---
name: council-a398f30e5ba4
description: "Your personal board of AI advisors — the only skill that uses truly different AI models (not one model role-playing). Get better answers to hard questions by having 3-5 models from different providers analyze independently, then synthesizing consensus, disagreements, and action items. Each model brings genuinely different training and reasoning — catching blind spots that same-model approaches miss. Zero external dependencies: uses native OpenClaw sub-agents, no Python scripts, no API keys beyond your existing model config. Use when: user says /council, or asks for multi-model analysis of a decision, architecture, strategy, or any complex problem."
---

# Consilium — True Multi-Model Deliberation

Ask a hard question → 3-5 AI models from **different providers** analyze it independently → you get a synthesis with consensus, disagreements, action items, and minority opinions.

**Unlike other council skills:** this uses genuinely different models (Anthropic + OpenAI + Google + others), not one model playing multiple roles. Different training data = different blind spots = better coverage.

**Always respond in the same language as the user's question.**

## Examples

- `/council Should we migrate from monolith to microservices given our 4-person team?`
- `/council --profile fast Evaluate the risks of this investment strategy`
- `/council How to resolve a complex equity dispute with my co-founder?`
- After results: *"Tell me more about what Gemini said on point 3"* (follow-up with specific panelist)

## Requirements

- **Minimum 3 models** from different providers in `agents.defaults.models` allowlist
- Tools: `sessions_spawn`, `subagents`, `sessions_history` (enabled by default)
- Each council run = 3-5 API calls (one per model) + synthesis
- No additional API keys, Python scripts, or external dependencies

## Privacy & Data

- Your question is sent to each model provider in your panel. Only use models/providers you trust.
- `council-panel.json` (saved to workspace root) contains only model names and slot assignments, not queries or responses.
- Panelist responses exist only in sub-agent session memory and are auto-archived per your OpenClaw settings.
- No data is sent to external services beyond your configured model providers.

## Panel

On first use, check available models and ask the user to confirm the panel. Save to workspace root as `council-panel.json` for reuse. User can re-run panel selection anytime with `--models`.

### Slot roles (fill from available models)

| Slot | Role | Good candidates |
|------|------|-----------------|
| Deep thinker | Nuance, system thinking | Claude Opus, GPT-5, Gemini Pro |
| Pragmatist | Concise, actionable | Claude Sonnet, GPT-mini, Gemini Flash |
| Broad analyst | Wide knowledge, structure | GPT-5, Gemini Pro, Claude Opus |
| Technical | Rigor, edge cases | Gemini Pro, Claude Sonnet, GLM |
| Contrarian | Challenge assumptions | GLM, any model with contrarian lens |

**Rules:** Each slot = different model. Prefer different providers. Min 3 models to run. If fewer than 3 available, inform user.

### Example `council-panel.json`

```json
{
  "panel": [
    { "slot": "deep_thinker", "model": "anthropic/claude-opus-4-6", "lens": "Deep analysis" },
    { "slot": "pragmatist", "model": "anthropic/claude-sonnet-4-5", "lens": "Pragmatic" },
    { "slot": "broad_analyst", "model": "github-copilot/gpt-5.2", "lens": "Broad knowledge" }
  ],
  "confirmed": "2026-02-24"
}
```

## Profiles

- **thorough** (default): All panel slots, quorum = max(slots - 2, 2)
- **balanced**: 3 strongest slots, quorum 2
- **fast**: 2 fastest slots, quorum 2

## Workflow

1. **Dispatch** — spawn panelists in parallel (`sessions_spawn`, mode=run, timeout 120s). Assign unique lens per slot. Detect question language, hardcode in prompt. Tell user: "Panel dispatched, ~60s. Send a follow-up when ready."
2. **Collect** — on user's follow-up: `subagents list` → `sessions_history`. Synthesize when quorum met.
3. **Debate** (only if `--rounds 2`) — anonymized digest → rebuttals. See `references/PROTOCOL.md`.
4. **Synthesize** — produce output below.

## Output Format

```
## Council of Experts
**Question:** ... | **Panel:** ... | **Profile:** ...
---
### Positions
**{Model}** ({lens}) — {2-3 sentence summary}

### ✅ Consensus
### ⚡ Disagreements
### 🗣️ Minority opinions

### 🎯 Synthesis
Agreement: 🟢 strong (4-5) | 🟡 mixed (3) | 🔴 split

### 📋 Action Items
1. **{Highest priority}** — {effort/time estimate}
2. **{Next action}** — {estimate}
3. **{Next action}** — {estimate}
```

Randomize position order. Quote with attribution. Preserve minority views. Never fabricate consensus. Section headers and content in user's language.

## Follow-up

After synthesis, the user can drill deeper with a specific panelist:
- *"Tell me more about what GPT said on point 2"*
- *"I want the contrarian's take on the action items"*

Use `sessions_history` to retrieve that panelist's full response, then expand on the specific point in that model's perspective.

## Flags

`--profile thorough|balanced|fast` · `--models <list>` · `--skip <model>` · `--rounds 2` · `--quorum N` · `--timeout N` · `--lens "..."` · `--lenses "a,b,c"`

Prompt templates, debate mechanics, error handling → `references/PROTOCOL.md`


---
Source attribution: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/consilium/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 skill-library-mcp contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/consilium/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Development & Engineering, Product Management, Sales
Roles: Business Development, Data Scientist, Growth Product Manager, ML / AI Engineer, Product Manager
Specialties: Specialty not specified
Tools: Anthropic API, Google Gemini, OpenAI API, Openclaw
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 06a5da4800dda15b058050c2ff85bf3596474f2a956e248315c5a1ab4eb30cb7