Council Agent Guide

Multi-LLM consensus system that runs several models in parallel and synthesises their best thinking into one answer.

Overview
Quick Setup
Configuration
Preset Examples
Role Prompts
Usage
Timeouts & Error Handling
Troubleshooting
Advanced

Overview

The Council agent sends your prompt to multiple LLMs (councillors) in parallel, then the council agent itself synthesises the optimal answer from all councillor responses.

Key Benefits

Higher confidence — consensus across models reduces single-model blind spots
Diverse perspectives — different architectures catch different issues
Graceful degradation — the council agent synthesises from whatever councillor results came back
Configurable presets — different council compositions for different tasks

How It Works

User prompt
    │
    ├──────────────┬──────────────┐
    ▼              ▼              ▼
 Councillor A  Councillor B  Councillor C
 (model X)     (model Y)     (model Z)
🔍 read-only   🔍 read-only   🔍 read-only
    │              │              │
    └──────────────┴──────────────┘
                   │
                   ▼
          Council Agent
          (synthesises)
                   │
                   ▼
         Synthesised response

Quick Setup

Step 1: Add Council Configuration

Edit ~/.config/opencode/oh-my-opencode-slim.json (or .jsonc):

{
  "council": {
    "presets": {
      "default": {
        "alpha": { "model": "openai/gpt-5.4-mini" },
        "beta":  { "model": "google/gemini-3-pro" },
        "gamma": { "model": "openai/gpt-5.3-codex" }
      }
    }
  }
}

Step 2: Use the Council Agent

Talk to the council agent directly:

@council What's the best approach for implementing rate limiting in our API?

Or let the orchestrator delegate when it needs multi-model consensus.

That's it — the council runs, synthesises, and returns one answer.

Configuration

Council Settings

Configure in ~/.config/opencode/oh-my-opencode-slim.json (or .jsonc):

{
  "council": {
    "default_preset": "default",
    "presets": {
      "default": { /* councillors */ }
    },
    "timeout": 180000
  }
}

Setting	Type	Default	Description
`presets`	object	—	Required. Named councillor presets (see below)
`default_preset`	string	`"default"`	Which preset to use when none is specified
`timeout`	number	`180000`	Per-councillor timeout in ms (3 minutes)
`councillor_retries`	number	`3`	Max retries per councillor on empty provider response (0–5). Each retry creates a fresh session

Councillor Configuration

Each councillor within a preset:

Field	Type	Required	Description
`model`	string	Yes	Model ID in `provider/model` format
`variant`	string	No	Model variant (e.g., `"high"`, `"low"`)
`prompt`	string	No	Role-specific guidance injected into the councillor's user prompt (see Role Prompts)

Constraints

Councillors run as agent sessions with read-only codebase access — they can read files, search by name (glob), search by content (grep), search by AST pattern (codesearch), and query the language server (LSP). They cannot modify files, run shell commands, or spawn subagents. This makes council responses grounded in actual code rather than guessing.
The council agent itself synthesises the final answer from councillor results using its own model.
Councillor agents can be configured (model, temperature, MCPs, skills) via the standard agents.councillor preset override.

Preset Examples

1-Councillor: Second Opinion

Use a single councillor when you want a second model's take without overhead:

{
  "council": {
    "presets": {
      "second-opinion": {
        "reviewer": { "model": "openai/gpt-5.4" }
      }
    }
  }
}

When to use: Quick sanity check from a different model.

2-Councillor: Compare & Contrast

Two councillors with different models:

{
  "council": {
    "presets": {
      "compare": {
        "analyst":  { "model": "openai/gpt-5.4" },
        "creative": { "model": "google/gemini-3-pro" }
      }
    }
  }
}

When to use: Architecture decisions where you want perspectives from two different providers.

3-Councillor: Balanced Council

The default setup — three diverse models:

{
  "council": {
    "presets": {
      "default": {
        "alpha": { "model": "openai/gpt-5.4-mini" },
        "beta":  { "model": "google/gemini-3-pro" },
        "gamma": { "model": "openai/gpt-5.3-codex" }
      }
    }
  }
}

When to use: General-purpose consensus. Good balance of speed, cost, and diversity.

N-Councillor: Full Review Board

As many councillors as you need — the system runs them all in parallel:

{
  "council": {
    "presets": {
      "full-board": {
        "alpha":   { "model": "anthropic/claude-opus-4-6" },
        "bravo":   { "model": "openai/gpt-5.4" },
        "charlie": { "model": "openai/gpt-5.3-codex" },
        "delta":   { "model": "google/gemini-3-pro" },
        "echo":    { "model": "openai/gpt-5.4-mini" }
      }
    },
    "timeout": 300000
  }
}

When to use: High-stakes design reviews or complex architectural decisions where maximum model diversity matters. Increase timeout since there are more responses to collect.

