Agent skill

Council

by warpdotdev in warpdotdev/common-skills

Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation.

MITAuto-check passedSecurity

Install Council

skills CLI
$ npx skills add warpdotdev/common-skills --skill council -a claude-code

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

GitHub CLI
$ gh skill install warpdotdev/common-skills council --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/warpdotdev/common-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/council .claude/skills/council && 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
GitHub stars
606
Used in
1 other repo
Token cost
~1.8k tokens
SKILL.md length
898 words
Files
1
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation.

  • Works in 6 steps: Frame the council question → Choose council members → Brief before launching → …
  • The user asks for a council
  • SKILL.md covers Workflow, Final answer template and Practical notes
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Council is an agent skill from warpdotdev/common-skills. Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation. Use this skill whenever the user asks for a council, second opinions, multiple agents/models to evaluate one question, parallel investigation, red-team/blue-team comparison, or help deciding between competing technical approaches.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Security, covering Security operations, Red teaming and adversary simulation and Subagents. The licence is MIT.

When your agent uses it

  • The user asks for a council
  • Second opinions
  • Multiple agents/models to evaluate one question
  • Parallel investigation

Example prompts

  • “/council”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Frame the council question
  2. Choose council members
  3. Brief before launching
  4. Ask for structured reports
  5. Collect reports
  6. Synthesize the recommendation

What it can do on your machine

Read from SKILL.md and the folder at commit 69b4753. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    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 markdown).

    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 loads about 1.8k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 898 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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 passed

The automated check found no risky patterns in SKILL.md.

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 warpdotdev/common-skills at commit 69b4753, republished under its MIT licence (© warpdotdev). 898 words, ~1,773 tokens.

Download SKILL.mdSave it as .claude/skills/council/SKILL.md (or your agent's skills folder).
name
council
description
Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation. Use this skill whenever the user asks for a council, second opinions, multiple agents/models to evaluate one question, parallel investigation, red-team/blue-team comparison, or help deciding between competing technical approaches.

Council

Use this skill to coordinate multiple subagents investigating the same question, with different models first and different assigned perspectives second, then synthesize their reports into one recommendation.

This skill is best for judgment-heavy tasks: architecture tradeoffs, risky bug fixes, code review red-teaming, rollout decisions, incident analysis, and “is this alternative worth pursuing?” questions.

Workflow

1. Frame the council question

State the decision the council should answer in one sentence. Identify:

  • the competing options or hypothesis under review;
  • the codebase, branch, PR, issue, design, or artifact to inspect;
  • whether agents should be read-only or may make code changes;
  • the final decision criteria, such as correctness, risk, implementation cost, testability, rollout safety, or product behavior.

If the user’s request is ambiguous, ask only the minimum clarification needed. Otherwise choose sensible defaults and proceed.

2. Choose council members

Prioritize model diversity. A council should not default to three agents on the same model with different angles; use that only when the available launch configuration cannot provide multiple useful models, or when the user explicitly asks for one model. If model diversity is unavailable, say so briefly before falling back to perspective-only diversity.

Preferred default roster for a three-member council:

  • Opus 4.7 or the strongest available Claude/Opus reasoning model: architecture, correctness, and edge-case analysis.
  • GPT 5.5 or the strongest available GPT/Codex model: implementation-grounded review, feasibility, and test strategy.
  • An open-source model such as Kimi 2.6, GLM 5.1, or the strongest available OSS/local model: contrarian critique, hidden assumptions, and alternative framing.

If one of these exact models is unavailable in the active harness, use the closest available model from that family and note the substitution. If no open-source model is available, use a third distinct frontier model if possible; otherwise use the strongest remaining model with a deliberately adversarial or specialist angle.

Assign both a model and an angle to each member. Avoid making the angles redundant with the models; for example, do not ask all members to do general architecture review. Useful angle combinations include:

  • architect/correctness reviewer;
  • implementation/testability reviewer;
  • red-team, security, performance, or product-risk reviewer;
  • contrarian “argue against the obvious solution” reviewer.

When different children need different models, launch them in separate run_agents calls because model selection is run-wide. If the requested model resolves differently than expected, treat the resolved launch settings as authoritative and continue unless they make the task infeasible.

When using non-default harnesses, choose valid model IDs for that harness. For example, Claude Code may expose claude-opus-4-7, Codex may expose gpt-5.5, and open-source models depend on the currently configured local or remote provider. Do not invent unsupported model IDs; if a desired model is not available, select the closest supported substitute and preserve the intended angle diversity.

For read-only investigations, keep all children in the same checkout and explicitly tell them not to edit files. For implementation or prototyping councils, give each local child its own git worktree and branch so they cannot collide.

3. Brief before launching

For explicit orchestration requests, briefly tell the user which council members you plan to launch and what each will investigate, then wait for approval before calling run_agents.

