# Collab Deliberation > Structure multi-agent brainstorming and deliberation (options, tradeoffs, decision framing) without drifting into implementation. Use when this capability is needed. - Skill: `tomevault-io/collab-deliberation` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/collab-deliberation` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/collab-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/collab-deliberation --- # Collab Deliberation Use this skill when the user asks for brainstorming, tradeoffs, option comparison, or decision support before implementation. This skill is for ideas and decisions, not coding. ## Terminology + feature gate (required) - In this skill, "collab" means multi-agent tool usage (`spawn_agent` / `wait` / `close_agent`). - Codex CLI feature gating is `features.multi_agent=true`; treat `collab` as legacy naming in some env/artifact keys. - For symbolic orchestration, existing key names remain `RLM_SYMBOLIC_COLLAB` and `manifest.collab_tool_calls`. ## Deliberation Default v1 (required) - Keep MCP as the lead control plane. Use collab/delegated subagents to generate and challenge options. - Run full deliberation when any hard-stop trigger is true: - Irreversible/destructive change with unclear rollback. - Auth/secrets/PII boundary touched. - Direct production customer/financial/legal impact. - Conflicting intent on high-impact work. - Otherwise compute a risk score (`0..2` each): reversibility, external impact, security/privacy boundary, blast radius, requirement clarity, verification strength, time pressure. - Run full deliberation when score `>=7` or two or more criteria score `2`. - Use these time budgets for auto-deliberation: | Class | Horizon | Soft cap | Hard cap | | --- | --- | --- | --- | | `T0` | `<=15m` | `5s` | `12s` | | `T1` | `15m..2h` | `20s` | `45s` | | `T2` | `2h..8h` | `60s` | `120s` | | `T3` | `>8h` | `120s` | `300s` | - On soft cap: stop branching and execute the best current plan. - On hard cap: disable auto-deliberation for that stage and continue execution. ## Auto-trigger cadence (required) - Run deliberation at task bootstrap for non-trivial work. - Re-run deliberation after each meaningful chunk (default: behavior change or about 2+ files touched). - Re-run deliberation when external feedback lands (PR review, bot findings, CI failures). - Re-run deliberation when ambiguity/risk increases mid-flight (new constraints, conflicting evidence, high-signal `P1` or any `P0` finding). - Re-run deliberation at least every 45 minutes during active implementation. - If orchestration uses symbolic RLM, keep runtime auto-deliberation enabled: - `RLM_SYMBOLIC_DELIBERATION=1` (default) - `RLM_SYMBOLIC_DELIBERATION_INTERVAL` (default `2`) - `RLM_SYMBOLIC_DELIBERATION_MAX_RUNS` (default `12`) - `RLM_SYMBOLIC_DELIBERATION_MAX_SUMMARY_BYTES` (default `2048`) - `RLM_SYMBOLIC_DELIBERATION_INCLUDE_IN_PLANNER=1` (default) ## Workflow (required) 1) Frame the decision. - Write a one-sentence decision statement. - Capture goals, constraints, non-goals, and success criteria. - List assumptions and label each `confirmed` or `unconfirmed`. 2) Close critical context gaps. - Ask up to 3 targeted questions only if answers could change the recommendation. - If delegation is available, prefer a subagent for context gathering before asking the user. - If collab spawning fails (for example `agent thread limit reached`), proceed solo and explicitly note the limitation; do not block on spawning. 3) Generate distinct options. - Produce 3-5 materially different options. - For each option include approach, prerequisites, blast radius, and time/risk profile. 4) Evaluate and stress test. - Use a tailored rubric (3-5 dimensions relevant to the decision). - For each option include one likely failure mode and one mitigation. 5) Recommend or defer explicitly. - Recommend one option when confidence is sufficient. - If uncertainty is high, defer with explicit decision gates. 6) Close with decision-driving questions. - List 1-3 prioritized open questions that could change the recommendation. - End with one concrete next step that improves decision quality without implementation. ## Output contract - `Decision`: one sentence. - `Context`: goals, constraints, non-goals, assumptions. - `Options`: 3-5 concise options. - `Tradeoffs`: rubric and comparative rationale. - `Recommendation`: chosen option or explicit defer with decision gates. - `Open questions`: prioritized items only. - `Next step`: single highest-leverage action. - `Confidence`: `high` | `medium` | `low`. ## Guardrails - Separate facts from assumptions. - Do not implement or modify code unless explicitly asked. - Do not present uncertainty as certainty. - Keep outputs concise and action-oriented. - If collab subagents are used, close lifecycle loops per id (`spawn_agent` -> `wait` -> `close_agent`) before finishing. - If collab subagents are used, always set explicit `agent_type` (omission defaults to `default`) and prefix spawned prompts with `[agent_type:]`. - If you cannot close collab agents (missing ids) and spawn keeps failing, restart the session and re-run deliberation; keep work moving by doing solo deliberation meanwhile. ## Related skills - `collab-subagents-first`: for implementation-phase stream ownership and lifecycle after deliberation. - `delegation-usage`: for delegation MCP orchestration when decisions require delegated execution. - `docs-first`: for turning chosen option into PRD/TECH_SPEC/ACTION_PLAN before edits. - `agent-first-adoption-steering`: for non-coercive option framing and advanced-feature nudges. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/kbediako) — claim your Tome and manage your conversions.