LLM Council Skill

Multi-model council: parallel drafts → adversarial critique → validated synthesis.

Prerequisite: This skill requires the the-llm-council Python package to be installed. The skill provides IDE integration but the actual council runs via the installed CLI. If you see command not found: council, run pip install the-llm-council first.

Setup

1. Install

pip install the-llm-council>=0.2.0

# With specific provider SDKs
pip install the-llm-council[anthropic,openai,google]

2. Configure API Keys

Provider	Environment Variable	Notes
OpenRouter	OPENROUTER_API_KEY	Recommended - single key for all models
OpenAI	OPENAI_API_KEY	Direct GPT access
Anthropic	ANTHROPIC_API_KEY	Direct Claude access
Google	GOOGLE_API_KEY or GEMINI_API_KEY	Direct Gemini access

# Minimum setup (OpenRouter)
export OPENROUTER_API_KEY="your-key"

3. Verify

council doctor

Usage

council run <subagent> "<task>" [options]

CLI Options

Option	Description
--json	Output structured JSON
--health-check	Run preflight provider check
--verbose, -v	Verbose output
--models, -m	Comma-separated model IDs
--providers, -p	Comma-separated provider list
--timeout, -t	Timeout in seconds (default: 120)
--max-retries	Max retry attempts (default: 3)
--no-artifacts	Disable artifact storage (faster)
--no-degradation	Disable graceful degradation (strict mode)

Other Commands

council doctor    # Check provider health
council config    # Show current configuration

Subagents

Subagent	Use For	Details
implementer	Feature code, bug fixes	See subagents/implementer.md
reviewer	Code review, security audit	See subagents/reviewer.md
architect	System design, APIs	See subagents/architect.md
researcher	Technical research	See subagents/researcher.md
planner	Roadmaps, execution plans	See subagents/planner.md
assessor	Build vs buy decisions	See subagents/assessor.md
red-team	Security threat analysis	See subagents/red-team.md
test-designer	Test suite design	See subagents/test-designer.md
shipper	Release notes	See subagents/shipper.md
router	Task classification	See subagents/router.md

Multi-Model Configuration

Run multiple models in parallel for adversarial debate:

# Via CLI flag
council run architect "Design caching layer" \
  --models "anthropic/claude-3.5-sonnet,openai/gpt-4o,google/gemini-pro"

# Via environment variable
export COUNCIL_MODELS="anthropic/claude-3.5-sonnet,openai/gpt-4o,google/gemini-pro"

Model Pack Overrides

Fine-tune which models handle specific task types:

export COUNCIL_MODEL_FAST="anthropic/claude-3-haiku"      # Quick tasks
export COUNCIL_MODEL_REASONING="anthropic/claude-3-opus"  # Deep analysis
export COUNCIL_MODEL_CODE="openai/gpt-4o"                 # Code generation
export COUNCIL_MODEL_CRITIC="anthropic/claude-3.5-sonnet" # Adversarial critique

Config File

Optional YAML configuration:

# ~/.config/llm-council/config.yaml
providers:
  - name: openrouter
    api_key: ${OPENROUTER_API_KEY}
    default_model: anthropic/claude-3-opus

defaults:
  timeout: 120
  max_retries: 3
  summary_tier: actions

Python API

from llm_council import Council

council = Council(providers=["openrouter"])
result = await council.run(
    task="Build a login page with OAuth",
    subagent="implementer"
)
print(result.output)

When to Use

Use council for:

• Feature implementation requiring production quality
• Code review with security analysis (CWE IDs)
• Architecture design decisions
• Technical research informing decisions
• Build vs buy assessments
• Security threat modeling

Skip council for:

• Quick file lookups
• Single-line fixes
• Simple questions

Examples

# Feature implementation
council run implementer "Add pagination to users API" --json

# Code review
council run reviewer "Review the authentication changes" --json

# Multi-model architecture design
council run architect "Design caching layer" \
  --models "anthropic/claude-3.5-sonnet,openai/gpt-4o" --json

# Security threat model
council run red-team "Analyze auth system vulnerabilities" --json

Security Notes

• API Keys: Never embed secrets in task descriptions or skill files. Use environment variables.
• Data Sensitivity: Avoid sending files containing secrets (.env, credentials) to the council. Context is sent to external LLM providers.
• Skill Integrity: Treat SKILL.md and subagents/*.md as configuration code. Keep under version control.

Troubleshooting

# Check all providers
council doctor

# Verbose output for debugging
council run implementer "task" --verbose

# Faster runs (skip artifact storage)
council run implementer "task" --no-artifacts