Borrowing it
Nothing to install: this file belongs to swarm-ai-research/swarm. 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/swarm-ai-research/swarm/main/.claude/commands/council_review.mdgit clone --depth 1 https://github.com/swarm-ai-research/swarmWrote 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/swarm-ai-research/swarm/council_review)<a href="https://agentmods.dev/commands/swarm-ai-research/swarm/council_review"><img src="https://agentmods.dev/badge/commands/swarm-ai-research/swarm/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/commands/swarm-ai-research/swarm/council_review"><img src="https://agentmods.dev/badge/commands/swarm-ai-research/swarm/council_review.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 | $0.01918 |
| Opus 5 | $0.00000 | $0.00959 |
| Sonnet 5 | $0.00000 | $0.00384 |
| Haiku 4.5 | $0.00000 | $0.00192 |
Grade A, and why
council_review scanned grade A with 1 finding 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 11d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/council_review
Run a multi-LLM council evaluation on study results. Three expert personas (mechanism designer, statistician, red-teamer) deliberate on the findings using the council protocol.
Usage
/council_review <run_dir> [--type sweep|scenario|cross_study] [--provider anthropic|openai|ollama]
Examples:
/council_review runs/20260213-143607_delegation_games_sweep/council_review scenarios/baseline.yaml --type scenario/council_review runs/study_a runs/study_b --type cross_study/council_review runs/latest_sweep --provider ollama
Prerequisites
The evaluator automatically creates LLM agents from each council member's config. You need at least one LLM provider available:
| Provider | Setup | Notes |
|---|---|---|
| Anthropic (default) | export ANTHROPIC_API_KEY=sk-ant-... |
Uses claude-sonnet-4-20250514 |
| OpenAI | export OPENAI_API_KEY=sk-... |
Uses gpt-4o |
| Ollama (local, free) | brew install ollama && ollama serve |
Requires a pulled model |
| Groq | export GROQ_API_KEY=gsk_... |
Uses llama-3.3-70b-versatile |
| Together | export TOGETHER_API_KEY=... |
Uses meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo |
| DeepSeek | export DEEPSEEK_API_KEY=sk-... |
Uses deepseek-chat |
export GOOGLE_API_KEY=... |
Uses gemini-2.0-flash (requires google-genai) |
To use a non-default provider, pass --provider:
/council_review runs/my_sweep --provider ollama
Or mix providers per member:
from swarm.agents.llm_config import LLMConfig, LLMProvider
from swarm.council.study_evaluator import StudyEvaluator, default_evaluator_config
config = default_evaluator_config(provider_configs={
"mechanism_designer": LLMConfig(provider=LLMProvider.ANTHROPIC, model="claude-sonnet-4-20250514"),
"statistician": LLMConfig(provider=LLMProvider.OPENAI, model="gpt-4o"),
"red_teamer": LLMConfig(provider=LLMProvider.OLLAMA, model="llama3"),
})
evaluator = StudyEvaluator(config=config)
evaluation = evaluator.evaluate_sweep("runs/my_sweep")
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.
- 11d ago First seen · 175 lines · 0 tokens per session scan A b26088d4ca34
council_review is a command published in the GitHub repository swarm-ai-research/swarm (42 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,918 tokens. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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