Agent skill

Council Review

by alinaqi in alinaqi/maggy

Multi-model validation council — auto-validate plans, architecture changes, and PRs via validate-plan/review before executing

MITAuto-check: notes

Install Council Review

skills CLI
$ npx skills add alinaqi/maggy --skill council-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alinaqi/maggy council-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/council-review .claude/skills/council-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
council-review
GitHub stars
707
Token cost
~756 tokens
SKILL.md length
314 words
Files
1
Skills in repo
71
Repo updated
First seen
Licence
MIT

At a glance

Multi-model validation council — auto-validate plans, architecture changes, and PRs via validate-plan/review before executing

  • SKILL.md covers When to Auto-Trigger, Configuration, Model Inventory and How This Skill is Used
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Council Review is an agent skill from alinaqi/maggy. Multi-model validation council — auto-validate plans, architecture changes, and PRs via validate-plan/review before executing

Its SKILL.md is about 760 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with DeepSeek. The repository describes itself as: What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center. The licence is MIT.

Example prompts

  • “/council-review”

Requirements

  • Pre-approved tools (allowed-tools): Bash, Read

What it can do on your machine

Read from SKILL.md and the folder at commit 72a456e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Council Review loads about 756 tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 314 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~756

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alinaqi/maggy at commit 72a456e, republished under its MIT licence (© alinaqi). 314 words, ~756 tokens.

Download SKILL.mdSave it as .claude/skills/council-review/SKILL.md (or your agent's skills folder).
name
council-review
description
Multi-model validation council — auto-validate plans, architecture changes, and PRs via validate-plan/review before executing
allowed-tools
Bash, Read
when-to-use
When you write a plan to ~/.claude/plans/, make architectural changes, or before marking a PR done; required for CLAUDE-tier tasks
user-invocable
false
effort
high

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:

bash
~/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:

bash
~/bin/review --all "Review this architecture: <summary>"
PR Review (auto_review_prs)

Before marking a PR as done, run:

bash
~/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:

ContextDefault ReviewersWhen
planClaude Fable 5 (chief), DeepSeek Pro, Codex, Gemini ProBefore executing any plan
reviewClaude Fable 5 (chief), DeepSeek Pro, KimiCode review, PR review
architectureClaude Fable 5 (chief), DeepSeek Pro, Gemini Pro, GrokSystem design, schema changes
Threshold Rules

The threshold setting controls how many approvals are needed:

  • threshold: 2 with 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 identifier
  • cmd — CLI command to invoke (null for Claude models, which are the host)
  • tier — routing priority (0=cheapest, 12=most capable)
  • label — human-readable name

Use POST /api/models/health to verify all models are responding.

How This Skill is Used

This skill is loaded by Claude Code on session start. It provides the behavioral rules for when to invoke multi-model validation. The actual execution happens via ~/bin/validate-plan and ~/bin/review which are already installed.

Do not skip council validation for CLAUDE-tier tasks. The whole point is that architecture and security decisions get independent verification before execution.

© alinaqi, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/council-review of alinaqi/maggy.

Open the folder on GitHubat commit 72a456e

Compare with similar skills

Council Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Council Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Council Review this skillalinaqi/maggy707—~756Automated safety check: NotesMIT
ModLens Image Vision Bridgeliustack/modlens4.2k—~1.3kAutomated safety check: NotesMIT
Distilly Person Profile Buildertitanwings/distilly25k—~15kAutomated safety check: NotesMIT
Evals Contextzgsm-ai/costrict4.5k1 repos~1.9kAutomated safety check: PassApache-2.0
J SpaceTiger3807861189/J-Space-Cognition-Suite3k—~3kAutomated safety check: PassApache-2.0
Weavebench Cua ReproduceAMAP-ML/LongHorizon-Harness1.7k—~1.6kAutomated safety check: PassMIT

Similar skills

  • Gives text-only models sight by running the modlens CLI on an image path or URL and returning structured JSON evidence with transcribed text, layout and semantics.

    4.2k GitHub stars~1.3k tokensUpdated 7 days ago
    AI & LLM EngineeringAuto-check: notes
  • Distills source material about a colleague, a relationship or a celebrity into reusable Person Profiles that an agent can later work from, in English or Chinese.