Multiple Presets

Define several presets and choose at invocation time:

{
  "council": {
    "default_preset": "balanced",
    "presets": {
      "quick": {
        "fast": { "model": "openai/gpt-5.4-mini" }
      },
      "balanced": {
        "alpha": { "model": "openai/gpt-5.4-mini" },
        "beta":  { "model": "google/gemini-3-pro" }
      },
      "heavy": {
        "analyst":   { "model": "anthropic/claude-opus-4-6" },
        "coder":     { "model": "openai/gpt-5.3-codex" },
        "reviewer":  { "model": "google/gemini-3-pro" }
      }
    }
  }
}

How to select a preset:

Caller	How
User via `@council`	The council agent can pass a `preset` argument to the `council_session` tool
Orchestrator delegates	Orchestrator invokes `@council`, which selects the preset
No preset specified	Falls back to `default_preset` (defaults to `"default"`)

Role Prompts

Councillors accept an optional prompt field that injects role-specific guidance into the user prompt. This lets you steer each participant's behaviour without changing the system prompt.

Councillor prompt — prepended to the user prompt before the divider:

<role prompt>
---
<user prompt>

Example: Specialised Review Board

Councillors accept an optional prompt field:

{
  "council": {
    "presets": {
      "review-board": {
        "reviewer": {
          "model": "openai/gpt-5.4",
          "prompt": "You are a meticulous code reviewer. Focus on edge cases, error handling, and potential bugs."
        },
        "architect": {
          "model": "google/gemini-3-pro",
          "prompt": "You are a systems architect. Focus on design patterns, scalability, and maintainability."
        },
        "optimiser": {
          "model": "openai/gpt-5.3-codex",
          "prompt": "You are a performance specialist. Focus on latency, throughput, and resource usage."
        }
      }
    }
  }
}

Without a prompt, the councillor uses its default behaviour — no changes to the prompt.

Usage

Direct Invocation (User)

Talk to the council agent like any other agent:

@council Should we use event sourcing or CRUD for the order service?

The council agent runs councillors in parallel and synthesises the result directly.

Orchestrator Delegation

The orchestrator can delegate to @council when it needs multi-model consensus:

This is a high-stakes architectural decision. @council, get consensus on the database migration strategy.

The orchestrator's prompt includes guidance on when to delegate to council:

Delegate when: Critical decisions needing diverse model perspectives • High-stakes architectural choices where consensus reduces risk • Ambiguous problems where multi-model disagreement is informative

Reading the Output

Council responses include a summary footer:

<synthesised answer>

---
*Council: 3/3 councillors responded (alpha: gpt-5.4-mini, beta: gemini-3-pro, gamma: gpt-5.3-codex)*

If some councillors failed:

<synthesised answer from available councillors>

---
*Council: 2/3 councillors responded (alpha: gpt-5.4-mini, beta: gemini-3-pro)*

Timeouts & Error Handling

Timeout Behaviour

Timeout	Default	Scope
`timeout`	180000 ms (3 min)	Per-councillor — each councillor gets this much time

Councillors that don't respond in time are marked timed_out. The council agent proceeds with whatever results came back.

Graceful Degradation

Scenario	Behaviour
Some councillors fail	Council agent synthesises from the available results
All councillors fail	Returns error immediately
Councillor gets empty response	Retries up to `councillor_retries` times with fresh sessions

Empty Response Detection

Providers sometimes silently drop requests — returning zero tokens with no error. This is detected automatically:

Background tasks (@explorer, @fixer, etc.): Empty responses trigger the fallback chain (next model in fallback.chains). Controlled by fallback.retry_on_empty (default true). Set to false to accept empty responses without retrying.
Council councillors: Empty responses trigger up to councillor_retries fresh sessions (default 3). Only "Empty response from provider" errors are retried — timeouts and other failures return immediately.

To disable empty-response retry globally:

{
  "fallback": { "retry_on_empty": false }
}

Troubleshooting

Council Not Available

Problem: @council agent doesn't appear or tool is missing

Solutions:

Verify council is configured in your plugin config:

cat ~/.config/opencode/oh-my-opencode-slim.json | grep -A 5 '"council"'

Ensure at least one preset with one councillor is defined
Restart OpenCode after config changes

All Councillors Timing Out

Problem: "All councillors failed or timed out"

Solutions:

Increase timeout:
```
{ "council": { "timeout": 300000 } }
```
Verify model IDs — models must be in provider/model format and available in your OpenCode configuration
Check provider connectivity — ensure the model providers are reachable

Preset Not Found

Problem: Preset "xyz" not found

Solutions:

Check the preset name matches exactly (case-sensitive)
Verify the preset exists under council.presets in your config
If not specifying a preset, check default_preset points to an existing one

Subagent Depth Exceeded

Problem: "Subagent depth exceeded"

This happens when the council is nested too deep (council calling council, or orchestrator → council → council). The default max depth is 3.

