Merge branch 'main' into main

README.md

@@ -19,8 +19,8 @@
 </p>
 
 <p align="center">
-  <strong>80-94% less code &middot; 3-6&times; faster &middot; 47-77% cheaper</strong><br>
-  <sub>Median of 10 runs across Haiku, Sonnet, and Opus. <a href="benchmarks/">Reproduce it yourself.</a></sub>
+  <strong>80-94% less code &middot; 3-6&times; faster &middot; 42-75% cheaper</strong><br>
+  <sub>Per-task code, latency, and cost on the Claude API, not your plan's quota. Median across Haiku, Sonnet, and Opus (10 runs for code and latency, 30 for the re-verified cost). Results vary by model and prompt: the ruleset re-injects each turn, so on a short prompt or a terse reasoning model that overhead can outweigh the savings. <a href="benchmarks/">Reproduce it yourself.</a></sub>
 </p>
 
 ---
@@ -50,7 +50,9 @@ Five everyday tasks (email validator, debounce, CSV sum, countdown timer, rate l
   <img src="assets/benchmark-3model.svg" width="860" alt="Median lines of code per arm across Haiku, Sonnet and Opus; ponytail writes 80-94% less code than the no-skill baseline">
 </p>
 
-**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/](benchmarks/). Production-grade tasks, where an unconstrained agent bloats far more, are written up in [benchmarks/results/](benchmarks/results/).
+**80-94% less code, 42-75% less cost, and 3-6× faster than a no-skill agent, on every Claude 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/](benchmarks/). Production-grade tasks, where an unconstrained agent bloats far more, are written up in [benchmarks/results/](benchmarks/results/).
+
+**That is the byproduct, not the pitch.** These are Claude numbers, and they vary by model. Capable instruction-following models follow the ladder and write far less, cheaper and faster. Terse reasoning models can go the other way: the ladder is a deliberation step, so the model spends thinking tokens working through the rungs before it saves any output, and together with the always-on ruleset that can cost more than the shorter code saves. On GPT-5.5 it does. And all of this is single-shot, one prompt in and one answer out: a real agent session re-injects the ruleset and runs the ladder every turn, which this benchmark does not measure, so per-session cost can land either way. The rule was never "fewest tokens." It is: write only what the task needs, and never cut validation, error handling, security, or accessibility. The code ends up small because it is necessary, not golfed, and that is the part that stays maintainable. Lower cost and latency are a side effect on the models that follow it.
 
 ## How it works
 
@@ -156,6 +158,13 @@ hermes plugins install DietrichGebert/ponytail --enable
 ```
 
 Restart Hermes after installing. The plugin injects the active Ponytail mode before each LLM turn, registers the bundled skills as `ponytail:<skill>`, and adds `/ponytail`, `/ponytail-review`, `/ponytail-audit`, `/ponytail-debt`, and `/ponytail-help`. In shared gateways, restrict `/ponytail` to trusted users with Hermes slash-command access controls; runtime mode is process-local.
+### 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.
 
@@ -194,6 +203,8 @@ 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