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 sutchan/Agent-Skills-Hub --skill analyze-projectgit clone --depth 1 https://github.com/sutchan/Agent-Skills-HubWrote 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/sutchan/agent-skills-hub/analyze-project)<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/analyze-project"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/analyze-project/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/sutchan/agent-skills-hub/analyze-project"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/analyze-project.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 | $0.00097 | $0.00528 |
| Opus 5.5 | $0.00039 | $0.00211 |
| Sonnet 5.5 | $0.00019 | $0.00106 |
| Haiku 4.5 | $0.00010 | $0.00053 |
Grade A, and why
analyze-project 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 19d 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
94% identical to analyze-project — 8 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
analyze-project
Use this as the Rigor Analyze / Rigor Audit read-only skill. The installed slug
remains analyze-project for compatibility.
Use the shared operating principles in
../ai-research-reproduction/references/agent-operating-principles.md; this skill should guide
read-only analysis without constraining the model's project-specific reasoning.
When to apply
- The user wants to understand a deep learning repository before changing it.
- The user needs a map of model structure, training entrypoints, inference entrypoints, and config relationships.
- The user wants conservative suggestions about likely insertion points or suspicious implementation patterns.
- The user explicitly wants read-only analysis and not heavy execution.
When not to apply
- When the main task is to execute a failing command or debug a traceback.
- When the user wants environment setup or asset download only.
- When the user wants speculative adaptation or broad exploratory patching.
- When the task is a general literature summary without repository analysis.
Clear boundaries
- This skill is read-mostly.
- It may run lightweight static inspection helpers.
- It does not patch repository code.
- It does not own final reproduction outputs.
- It should mark suspicious patterns as heuristics, not confirmed bugs.
Output expectations
analysis_outputs/SUMMARY.mdanalysis_outputs/RISKS.mdanalysis_outputs/status.json
Notes
Use references/analysis-policy.md and the shared ../ai-research-reproduction/references/research-pitfall-checklist.md.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 19d ago Changed · +1 lines 7f8838ffc82c
- 25d ago Changed · +3 lines · +15 tokens per session 102b69570b09
- 1mo ago Changed · -3 lines · -15 tokens per session 1fd9afebeb18
- 1mo ago First seen · 49 lines · 97 tokens per session scan A 21c8c40d11bc
analyze-project is a skill published in the GitHub repository sutchan/Agent-Skills-Hub (2 stars, last pushed 3d ago), licensed MIT. It adds 97 tokens to every session and 528 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to analyze-project, differing in 8 lines, and is treated as a copy.
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