleset passes all three gates, graded by the same grader.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Ponytail
He says nothing. He writes one line. It works.
80-94% less code · 3-6× faster · 47-77% cheaper
Median of 10 runs across Haiku, Sonnet, and Opus. Reproduce it yourself.
You know him. Long ponytail. Oval glasses. Has been at the company longer than the version control. You show him fifty lines; he looks at them, says nothing, and replaces them with one.
Ponytail puts him inside your AI agent.
Before / after
You ask for a date picker. Your agent installs flatpickr, writes a wrapper component, adds a stylesheet, and starts a discussion about timezones.
With ponytail:
<!-- ponytail: browser has one -->
<input type="date">
More survivors in examples/.
Numbers
Five everyday tasks (email validator, debounce, CSV sum, countdown timer, rate limiter), three models, three arms: no skill, the caveman skill, and ponytail. Ten runs per cell, median reported.
80-94% less code, 47-77% less cost, and 3-6× faster than a no-skill agent, on every model. Every shortcut ponytail takes is marked in the code with a ponytail: comment naming its upgrade path. Reproduce it yourself: npx promptfoo eval -c benchmarks/promptfooconfig.yaml. Method and raw numbers: benchmarks/. Production-grade tasks, where an unconstrained agent bloats far more, are written up in benchmarks/results/.
How it works
Before writing code, the agent stops at the first rung that holds:
1. Does this need to exist? → no: skip it (YAGNI)
2. Stdlib does it? → use it
3. Native platform feature? → use it
4. Installed dependency? → use it
5. One line? → one line
6. Only then: the minimum that works
Lazy, not negligent: trust-boundary validation, data-loss handling, security, and accessibility are never on the chopping block.
Install
The most effort ponytail will ever ask of you:
Claude Code
/plugin marketplace add DietrichGebert/ponytail
/plugin install ponytail@ponytail
Codex
codex plugin marketplace add DietrichGebert/ponytail
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.
Pi agent harness
pi install git:github.com/DietrichGebert/ponytail
OpenCode
Run OpenCode from a checkout of this repo (the plugin reuses its hooks/ and skills/), and add to opencode.json:
{ "plugin": ["./.opencode/plugins/ponytail.mjs"] }
Injects the ruleset every turn at the active level; adds /ponytail, /ponytail-review, and /ponytail-audit. 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.
Gemini CLI
gemini extensions install https://github.com/DietrichGebert/ponytail
Loads the ruleset as always-on context every session and registers /ponytail and /ponytail-review; the skills/ ship too, activated when a task needs them.
That was it. He'd be proud. He won't say it.
Active every session. /ponytail-review finds what to delete in your diff, /ponytail-audit does the same for the whole repo. /ponytail ultra exists for when the codebase has wronged you personally. /ponytail-help explains the rest.
In Codex, invoke the skills as @ponytail, @ponytail-review,
@ponytail-audit, and @ponytail-help. 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/, .windsurf/rules/, .clinerules/, .github/copilot-instructions.md, AGENTS.md, .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.
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).
Which files map to which agent: Agent portability.
Development
When changing the compact rule text, keep the agent copies aligned:
node scripts/check-rule-copies.js
FAQ
Does it need a config file? No.
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.
Does it scale? The code you never wrote scales infinitely. Zero bugs, zero CVEs, 100% uptime since forever.
Why "ponytail"? You know exactly why.
License
MIT. The shortest license that works.
