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 strikersam/autonomous-ai-agency --skill council-reviewgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/strikersam/autonomous-ai-agency/council-review)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/council-review"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/council-review/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/strikersam/autonomous-ai-agency/council-review"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/council-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00044 | $0.00781 |
| Opus 5 | $0.00022 | $0.00391 |
| Sonnet 5 | $0.00009 | $0.00156 |
| Haiku 4.5 | $0.00004 | $0.00078 |
Grade A, and why
council-review 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.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: council-review
When to Use
Use this skill:
- Before merging any PR that changes production code
- When asked "is this safe?" or "can this go out?"
- After a self-review that feels uncertain
- For any change to risky modules (auth, keys, agent tools, routing)
Instructions
Step 1 — Gather the diff
git diff main...HEAD # all changes vs main
git diff --stat main...HEAD # file summary
Step 2 — Run each reviewer role independently
For each role below, read the diff and answer the questions for that role. Record findings in a structured review comment.
Role 1: Security Reviewer
Questions to answer:
- Does this change introduce or weaken an auth check?
- Are any secrets, tokens, or API keys potentially exposed?
- Does any new code accept untrusted input without validation?
- Are file paths sanitized? (especially in
agent/tools.py) - Does any new dependency introduce a known CVE?
Role 2: Correctness Reviewer
Questions to answer:
- Does the implementation match the stated goal?
- Are edge cases handled (empty input, None, zero, very long strings)?
- Are error conditions propagated correctly?
- Would any existing test fail after this change?
- Are there any off-by-one errors, race conditions, or type mismatches?
Role 3: Performance Reviewer
Questions to answer:
- Does this change add any blocking I/O on the async path?
- Are there any N+1 query or repeated expensive computation patterns?
- Does any new loop run on every request?
- Is caching appropriate? (especially for health checks, model registry)
Role 4: Maintainability Reviewer
Questions to answer:
- Is the code readable without inline explanation?
- Are variable names clear?
- Are new abstractions justified or is this over-engineering?
- Does this add duplication that should be shared?
- Is the module boundary respected? (don't let routing logic leak into proxy.py)
Step 3 — Produce a council verdict
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 · 121 lines · 44 tokens per session scan A e9e1bdcf23d2
council-review is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 781 once invoked, about $0.0002 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 2026-08-31.
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