# Deliberation > Multi-agent architectural deliberation protocol for heterogeneous model debate on complex design problems Use when this capability is needed. - Skill: `tomevault-io/deliberation` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/deliberation` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/deliberation/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/deliberation --- # Multi-Agent Deliberation Protocol This skill defines the protocol for heterogeneous model deliberation — using multiple LLMs (Claude, Gemini, GPT) to debate complex architectural and design problems via GitHub Discussions. ## When to Use Deliberation Deliberation is most valuable for: - **Architecturally complex problems** with multiple viable approaches - **Trade-off decisions** where different priorities lead to different conclusions - **Ambiguous requirements** that benefit from multiple interpretations - **Novel patterns** where training data divergence creates useful diversity Deliberation is **not** valuable for: - Clear-cut factual questions (use single-model lookup) - Simple implementation decisions (use primary agent) - Time-sensitive decisions (deliberation takes multiple rounds) ## The Deliberation Medium: GitHub Discussions GitHub Discussions serve as the persistent, auditable deliberation space. Benefits: - **Permanent record** — "what were we thinking when we designed this?" - **Team visibility** — human collaborators can observe or join - **Natural context** — each agent re-reads the full history when engaging - **Semantic framing** — "discussion" primes collaborative analysis, not solution-building Use the **Ideas** category for architectural deliberations. ## Agent Roles ### Deliberator Agents (3) - **Claude Opus 4.6** — max adaptive thinking, strong at nuanced reasoning - **Gemini 3 Pro** — deep think mode, highest agentic reliability - **GPT-5.2** — xhigh reasoning effort, strong general reasoning Each deliberator: - Has **read-only codebase access** (no write/edit tools) - Can **post discussion comments** via GitHub API - Can **research externally** (web search, doc lookup) - **Operates independently** — no shared context between rounds ### Orchestrator (Primary Agent) - **Posts the initial problem** statement with relevant prior decisions - **Triggers deliberation rounds** (spawning all 3 deliberators in parallel) - **Synthesizes final decision** and stores it in mem0 ## Rules for Deliberating Agents ### Identity Always identify yourself in **every comment** using the format: ``` **[Model Name agent]** — Your comment begins here... ``` Examples: `**[Claude Opus 4.6 agent]**`, `**[Gemini 3 Pro agent]**`, `**[GPT-5.2 agent]**` ### Investigation Protocol 1. **Read the full discussion** including all prior comments before responding 2. **Investigate the codebase independently** — read relevant source files, trace data flows, check existing implementations 3. **Research externally** when the problem involves libraries, APIs, or patterns you're uncertain about 4. **Form your position** based on evidence, not prior comments ### Critical Engagement - **Challenge assumptions** — if a prior comment makes claims without evidence, ask for it - **Disagree constructively** — state what you disagree with and why, then propose an alternative - **Identify blind spots** — look for what others missed (edge cases, performance implications, maintenance burden) - **Recognize good ideas** — if a proposal is sound, say so (consensus is valuable when earned) ### Evidence Requirements - **Cite specific files and line numbers** when referencing code (use `file:line` format) - **Link to documentation** when referencing library/API behavior - **Quote relevant code** when discussing implementation details - **Quantify trade-offs** when possible (performance, complexity, maintainability) ### Boundaries - **DO NOT implement anything** — no code changes, no PRs, no file creation - **DO NOT take the lead** — you are one voice among equals - **DO NOT summarize** — that's the orchestrator's job - **DO NOT repeat yourself** — if you've made your point in a prior round, add new insight or signal agreement ## Comment Structure Template Structure your comments for clarity: ```markdown **[Model Name agent]** ### Investigation [What I discovered in the codebase/research] ### Position [My view on the problem and proposed solutions] ### Concerns [Specific issues I see with current proposals, with evidence] ### Suggestions [Concrete alternatives or refinements, with rationale] ``` This structure is a guideline, not a requirement. Adapt to the discussion flow. ## Round Dynamics **Round 1:** All agents investigate independently and post initial positions **Round 2+:** Agents respond to each other's proposals, refining or challenging **Convergence signals:** - Agents agree on key trade-offs even if they differ on final choice - New rounds produce no new insights (agents repeat prior points) - A clear decision emerges with documented rationale **Divergence is okay** — if agents fundamentally disagree, that signals the decision needs human judgment or more information. ## Memory Integration **Before deliberation starts:** - Orchestrator searches mem0 for related architectural decisions - Relevant prior decisions are included in the discussion body - Agents see this context and can build on or challenge prior decisions **After deliberation concludes:** - Orchestrator stores the decision in mem0 with discussion link - Future deliberations can discover and reference this decision ## Anti-Patterns Avoid these common failure modes: ❌ **Rubber-stamping** — agreeing without independent investigation ❌ **Scope creep** — solving adjacent problems not in the discussion scope ❌ **Premature implementation** — proposing code before architecture is clear ❌ **Credential arguments** — "I'm better at X" (evidence speaks for itself) ❌ **Repetition** — restating your position without new evidence ❌ **Bikeshedding** — debating trivial details while avoiding hard trade-offs ## Related Patterns - **parallel-agents** (Simon Willison) — multiple agents on separate tasks (not deliberation) - **model-routing** — task-appropriate model selection (not multi-model debate) - **Multi-Agent Debate (MAD)** research — academic foundation for this pattern - **MALLM Framework** — research framework for configurable multi-agent LLM debate ## References - Academic research validates heterogeneous (different model) debate for complex/ambiguous problems - GitHub Discussions provide natural semantic framing vs Issues (which bias toward implementation) - Fresh context each round (no persistence) reduces confirmation bias and enables new insights --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/pvliesdonk) — claim your Tome and manage your conversions.