Borrowing it
Nothing to install: this file belongs to amiable-dev/llm-council. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/amiable-dev/llm-council/master/.github/skills/council-review/SKILL.mdgit clone --depth 1 https://github.com/amiable-dev/llm-councilWrote 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/amiable-dev/llm-council/council-review)<a href="https://agentmods.dev/skills/amiable-dev/llm-council/council-review"><img src="https://agentmods.dev/badge/skills/amiable-dev/llm-council/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/amiable-dev/llm-council/council-review"><img src="https://agentmods.dev/badge/skills/amiable-dev/llm-council/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 | $0.00050 | $0.01069 |
| Opus 5 | $0.00025 | $0.00535 |
| Sonnet 5 | $0.00010 | $0.00214 |
| Haiku 4.5 | $0.00005 | $0.00107 |
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 10d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Council Code Review Skill
Get multiple AI perspectives on code changes with structured, actionable feedback.
When to Use
- Review pull requests before merging
- Get code quality feedback on implementations
- Identify potential issues across multiple dimensions
- Validate changes against coding standards
Workflow
- Prepare Input: Provide file paths or git diff
- Invoke Review: Call
mcp:llm-council/verifywith code-review rubric - Process Feedback: Receive structured scores and issue list
- Address Issues: Fix blocking issues before proceeding
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
snapshot_id |
string | required | Git commit SHA for reproducibility |
file_paths |
list | null | List of files to review (full file analysis) |
git_diff |
string | null | Unified diff format for change-focused review |
rubric_focus |
string | null | Focus area: "Security", "Performance", etc. |
tier |
string | "high" | Confidence tier: "quick", "balanced", "high", "reasoning" |
Tier Selection Guide
| Tier | Use When | Timeout |
|---|---|---|
balanced |
Routine code reviews | ~90s |
high |
Quality-critical reviews (default) | ~180s |
reasoning |
Complex architectural or security reviews | ~600s |
Input Formats
Supports both:
file_paths: List of files to review (full file analysis)git_diff: Unified diff format for change-focused reviewsnapshot_id: Git commit SHA (required for reproducibility)
Rubric (ADR-016)
| Dimension | Weight | Focus |
|---|---|---|
| Accuracy | 35% | Correctness, no bugs, logic errors |
| Completeness | 20% | All requirements addressed |
| Clarity | 20% | Readable, maintainable code |
| Conciseness | 15% | No unnecessary complexity |
| Relevance | 10% | Addresses stated requirements |
Output Schema
{
"verdict": "pass|fail|unclear",
"confidence": 0.82,
"rubric_scores": {
"accuracy": 7.5,
"completeness": 8.0,
"clarity": 9.0,
"conciseness": 8.5,
"relevance": 9.0
},
"blocking_issues": [
{
"severity": "major",
"file": "src/api.py",
"line": 42,
"message": "Missing input validation"
}
],
"rationale": "Overall, the code is well-structured...",
"partial": false,
"timeout_fired": false,
"completed_stages": ["stage1", "stage2", "stage3"]
}
What ships with it
1 file 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.
- 10d ago First seen · 131 lines · 50 tokens per session scan A a8b1e6dd179e
council-review is a skill published in the GitHub repository amiable-dev/llm-council (41 stars, last pushed 9d ago), licensed MIT. It adds 50 tokens to every session and 1,069 once invoked, about $0.0003 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.
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