Replace the flat orange badge with a clickable terminal-style banner
image: the "he's building" sticker, a bold headline, and an orange
JOIN THE WAITLIST call to action. Localized banners for EN/ES/KO.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Grouped bars of LOC, tokens, cost and time as a % of the no-skill baseline
(lower is leaner/cheaper/faster), plus a separate safety strip (baseline,
caveman and ponytail 100%; yagni-oneliner 95%). System-gray palette so it reads
on both GitHub themes. The chart commits landed after #158 had already
squash-merged, so this brings the chart onto main.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs: correct cost claim to 42-75% from 30-rep re-verification
Re-ran the cost benchmark at 30 reps per cell on Claude (Haiku/Sonnet/Opus):
ponytail is 42-75% cheaper than no-skill, not the previously published 47-77%.
The direction holds, both ends came in a few points lower. Updates the README
headline and body, the benchmark chart subtitle, and the benchmarks/README cost
table, and adds a dated results doc with full method.
Also adds the OpenAI (gpt-4.1-mini/gpt-5.4-mini/gpt-5.5) and Gemini configs. On
OpenAI reasoning models ponytail costs more, not less, so the claim stays
Claude-scoped. Gemini run pending a fresh-quota day.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs: scope the body claim to Claude models
"on every model" read as cross-provider, but the 30-rep verification shows
the cost win reverses on OpenAI reasoning models. Match the caption and
benchmarks/README, which already say Claude.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs: reframe the pitch as the discipline, not token savings
The cost/code/latency numbers vary by model and on some (terse reasoning
models like GPT-5.5) ponytail costs more, so leading with them as a universal
win was misleading. Adds model-variance to the headline caption and a paragraph
making the stated point the mental model: write only what the task needs,
safety kept, maintainable code. Savings are a model-dependent side effect.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs: name the ladder's reasoning cost
The ladder is a deliberation step: on reasoning models the agent spends
thinking tokens working through the rungs before it saves any output, which
together with the always-on ruleset can outweigh the shorter code. Makes the
GPT-5.5 cost increase legible rather than just stating it.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs: state the single-shot limitation honestly
The benchmark is single-shot (one prompt, one completion); it does not measure
a real multi-turn agent session, where the ruleset re-injects and the ladder
deliberates every turn. Adds that caveat to the README, and corrects the
benchmarks/README note that claimed caching widens the gap "in ponytail's
favor" (unverified, and a measured agentic A/B in #121 found the opposite can
happen). Per-session cost can land either way.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs: fix run count in caption (cost is 30 runs, not 10)
Cost was re-verified at 30 reps; code and latency are still the original 10.
The headline caption said "10 runs" across the board, which undersold the cost
verification. Now states the split, matching benchmarks/README.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A dark-bg-ready variant of the mark: white face fill plus a die-cut white
contour so it reads on dark backgrounds, where logo.png (black on transparent)
and the social-preview face do not. Ships as SVG (scalable, white + black
layers) and a 1085x1241 PNG.
Contributed by @pixexid in #42.
Co-authored-by: pixexid <54691335+pixexid@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Commit a promptfoo harness (config + arm prompts + LOC metric + vendored
caveman SKILL) so anyone can re-run the comparison: no-skill vs caveman vs
ponytail, across Haiku / Sonnet / Opus, 10 runs per cell, median reported.
Replace the old unreproducible 6-task chart with assets/benchmark-3model.svg
from this run, and reframe the README to the reproducible numbers: ponytail
writes 80-94% less code, costs 47-77% less, and runs 3-6x faster than a
no-skill agent on every model. benchmarks/README.md carries the median tables
and the reproduce command. Drops nothing that is not measured.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Six no-skill control arms re-run through the same harness so all three
arms share one model. README Numbers section and chart now cite the
complete dataset: -47% tokens, 3x faster, 490 vs 3,629 LOC, extension
96 vs 1,115 lines, probes green everywhere. Em dashes removed.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
