Human-Machine Brainstorm (人机风暴)
This skill should be used when the user asks to "人机风暴", "Human-Machine Brainstorm", "human storm", "ccb brainstorm", "需求对齐调度", "spec convergence", or wants a CCB-based multi-model requirement alignment loop with Codex as the dispatcher.
Best use case
Human-Machine Brainstorm (人机风暴) is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
This skill should be used when the user asks to "人机风暴", "Human-Machine Brainstorm", "human storm", "ccb brainstorm", "需求对齐调度", "spec convergence", or wants a CCB-based multi-model requirement alignment loop with Codex as the dispatcher.
Teams using Human-Machine Brainstorm (人机风暴) should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/human-machine-brainstorm/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Human-Machine Brainstorm (人机风暴) Compares
| Feature / Agent | Human-Machine Brainstorm (人机风暴) | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
This skill should be used when the user asks to "人机风暴", "Human-Machine Brainstorm", "human storm", "ccb brainstorm", "需求对齐调度", "spec convergence", or wants a CCB-based multi-model requirement alignment loop with Codex as the dispatcher.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Human-Machine Brainstorm (HMB) — CCB Dispatcher Loop ## Purpose Run a repeatable multi-model requirement alignment loop in **CCB** where: - **Codex** acts as the *dispatcher* (facilitator + router). - **Claude Code** acts as the *scribe* (single source of truth spec author). - **OpenCode (Gemini)** acts as the *divergent thinker* (alternatives + ASCII prototypes). Keep every round auditable by exporting per-provider context into `./.ccb/history/` and keeping the canonical spec in `./.ccb/spec/`. ## Hard Rules - Treat `./.ccb/spec/overview.md` as the **single source of truth**. Only Claude Code edits it. - Never assume panes “share context”. Always broadcast updates explicitly. - Enforce question IDs in this format: - Claude: `C-Q01`, `C-Q02`, ... - OpenCode: `O-Q01`, `O-Q02`, ... - Accept user answers only in ID-addressed form (so routing is deterministic). ## Quick Start (zero-friction, recommended) This workflow is optimized for a **2×Codex** setup: - **Cmd pane** runs a dedicated **Codex Chair** (dispatcher). - The normal **Codex provider pane** participates as a reviewer/solver (not just idle). 1) Create (or choose) a topic directory (recommended location: `$HOME/ccb-startups/...`). - Optional helper: `bash $HOME/.codex/skills/human-machine-brainstorm/scripts/hmb-init.sh "<topic-slug>"` 2) Start CCB. - If CCB global config enables the chair cmd pane, just run: `ccb` - Otherwise: `ccb claude codex opencode cmd` (fallback) 3) Talk only to the **Codex Chair** (cmd pane). - Paste the raw requirement. - The chair broadcasts to `claude`, `opencode`, and participant `codex` via `ask`. - Use the round prompt template in `references/round_prompt_template.md` if needed. ## Round Loop (R1/R2/R3...) ### Step A — Broadcast (dispatcher = Codex Chair) Send the same “Round prompt” to: - `ask claude "<ROUND PROMPT>"` - `ask opencode "<ROUND PROMPT>"` - `ask codex "<ROUND PROMPT>"` (participant Codex pane) Require them to respond with: - 10–20 numbered questions using `C-Q##` / `O-Q##` / `P-Q##` - 1 ASCII diagram (flow/state/component) - 1 short “current assumptions” list ### Step B — Collect Answers (human) Ask the human to answer in this format: - `C-Q01: ...` - `C-Q02: ...` - `O-Q01: ...` - `P-Q01: ...` Optionally allow a shared block: - `SHARED: ...` (facts that apply to both) ### Step C — Route Answers (dispatcher = Codex) Send Claude only `C-*` + `SHARED`. Send OpenCode only `O-*` + `SHARED`. Send participant Codex only `P-*` + `SHARED`. ### Step D — Export Evidence (end of round) From the `cmd` pane (or any shell pane) run: - `./.ccb/bin/round-save.sh 20` This writes: - `./.ccb/history/claude-<timestamp>.md` - `./.ccb/history/codex-<timestamp>.md` - `./.ccb/history/opencode-<timestamp>.md` ### Step E — Update Spec (scribe = Claude Code) Ask Claude to update: - `./.ccb/spec/overview.md` (bump version vN) - `./.ccb/spec/open_questions.md` (close answered questions) - `./.ccb/spec/decisions.md` (record non-reversible decisions) - `./.ccb/spec/changelog.md` (vN → vN+1 diff) Then re-run another round until all reviewers say “no blocking issues”. ## Final Handoff to GPT-5.2 (new session) Provide a clean handoff pack: - `./.ccb/spec/overview.md` - `./.ccb/spec/decisions.md` - `./.ccb/spec/open_questions.md` (should be empty or non-blocking) - `./.ccb/spec/changelog.md` Instruct GPT-5.2 to: - Treat the spec as authoritative - Output an executable plan first - Use multi-agent decomposition for implementation/testing/review
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