Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
日本語の概要は準備中です。原文の説明を表示しています。
Interactive 9-step prompt crafting and delegation protocol for autonomous multi-agent teams. Enforces objective verification, integrity modes, and acceptance criteria across Antigravity, Claude Code, Cursor, OpenCode, Codex, and Roo Code.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
A structured workflow to turn high-level user ideas into robust, objectively verifiable multi-agent project specifications and delegate them cleanly to execution swarms.
Two-phase workflow:
Action: call the Workflow tool with scriptPath set to
$HOME/.claude/workflows/teamwork-dispatch.mjs — resolve $HOME yourself rather
than hardcoding a username — and args set to whatever the user said after the
command, passed through verbatim. If they said nothing, pass no args; step 1
asks.
Use scriptPath, not name. By-name lookup for a custom workflow script has been
observed to fail with Workflow "..." not found even when the file exists and its
meta.name matches.
Then wait for the call to finish and relay its result — the draft path, the validation outcome, and any issues it reports. Do not summarise or reinterpret it.
Do NOT walk through the nine steps yourself in response to this skill. The
protocol below is the specification the script implements; it is not a set of
instructions to follow inline. This repo has already paid for that mistake once,
recorded in skills/basic/startcycle-graph/SKILL.md: an earlier version embedded
its pipeline in prose, the model followed it "in spirit" instead of invoking the
script, and the entire graph — subagents, state, review, quality gate — silently
never ran. A 9-step protocol with integrity modes and acceptance criteria is
exactly the shape of thing that gets approximated.
If the Workflow tool is unavailable (some harnesses have none; Claude Code can
have Dynamic Workflows switched off in /config), then run the protocol below
manually, in order, one step at a time.
| Claude Code | The script above. Deterministic: it runs or it doesn't. |
| Codex · Cursor · OpenCode · Roo · Antigravity | The prose protocol below, interpreted by that harness's model. |
The .mjs script depends on Claude Code's Dynamic Workflows runtime — the ambient
agent() global and the Workflow tool. No other harness exposes an equivalent
today, so the prose is not a fallback there, it is the implementation. Both are
kept in this one file deliberately: two files would drift, and the drift would be
invisible until someone on the other harness got different behaviour.
This is not Antigravity's /teamwork-preview. That command is compiled into
the agy binary, with its own conductor/orchestrator/auditor agent types, and is
maintained by Google. This is an independent implementation of the same idea on a
different runtime. It will behave differently, and it does not claim otherwise.
| # | Principle | Rule |
|---|---|---|
| 1 | Specify What, Not How | Define requirements and acceptance criteria. Never prescribe implementation details (file structure, algorithms, libraries) unless the user explicitly mandates them. |
| 2 | Objective Verification | Every requirement needs an independent verification mechanism. Programmatic verification (tests, assertion scripts, CLI benchmarks) is preferred; explicit agent-as-judge rubrics are accepted when programmatic testing is impossible. |
| 3 | Acceptance Criteria = Guardrails | Acceptance criteria serve as the quality bar to prevent premature self-certification of incomplete or broken work. |
| 4 | Minimal Requirements | Only specify what the user explicitly cares about. Give the agent team maximal solution space. |
Maintain a prompt draft artifact (prompt_draft.md) throughout the interaction. It provides real-time visibility to the user and tracks step progression.
# Teamwork Project Prompt — Draft
> Status: Step 1 — Eliciting project idea
> Goal: Craft prompt → get user approval → delegate
> Requested team: [none — routes automatically from description]
[Project description — 1-2 sentences]
Working directory: [TBD]
Integrity mode: [development | demo | benchmark]
## Requirements
### R1. [TBD]
### R2. [TBD]
## Acceptance Criteria
### [Category]
- [ ] [Objective condition checkable without subjective bias]
---
*Next: when approved → delegate via execution protocol*
prompt_draft.md and set status to Step 2.Clarify operational boundaries:
integrity_mode: developmentintegrity_mode: demointegrity_mode: benchmarkWhy this matters: Verification is a forcing function. Its job is to create an objective test target that forces a genuine build → test → debug loop and prevents premature self-certification.
## Verification Resources section.- [ ]).~/teamwork_projects/{project_name} or a relative path in the current repo).Working directory: <path> at top of prompt draft.Assemble the final structured prompt:
[1-2 sentence project description]
Working directory: <path>
Integrity mode: [development | demo | benchmark]
[Optional: Team scaling directive]
## Requirements
### R1. [Primary Deliverable]
[What it does, not how to build it]
### R2. [Secondary Deliverable]
[What it does, not how to build it]
## Acceptance Criteria
### [Category]
- [ ] [Objective condition checkable without subjective bias]
Pre-flight Checklist:
Seek explicit approval from the user before triggering execution.
Once approved by the user:
Before delegating, start the live map (Trigger B) so the user can follow the team: aos-trail --ensure (add --plan <plan-file> if the plan path is explicit) (safe to run twice: it reuses a map already running for this repo). Put the live-map link in your reply (the autostart hook also adds it as context when active). Inside AO (env var AO_BROWSER_CAPABILITY set) also run ao preview <url>. See the agenttrail skill.
If running in Google Antigravity with native subagent support:
invoke_subagent:
TypeName: teamwork_previewRole: Teamwork CoordinatorPrompt: Full prompt content from prompt_draft.mdLaunched./startcycle-graph / subagents.opencode run or Codex runner.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
日本語の概要は準備中です。原文の説明を表示しています。
Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
日本語の概要は準備中です。原文の説明を表示しています。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
日本語の概要は準備中です。原文の説明を表示しています。
Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
日本語の概要は準備中です。原文の説明を表示しています。
agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
日本語の概要は準備中です。原文の説明を表示しています。