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 am-command-ponytail-helpgit 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/am-command-ponytail-help)<a href="https://agentmods.dev/skills/samplexbro/agentsmesh/am-command-ponytail-help"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/am-command-ponytail-help/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/am-command-ponytail-help"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/am-command-ponytail-help.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 | $0.00019 | $0.00309 |
| Opus 5.5 | $0.00008 | $0.00124 |
| Sonnet 5.5 | $0.00004 | $0.00062 |
| Haiku 4.5 | $0.00002 | $0.00031 |
Grade A, and why
am-command-ponytail-help 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 28d 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.
What it actually says
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-gain (measured-impact scoreboard from the benchmark), /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.
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.
- 28d ago First seen · 8 lines · 19 tokens per session scan A 2a8e161caa29
am-command-ponytail-help is a skill published in the GitHub repository sampleXbro/agentsmesh (25 stars, last pushed 22d ago), licensed MIT. It adds 19 tokens to every session and 309 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-19.
Other skills, from other repositories
Agent Browser Automation
Fast Rust-based headless browser automation CLI with Node.js fallback for AI agents, featuring navigation, clicking, typing, snapshots, and structured commands optimized for agent workflows.
tournament-manager
Tournament manager for the EasyChamp platform. Use when the user wants to create or operate a sports league, tournament, or bracket — covers generating a league, spinning up a tournament under it, building the bracket, producing a schedule with venues, and entering match results. Activates for 'create a league'…
replay
Find, analyze, and share AI coding sessions with vibe-replay. Use when the user asks for a replay, wants to find a past session, run a session retro, share Cursor/Claude/Codex session context, or attach session context to a PR.
schedules
GTM Agent schedules — recurring prompts the GTM Agent runs on a cadence, each occurrence starting a fresh agent task. Use for any request to do something on a schedule or recurring cadence: a daily digest, a weekly report, checking or changing when a scheduled run happens next, pausing or deleting one.
routines
Clay routines — create a routine from an existing function/workflow, then run a saved routine that exists in this workspace. Use when the user asks to create/register a routine, or to run, execute, or trigger a function, workflow, or routine (by name or id), pass it inputs, or check the results/status of a run. For…
credits-quotas-plans
Use when the user asks about credits, quotas, or plan limits, or verified usage requires a significant-spend warning or reveals a limit. Covers data-credit balance, action-execution balance, search result caps, period quotas, and upgrade paths before starting work that would only partially complete.