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 jrswab/axe --skill samplegit clone --depth 1 https://github.com/jrswab/axeWrote 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/jrswab/axe/sample)<a href="https://agentmods.dev/skills/jrswab/axe/sample"><img src="https://agentmods.dev/badge/skills/jrswab/axe/sample/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/jrswab/axe/sample"><img src="https://agentmods.dev/badge/skills/jrswab/axe/sample.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 | $0.00000 | $0.00152 |
| Opus 5.5 | $0.00000 | $0.00061 |
| Sonnet 5.5 | $0.00000 | $0.00030 |
| Haiku 4.5 | $0.00000 | $0.00015 |
Grade A, and why
sample 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.
What it actually says
Sample Skill
Purpose
This is a sample skill template for Axe. Skills are reusable instruction sets that guide AI agents in performing specific tasks. Use this template as a starting point for creating your own skills.
Instructions
- Define a clear, focused purpose for your skill.
- Write step-by-step instructions that an AI agent can follow.
- Be specific about inputs, constraints, and expected behavior.
- Include examples where helpful.
Output Format
Describe the expected structure and format of the skill's output. For example:
- Format: Plain text, Markdown, JSON, etc.
- Structure: Headings, bullet points, code blocks, etc.
- Length: Approximate expected length or constraints.
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 · 23 lines · 0 tokens per session scan A ebb85963235f
sample is a skill published in the GitHub repository jrswab/axe (897 stars, last pushed 13d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 152 tokens. 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 2026-08-30.
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printing-press-amend
Amend a published CLI from one of two input sources: (1) dogfood mode mines the active Claude Code session transcript for friction (missing flags, hand- rolled API payloads, silent-null returns); (2) direct-input mode accepts user-supplied asks (rename a command, add commands or feeds, fix a named bug, optionally…