oh-my-opencode-slim/docs/council.md

Council Agent Guide

Multi-model consensus for cases where you want more than one model's judgment.

Table of Contents

• Overview
• Quick Setup
• Configuration
• Model Fallback Chain
• Choosing the Council Model vs Councillor Models
• Preset Examples
• Role Prompts
• Usage
• Compatibility Notes
• Troubleshooting

---

Overview

The Council agent runs several councillors in parallel, then synthesizes their outputs into one answer.

What you get

• Higher confidence from cross-checking multiple models
• Diverse perspectives across providers or model families
• Graceful degradation when only some councillors return
• Configurable presets for different cost/speed trade-offs

How it works

Each councillor in a preset is registered as a dynamic subagent named councillor-<name> (e.g. councillor-alpha, councillor-beta), each with its own configured model. The orchestrator dispatches all councillors in parallel via OpenCode's native task() tool at depth 1, and each councillor appears as its own TUI pane.

User / Orchestrator
        |
        v
Council agent (@council, your configured synthesizer model)
        |
        +--> task(): councillor-alpha (configured model)
        +--> task(): councillor-beta  (configured model)
        +--> task(): councillor-gamma (configured model)
        |
        v
Council agent synthesizes councillor results
        |
        v
Final answer

The council agent waits for all councillors to respond (or fail), then synthesizes their results into a single report.

---

Quick Setup

Add a council model and at least one council preset to your plugin config:

~/.config/opencode/oh-my-opencode-slim.json

{
  "preset": "openai",
  "presets": {
    "openai": {
      "council": { "model": "openai/gpt-5.6" }
    }
  },
  "council": {
    "presets": {
      "default": {
        "alpha": { "model": "openai/gpt-5.6-luna" },
        "beta": { "model": "google/gemini-3-pro" },
        "gamma": { "model": "openai/gpt-5.3-codex" }
      }
    }
  }
}

Then use it directly:

@council What is the safest migration strategy for this schema change?

---

Configuration

Top-level council config

{
  "council": {
    "default_preset": "default",

    "presets": {
      "default": {
        "alpha": { "model": "openai/gpt-5.6-luna" }
      }
    }
  }
}

Setting	Type	Default	Description
presets	object	-	Required. Named councillor presets
default_preset	string	"default"	Preset used when none is specified

Councillor config

Each entry inside a preset is one councillor:

Field	Type	Required	Description
model	string | array	Yes	A provider/model string, or an ordered fallback chain tried until one responds
variant	string	No	Optional variant/reasoning setting (applies to chain entries without their own)
prompt	string	No	Optional role guidance prepended to the user prompt

Council agent (synthesizer) config

The synthesizer model is not configured inside council.presets.

Configure it using the normal agent system:

{
  "presets": {
    "openai": {
      "council": { "model": "openai/gpt-5.6", "variant": "high" }
    }
  }
}

Or with a global override:

{
  "agents": {
    "council": {
      "temperature": 0.2
    }
  }
}

---

Model Fallback Chain

When model is a string, the councillor uses that single model.

When model is an array, the councillor walks the chain in order:

{
  "council": {
    "presets": {
      "review": {
        "reviewer": {
          "model": [
            "openai/gpt-5.6",
            { "id": "google/gemini-3-pro", "variant": "high" },
            "anthropic/claude-opus-4-6"
          ],
          "prompt": "Focus on bugs, edge cases, and failure modes."
        }
      }
    }
  }
}

Entries are provider/model strings or { "id", "variant" } objects. The councillor tries each entry in order until one responds. Empty responses are retried once per entry; other failures advance to the next entry. The councillor only fails once every entry in the chain is exhausted.

---

Choosing the Council Model vs Councillor Models

There are two separate model layers:

1. The Council agent model — the model behind @council itself, which does the final synthesis.
2. The councillor models — the models that actually fan out in parallel, configured under council.presets.<preset>.<councillor>.model.

Configure the Council agent when you want to change

• the final synthesizer model
• shared council-agent behavior like temperature or MCPs

Configure councillors when you want to change

• which models participate in the vote
• model diversity
• role-specific reviewer / architect / optimizer behavior

Important rule

agents.councillor can change shared councillor settings such as temperature, MCPs, and skills, but it does not choose the councillor model.

Councillor models always come from:

council.presets.<preset>.<councillor>.model

---

Preset Examples

Minimal second opinion

{
  "presets": {
    "openai": {
      "council": { "model": "openai/gpt-5.6" }
    }
  },
  "council": {
    "presets": {
      "second-opinion": {
        "reviewer": { "model": "openai/gpt-5.6-luna" }
      }
    }
  }
}

Balanced multi-provider council

{
  "presets": {
    "openai": {
      "council": { "model": "openai/gpt-5.6" }
    }
  },
  "council": {
    "default_preset": "balanced",
    "presets": {
      "balanced": {
        "alpha": { "model": "openai/gpt-5.6-luna" },
        "beta": { "model": "google/gemini-3-pro" },
        "gamma": { "model": "anthropic/claude-opus-4-6" }
      }
    }
  }
}

---

Role Prompts

Each councillor can receive its own steering prompt:

{
  "council": {
    "presets": {
      "review-board": {
        "reviewer": {
          "model": "openai/gpt-5.6-luna",
          "prompt": "Focus on bugs, edge cases, and failure modes."
        },
        "architect": {
          "model": "google/gemini-3-pro",
          "prompt": "Focus on maintainability, boundaries, and long-term design."
        },
        "optimizer": {
          "model": "openai/gpt-5.3-codex",
          "prompt": "Focus on performance, latency, and resource usage."
        }
      }
    }
  }
}

The councillor sees:

<role prompt>
---
<user prompt>

---

Usage

Invocation

@council Should we use a job queue or an outbox pattern here?

The orchestrator may also delegate to @council for high-stakes or ambiguous decisions.

What you see

Each councillor appears as its own TUI pane, dispatched in parallel. As they complete, their responses stream into the panes. Once all councillors have responded (or failed), the council agent synthesizes their results.

Output

Council responses include:

1. Council Response — the synthesized final answer.
2. Per-Councillor Details — each responding councillor's individual response, using the councillor names from the configured preset.
3. Council Summary — agreement, disagreement resolution, remaining uncertainty, and a consensus confidence rating of unanimous, majority, or split.

A footer tracks participation:

---
*Council: 2/3 councillors responded (alpha: gpt-5.6-luna, beta: gemini-3-pro)*

Failure behavior

Scenario	Behavior
Some councillors fail	Synthesize from the successful ones
All councillors fail	Return an error
Preset has zero councillors	Return an error

---

Compatibility Notes

Removed master fields

The council.master field and other master-prefixed fields have been removed. A deprecation warning is logged this release if a config still contains them, but they no longer have any effect.

Prefer this instead:

{
  "presets": {
    "openai": {
      "council": { "model": "openai/gpt-5.6" }
    }
  }
}

Reserved keys inside presets

• A preset key named master is ignored
• Legacy nested councillors objects are still accepted for backward compatibility

---

Troubleshooting

@council is missing

Council is only available when config.council exists.

Make sure your config includes a council block with at least one preset.

Preset not found

Check:

1. the preset name is correct
2. it exists under council.presets
3. default_preset points to a real preset when omitted at runtime

All councillors fail

Verify the configured model IDs exist in your OpenCode environment. Each councillor model must be a valid provider/model identifier your OpenCode setup can reach.