The shared brief should include:

  • repository path or artifact location;
  • current branch or base context;
  • the exact question to answer;
  • relevant background and known concerns;
  • required files/symbols to inspect, if known;
  • constraints, especially read-only/no commits/no PRs;
  • expected report format.

Keep launch prompts short enough that task titles stay compact. If a long brief causes launch validation issues, launch with a minimal prompt and send the full brief to the child agents immediately afterward.

Show full SKILL.md (310 more words)Show less
4. Ask for structured reports

Ask every council member to return:

  1. exact file paths, symbols, docs, or evidence inspected;
  2. the current behavior or current implementation;
  3. the alternative being evaluated;
  4. correctness risks and edge cases;
  5. implementation and testing cost;
  6. recommendation: keep current approach, pursue alternative, or use a hybrid;
  7. confidence level and unknowns.

Encourage independence. Do not share one child’s findings with the others unless you are intentionally doing a second-round critique.

5. Collect reports

Read completion messages as they arrive. Do not rely on lifecycle success alone; the useful output is in the child’s report.

If a report is missing key evidence or makes an unsupported claim, send a focused follow-up question to that same child rather than launching a replacement. Reuse existing children for follow-ups because they retain context.

6. Synthesize the recommendation

Compare the reports by evidence quality, not by vote count. In the final answer:

  • lead with the recommendation;
  • call out consensus and disagreements;
  • explain why the recommended option wins against the decision criteria;
  • explicitly address the user’s stated concern;
  • include relevant file paths/symbols without overloading the answer;
  • distinguish “do now” from optional future hardening;
  • mention confidence and material unknowns.

Prefer a concise decision memo over a transcript summary. The user needs the distilled recommendation, not every intermediate detail.

Final answer template

Use this shape unless the task calls for something different:

markdown
## Recommendation

[One or two sentences with the decision.]

## Why

- [Key reason 1]
- [Key reason 2]
- [Key reason 3]

## Tradeoffs and risks

- [Risk or caveat]
- [Testing/rollout implication]

## Final call

[Concrete next step: merge current change, pursue alternative, hybrid, run tests, etc.]

Practical notes

  • If the council is read-only, tell children not to modify files, commit, create branches, or open PRs.
  • If the council involves PR or branch work, follow the repository’s normal version-control rules and use isolated worktrees for parallel local edits.
  • If the council is about code review feedback, mark review comments resolved only after the underlying issue is actually addressed.
  • Do not expose internal child agent IDs in user-facing summaries unless the user explicitly asks for them.

© warpdotdev, 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 .agents/skills/council of warpdotdev/common-skills.

Open the folder on GitHubat commit 69b4753

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in warpdotdev/common-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Council 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 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Council this skillwarpdotdev/common-skills6061 repos~1.8kAutomated safety check: PassMIT
Cybersecurityohmyjahh/xquads-squads276—~895Automated safety check: PassMIT
Rational Red Blue Debatedigoal/blog8.6k—~2.2kAutomated safety check: PassGPL-2.0
Detecting Azure Service Principal Abusemukul975/Anthropic-Cybersecurity-Skills34k—~2.1kAutomated safety check: PassApache-2.0
Detecting Pass The Hash Attacksmukul975/Anthropic-Cybersecurity-Skills34k—~904Automated safety check: PassApache-2.0
Detecting Privilege Escalation Attemptsmukul975/Anthropic-Cybersecurity-Skills34k—~922Automated safety check: PassApache-2.0

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Categories

Questions about Council

What does Council do?

Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation. Council is an agent skill from warpdotdev/common-skills. Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation.

When should I use Council?

Council fits situations like: the user asks for a council; second opinions; multiple agents/models to evaluate one question; parallel investigation.

How do I install Council in Claude Code?

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

How do I install Council in Codex?

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

Can I use Council 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 warpdotdev/common-skills --skill council -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, .gemini/skills/council, .github/skills/council and .opencode/skills/council in your project.

What does Council need to run?

SKILL.md names no scripts, command-line tools or credentials: Council is instructions for the agent only.

Does Council 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 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Council use?

Council 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 use?

About 1.8k tokens (SKILL.md is roughly 7.1k 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?

Skills that share tags, products or a category with Council: Cybersecurity (ohmyjahh/xquads-squads, 276 stars), Rational Red Blue Debate (digoal/blog, 8.6k stars), Detecting Azure Service Principal Abuse (mukul975/Anthropic-Cybersecurity-Skills, 34k stars) and Detecting Pass The Hash Attacks (mukul975/Anthropic-Cybersecurity-Skills, 34k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Council?

warpdotdev (a GitHub organization) maintains it in warpdotdev/common-skills, which has 606 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on September 30, 2026.

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