    25k GitHub stars~15k tokensUpdated 18 days ago
    Agent WorkflowsAuto-check: notes
  • Evals Context

    zgsm-ai/costrict

    Provides context about the CoStrict evals system structure in this monorepo.

    4.5k GitHub starsUsed in 1 repo~1.9k tokens
    AI & LLM EngineeringAuto-check passed
  • J Space

    Tiger3807861189/J-Space-Cognition-Suite

    Operate a selective workspace for complex reasoning, long tasks, repository engineering, coordinated agents, and authorized security analysis.

    3k GitHub stars~3k tokensUpdated 27 days ago
    Frontend & DesignAuto-check passed
  • Weavebench Cua Reproduce

    AMAP-ML/LongHorizon-Harness

    Reproduce CUA-Harness experiments on WeaveBench from a GitHub checkout.

    1.7k GitHub stars~1.6k tokensUpdated 1 mo ago
    Testing & QAAuto-check passed
  • Vision Skills

    Anionex/agent-vision-toolkit

    Local vision CLIs: glance (describe/ask/OCR an image), ground (locate a target, pixel box), detect (element inventory), trace (image to SVG geometry), crop (cut a pixel box to a file), and…

    1.2k GitHub stars~4k tokensUpdated 3 days ago
    Productivity & AutomationAuto-check passed

More from alinaqi/maggy

All 71 skills in this repo
  • Aeo Optimization

    alinaqi/maggy

    AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

    707 GitHub stars~3.7k tokensUpdated 17 days ago
    Auto-check passed
  • Agent Teams

    alinaqi/maggy

    Claude Code Agent Teams - default team-based development with strict TDD pipeline enforcement

    707 GitHub stars~5k tokensUpdated 17 days ago
    Auto-check: notes
  • AI Models

    alinaqi/maggy

    Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate

    707 GitHub stars~4.1k tokensUpdated 17 days ago
    Auto-check passed
  • Android Java

    alinaqi/maggy

    Android Java development with MVVM, ViewBinding, and Espresso testing

    707 GitHub stars~3.9k tokensUpdated 17 days ago
    Auto-check: notes
  • Android Kotlin

    alinaqi/maggy

    Android Kotlin development with Coroutines, Jetpack Compose, Hilt, and MockK testing

    707 GitHub stars~3k tokensUpdated 17 days ago
    Auto-check passed
  • Autonomous Testing

    alinaqi/maggy

    AI-driven testing agent that auto-discovers, generates, executes, evaluates, and fixes tests for any project type

    707 GitHub stars~1.1k tokensUpdated 17 days ago
    Auto-check passed

Works with

Questions about Council Review

What does Council Review do?

Multi-model validation council — auto-validate plans, architecture changes, and PRs via validate-plan/review before executing. Council Review is an agent skill from alinaqi/maggy.

How do I install Council Review in Claude Code?

Run `npx skills add alinaqi/maggy --skill council-review -a claude-code`. Or copy the skill folder (skills/council-review in alinaqi/maggy) into .claude/skills/council-review in your project. Claude Code loads it when a task matches its description.

How do I install Council Review in Codex?

Run `npx skills add alinaqi/maggy --skill council-review -a codex`. Or copy the skill folder (skills/council-review in alinaqi/maggy) into .agents/skills/council-review in your project. Codex loads it when a task matches its description.

Can I use Council Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alinaqi/maggy --skill council-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/council-review, .gemini/skills/council-review, .github/skills/council-review and .opencode/skills/council-review in your project.

What does Council Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Council Review is instructions for the agent only. Its frontmatter pre-approves these tools: Bash, Read.

Does Council Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Council Review safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Council Review use?

Council Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Council Review use?

About 756 tokens (SKILL.md is roughly 3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Council Review?

Skills that share tags, products or a category with Council Review: ModLens Image Vision Bridge (liustack/modlens, 4.2k stars), Distilly Person Profile Builder (titanwings/distilly, 25k stars), Evals Context (zgsm-ai/costrict, 4.5k stars) and J Space (Tiger3807861189/J-Space-Cognition-Suite, 3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Council Review?

alinaqi (a GitHub user) maintains it in alinaqi/maggy, which has 707 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on September 24, 2026.

Source: alinaqi/maggy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.