Multi-agent planning council that orchestrates independent implementation plans, anonymizes them, then merges into one final plan.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add am-will/codex-skills --skill llm-councilCompatible with
Supported agents
Supports configurable planner agents (Codex, Claude, Gemini, OpenCode, or custom CLI commands) running in parallel, with optional judge override
Conducts structured intake questioning before plan generation to clarify ambiguities, constraints, and success criteria
Produces validated Markdown outputs with automatic retry logic (up to 2 attempts) and failur
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionllm-councilExecute the skills CLI command in your project's root directory to begin installation:
epx add am-will/codex-skills --skill llm-councilFetches llm-council from am-will/codex-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/llm-council
Restart Cursor to activate llm-council. Access via /llm-councilin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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We added llm-council from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: llm-council is focused, and the summary matches what you get after install.
llm-council reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend llm-council for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for llm-council matched our evaluation — installs cleanly and behaves as described in the markdown.
llm-council reduced setup friction for our internal harness; good balance of opinion and flexibility.
llm-council has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in llm-council — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: llm-council is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added llm-council from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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