Orchestrates a three-stage council of AI models for structured evaluation and synthesis.
npx skills add https://github.com/tomlupo/ai-playground --skill llm-council
Please help me install this Agent Skill. Skill: llm-council Source: https://github.com/tomlupo/ai-playground/tree/main/.claude/skills/llm-council Command: npx skills add https://github.com/tomlupo/ai-playground --skill llm-council
This Skill provides a multi-model council to obtain diverse AI viewpoints on questions, decisions, debates, and brainstorming by orchestrating a three-stage workflow: independent responses, peer review, and chairman synthesis.
To begin a council session, ask a question via /council:ask "<your question>" to receive independent responses and a synthesized recommendation. For rapid exploration, you can also use /council:brainstorm "<topic>" or /council:debate "<topic>".
High-intent search queries and answers about installing and using this skill.
To get diverse AI perspectives for technical decision-making, you can use a multi-model council that gathers independent responses, anonymized peer review, and a synthesized recommendation. This three-stage workflow reduces bias and surfaces tradeoffs across multiple models.
The best way to brainstorm architectural choices using multiple AI models is through a structured council pattern that generates independent viewpoints, conducts anonymized peer review, and delivers a synthesized recommendation to evaluate tradeoffs effectively.
Yes, you can use multi-model peer review for complex problem solving and product decisions. The council pattern applies independent responses and chairman synthesis to provide balanced analysis across domains, making it ideal for evaluating tradeoffs and creative ideation.
A multi-model council reduces bias in AI-generated recommendations by executing a three-stage workflow: models first provide independent responses, then anonymized peer review evaluates those responses, and finally a chairman synthesis produces a balanced recommendation.
You need a multi-model council instead of a single AI model for evaluating tradeoffs when your scenario requires multiple viewpoints, structured evaluation, and reduced bias. It is particularly useful for technical reviews, product decisions, and complex problem solving.
No, llm-council does not require any specific dependencies or components to run a council session. You can begin a session directly by asking a question to receive independent responses, peer review, and a synthesized recommendation without additional setup.
K-Dense-AISimulate a council of archetypes to generate diverse viewpoints on any question.
jshsakuraCompare tools and products with evidence-backed evaluation criteria and tradeoffs.
47networkCoordinate multiple LLMs through anonymous peer review and synthesis.
dazzajiCoordinate two reviewer agents to generate and merge independent reviews into a consensus artifact set.
