Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/charlieviettq/awesome-agent-skillnpx agentmods add commands/charlieviettq/awesome-agent-skill/validate-skillsWrote 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/commands/charlieviettq/awesome-agent-skill/validate-skills)<a href="https://agentmods.dev/commands/charlieviettq/awesome-agent-skill/validate-skills"><img src="https://agentmods.dev/badge/commands/charlieviettq/awesome-agent-skill/validate-skills/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/commands/charlieviettq/awesome-agent-skill/validate-skills"><img src="https://agentmods.dev/badge/commands/charlieviettq/awesome-agent-skill/validate-skills.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 | $0.00013 | $0.00072 |
| Opus 5 | $0.00006 | $0.00036 |
| Sonnet 5 | $0.00003 | $0.00014 |
| Haiku 4.5 | $0.00001 | $0.00007 |
Grade A, and why
validate-skills 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 12d 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
Run the repository skill validator and report results.
python3 scripts/validate-skills.py
If validation fails, list each error with the file path and suggest the minimal fix. Do not modify unrelated skills.
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.
- 12d ago First seen · 13 lines · 13 tokens per session scan A 3cf7c6a15a0f
validate-skills is a command published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 72 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
Other commands, from other repositories
test
/test [optional: specific test file or pattern] /test --coverage /test --watch /test --red-only # Force RED-phase semantics (writes failing tests, no implementation) /test --tdd # Run with TDD enforcement explicitly enabled for this invocation.
retro
/retro [optional: sprint name or date range].
sdlc-test
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checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.