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 alinaqi/maggy --skill council-reviewgit clone --depth 1 https://github.com/alinaqi/maggyWrote 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/alinaqi/maggy/council-review)<a href="https://agentmods.dev/skills/alinaqi/maggy/council-review"><img src="https://agentmods.dev/badge/skills/alinaqi/maggy/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/alinaqi/maggy/council-review"><img src="https://agentmods.dev/badge/skills/alinaqi/maggy/council-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 4 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Excessive Agency · line 59 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00028 | $0.00766 |
| Opus 5.5 | $0.00011 | $0.00306 |
| Sonnet 5.5 | $0.00006 | $0.00153 |
| Haiku 4.5 | $0.00003 | $0.00077 |
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 2mo 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Council of Experts — Multi-Model Validation
When to Auto-Trigger
Plans (auto_validate_plans)
When you write a plan to ~/.claude/plans/, automatically validate it:
~/bin/validate-plan --threshold 2 ~/.claude/plans/<plan-file>.md
- 2+ of 3 approve → execute immediately
- 1 of 3 → surface reviewer feedback to user before proceeding
- 0 of 3 → revise plan, re-validate
Architecture Decisions (auto_review_architecture)
When making architectural changes (new services, API redesigns, database schema changes), run:
~/bin/review --all "Review this architecture: <summary>"
PR Review (auto_review_prs)
Before marking a PR as done, run:
~/bin/review --all --file <changed-files>
Configuration
Council behavior is configured in ~/.claude/council.yaml. The Maggy dashboard (Settings > Council) also manages this config.
Chief of the Council
chief: claude-fable-5 — Claude Fable 5 (Anthropic's most capable widely-released
model, GA 2026-06-09) leads every panel as the chief: it reviews first and casts
the deciding synthesis. Invoked via ~/bin/claude-fable-5. Override the chief in
~/.claude/council.yaml.
Reviewer Contexts
The chief leads each context, followed by the panel:
| Context | Default Reviewers | When |
|---|---|---|
plan |
Claude Fable 5 (chief), DeepSeek Pro, Codex, Gemini Pro | Before executing any plan |
review |
Claude Fable 5 (chief), DeepSeek Pro, Kimi | Code review, PR review |
architecture |
Claude Fable 5 (chief), DeepSeek Pro, Gemini Pro, Grok | System design, schema changes |
Threshold Rules
The threshold setting controls how many approvals are needed:
threshold: 2with 3 reviewers → need 2/3 to auto-execute- Clamped to [1, reviewer_count] — can't be 0 or exceed available reviewers
Model Inventory
All 13 tiers are listed in ~/.claude/council.yaml under models:. Each has:
id— unique identifiercmd— CLI command to invoke (null for Claude models, which are the host)tier— routing priority (0=cheapest, 12=most capable)label— human-readable name
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.
- 2mo ago First seen · 77 lines · 28 tokens per session scan A 326af45ba7dc
council-review is a skill published in the GitHub repository alinaqi/maggy (710 stars, last pushed 18d ago), licensed MIT. It adds 28 tokens to every session and 766 once invoked, about $0.0001 per session on Opus 5.5. 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 skills, from other repositories
claude-api
Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.
advisor-orchestrator-worker
Use when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple models, split work across a model team, run an advisor-worker loop, have a stronger model review the plan while cheap…
ring:adopting-lib-commons-huma-wrapper
Adopting the lib-commons/v5 shared Huma (OAS 3.1) OpenAPI wrapper + RFC 9457 problem model (commons/net/http/{openapi,problem}) in a Lerian Go service: wire openapi.New/ServeSpec + problem.Install (central >=500 scrub) on BOTH runtime and spec-gen paths, the per-rail problem.MapError flex seam, and rename-only spec…
rag-techniques-contribution-guidelines
Checks a RAGTechniques pull request against the repository's contribution guidelines (CONTRIBUTING.md): where new technique notebooks go, the README list entry and table row every new technique needs, the required notebook structure, and notebook hygiene. Use on any PR that adds or changes a notebook under…
ai-ml-development
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.
plankton-code-quality
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.