Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sampleXbro/agentsmesh --skill ponytail-gaingit clone --depth 1 https://github.com/sampleXbro/agentsmeshWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/samplexbro/agentsmesh/ponytail-gain)<a href="https://agentmods.dev/skills/samplexbro/agentsmesh/ponytail-gain"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/ponytail-gain/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/samplexbro/agentsmesh/ponytail-gain"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/ponytail-gain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.00486 |
| Opus 5.5 | $0.00033 | $0.00194 |
| Sonnet 5.5 | $0.00017 | $0.00097 |
| Haiku 4.5 | $0.00008 | $0.00049 |
Grade A, and why
ponytail-gain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to ponytail-gain — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Ponytail Gain
Display this scoreboard when invoked. One-shot: do NOT change mode, write flag files, or persist anything.
The figures are the published benchmark medians (5 everyday tasks: email
validator, debounce, CSV sum, countdown timer, rate limiter; three models:
Haiku, Sonnet, Opus). They are measured, not computed from the current repo.
Source: benchmarks/ and the README.
Scoreboard
Render plain ASCII bars. The bar length shows the measured range; the label carries the exact figure:
ponytail gain benchmark median · 5 tasks · 3 models
Lines of code no-skill ████████████████████ 100%
ponytail ██▌················· 6–20% ▼ 80–94%
Cost no-skill ████████████████████ 100%
ponytail █████▌·············· 23–53% ▼ 47–77%
Speed ponytail ▸ 3–6× faster
This repo: /ponytail-debt (shortcuts you deferred)
/ponytail-audit (what's still cuttable)
Honesty boundary
These are benchmark medians, not this repo. NEVER print a per-repo savings
number ("you saved X lines/tokens here"): the unbuilt version was never
written, so there is no real baseline to subtract from in a live repo. The
only real per-repo figures come from /ponytail-debt (a counted ledger), and
this card points there instead of inventing one.
Boundaries
One-shot display. Edits nothing, changes no mode. "stop ponytail" or "normal mode": revert.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 46 lines · 83 tokens per session scan A 18bd60426d7e
ponytail-gain is a skill published in the GitHub repository sampleXbro/agentsmesh (26 stars, last pushed 1mo ago), licensed MIT. It adds 83 tokens to every session and 486 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ponytail-gain, differing in 9 lines, and is treated as a copy.
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