Solutions:

Avoid patterns where the orchestrator delegates to council, which then delegates back to orchestrator
Use council as a leaf agent — it should not be chained recursively

Advanced

Model Selection Strategy

Choose models from different providers for maximum perspective diversity:

Strategy	Example
Diverse providers	OpenAI + Google + Anthropic
Same provider, different tiers	`gpt-5.4` + `gpt-5.4-mini`
Specialised models	Codex (code) + GPT (reasoning) + Gemini (analysis)

Cost Considerations

Each councillor is one agent session → N councillors = N sessions. Councillors may use multiple tool calls within their session (read, grep, etc.), which increases token usage but grounds responses in actual code.
The 1-councillor preset is the most cost-effective (1 call total)

Council Agent Mode

The council agent is registered with mode: "all" in the OpenCode SDK, meaning it works as both:

Primary agent — users can talk to it directly via @council
Subagent — the orchestrator can delegate to it

This is intentional: council is useful both as a user-facing tool for deliberate consensus-seeking and as a subagent the orchestrator can invoke for high-stakes decisions.

Customising Councillor Agents

Councillor is a registered agent, so you can customise it using the standard agents override system:

{
  "agents": {
    "councillor": {
      "model": "openai/gpt-5.4",
      "temperature": 0.3,
      "mcps": ["grep_app", "context7"]
    }
  }
}

Defaults: | Agent | Model | MCPs | Skills | Temperature | |-------|-------|------|--------|-------------| | councillor | openai/gpt-5.4-mini | none | none | 0.2 |

Note: Per-councillor model overrides in the council config (presets.<name>.<councillor>.model) take precedence over the agent-level default.

Architecture Diagram

┌─────────────────────────────────────────────────────────┐
│                    Plugin Entry                          │
│                    (src/index.ts)                        │
│                                                         │
│  config.council?                                        │
│    ├── CouncilManager (session orchestration)           │
│    ├── council_session tool (agent-gated)               │
│    ├── SubagentDepthTracker (recursion guard)           │
│    │                                                     │
│    └── Agent Sessions                                    │
│        └── councillor (read-only, 🔍)                   │
│            └── deny all + allow: read, glob, grep,      │
│                lsp, list, codesearch                     │
│                                                         │
│  Agent Registration                                     │
│    ├── council: mode "all" (user + orchestrator)        │
│    └── councillor: mode "subagent", hidden              │
└─────────────────────────────────────────────────────────┘

council.md 15 KB

Permalink History Raw

Council Agent Guide

Table of Contents

Overview

Key Benefits

How It Works

Quick Setup

Step 1: Add Council Configuration

Step 2: Use the Council Agent

Configuration

Council Settings

Councillor Configuration

Constraints

Preset Examples

1-Councillor: Second Opinion

2-Councillor: Compare & Contrast

3-Councillor: Balanced Council

N-Councillor: Full Review Board

Multiple Presets

Role Prompts

Example: Specialised Review Board

Usage

Direct Invocation (User)

Orchestrator Delegation

Reading the Output

Timeouts & Error Handling

Timeout Behaviour

Graceful Degradation

Empty Response Detection

Troubleshooting

Council Not Available

All Councillors Timing Out

Preset Not Found

Subagent Depth Exceeded

Advanced

Model Selection Strategy

Cost Considerations

Council Agent Mode

Customising Councillor Agents

Architecture Diagram

council.md 15 KB Permalink History Raw

Council Agent Guide

Table of Contents

Overview

Key Benefits

How It Works

Quick Setup

Step 1: Add Council Configuration

Step 2: Use the Council Agent

Configuration

Council Settings

Councillor Configuration

Constraints

Preset Examples

1-Councillor: Second Opinion

2-Councillor: Compare & Contrast

3-Councillor: Balanced Council

N-Councillor: Full Review Board

Multiple Presets

Role Prompts

Example: Specialised Review Board

Usage

Direct Invocation (User)

Orchestrator Delegation

Reading the Output

Timeouts & Error Handling

Timeout Behaviour

Graceful Degradation

Empty Response Detection

Troubleshooting

Council Not Available

All Councillors Timing Out

Preset Not Found

Subagent Depth Exceeded

Advanced

Model Selection Strategy

Cost Considerations

Council Agent Mode

Customising Councillor Agents

Architecture Diagram

council.md 15 KB

Permalink History Raw