Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Provider config from env (OPENAI/ANTHROPIC/FIREWORKS/OPENROUTER/custom OpenAI-compatible base URL). Persists transcript to a wiki page when --wiki
Installs just this skill. Get the whole plugin for auto-invocation.
⚡ How it fires
How this skill gets triggered: by you, by Claude, or both.
Fires itselfClaude auto-loads it when your prompt matches the work.
You can call itInvoke it directly when you want it.
Slash command/llm-council
👁️ Context preview
The summary Claude sees to decide when to auto-load this skill.
Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Provider config from env (OPENAI/ANTHROPIC/FIREWORKS/OPENROUTER/custom OpenAI-compatible base URL). Persists transcript to a wiki page when --wiki
---name: llm-council
description: Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Provider config from env (OPENAI/ANTHROPIC/FIREWORKS/OPENROUTER/custom OpenAI-compatible base URL). Persists transcript to a wiki page when --wiki <slug> is passed. Use when the user wants multiple AI perspectives, consensus-building, or the "LLM Council" approach for high-stakes reviews, plan critique, or contested learning rules.
user-invocable: true
allowed-tools: Read, Write, Bash, AskUserQuestion
---# LLM Council
Karpathy's LLM Council pattern, provider-agnostic. dair-academy's version hardcoded Fireworks; ours reads any OpenAI-compatible endpoint via env.
## When to use
- High-stakes plan review (`/plan` crosses N-file threshold)
- Conflicting learning-rules → re-resolve via vote
- User invokes `/council "<query>"` or `/wiki council`
- Architecture decisions where you want multiple viewpoints captured
- Persisting deliberation as a wiki page for future reference
## Three phases
1. **Independent**: each model answers in parallel
2. **Ranking**: each model ranks anonymized peer responses
3. **Synthesis**: chairman model reads all responses + rankings → final answer
## Provider config
Provider chosen via env. First-match wins:
node $SKILL_ROOT/scripts/council.js show <session-id>
```
`--wiki <slug>` writes the full transcript to `<wiki>/derived/council/<session-id>.md` and registers it via `wiki-cli.js page` so it shows in FTS5 search.
├── phase3_synthesis.txt # chairman's final answer
└── final_output.md # human-readable bundle
```
Console prints the markdown bundle. Pipe to `pbcopy` / `tee` as needed.
## Hard rules
1. Never skip the ranking phase. It's the core of the council pattern.
2. Save raw responses to disk verbatim. No summarization in storage.
3. Anonymize responses for ranking — models see `Response A/B/C/...`, not peer names.
4. The chairman sees both real names AND rankings.
5. Display all three phases to the user. No phase elision.
## Cost awareness
The script logs per-call latency + tokens on supported providers. Multiply by your provider rate to estimate. Council cost grows linearly with `len(models)^2` (each model ranks all others) plus the chairman.
Default council size: 3-5 models. More models = exponentially more ranking calls.
## Use with wiki
```
/wiki council agent-memory "should we adopt episodic memory in our agents?"
```
Loads `agent-memory` wiki context as system prompt prefix, runs council, persists transcript as `wiki/derived/council/<id>.md`. The transcript becomes searchable via `/wiki ask`.
