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Agent Skill · 研究检索

openclaw-projects(OpenClaw projects 搜索)

openclaw-projects 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

openclaw-projects 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 35,426。

总安装 2,088周安装 87GitHub Stars 公开资料未说明下载 696核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-projects(OpenClaw projects 搜索)
来源仓库:https://github.com/encryptshawn/openclaw-projects
安装命令:
openclaw skills install openclaw-projects
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-projects

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

OpenClaw projects 用于在飞书中协调多代理团队协作。适合在 OpenClaw 中为软件开发、营销等内容团队搭建项目时使用。支持 PM、开发人员、审阅人员和测试人员子代理分工。通过 clawhub 安装,结合来源仓库和 README 可进一步了解具体用法。

安装前需确认权限范围、维护状态,以及是否涉及联网、命令执行或文件读写。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install openclaw-projects;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openclaw-projects 怎么安装?

在终端执行 openclaw skills install openclaw-projects。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-projects 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openclaw-projects 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

openclaw-projects 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openclaw-projects 用的人多吗?

公开数据是累计安装 2,088 次,近一周安装 87 次,下载 696 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openclaw-projects 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openclaw-projects

OpenClaw projects 搜索 · 本页

2,088—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
openclaw_projects
description
>

OpenClaw Projects

This skill adds the concept of a Project to OpenClaw — a coordinated multi-agent team setup that lets one or more agents work together toward shared goals. Projects can be any team type: software development, marketing, real estate, content, sales, customer success, research, or anything else.

A Project is:

  • A folder at ~/.openclaw/projects/[project-id]/ containing the team rulebook, configuration, shared workspace, and inter-agent message queues
  • A defined workflow that takes work from intake through delivery
  • A wiring layer that connects multiple agents through OpenClaw's agent-to-agent communication
  • A coordination unit that uses one task manager (Asana or ClickUp) as the source of truth for task ownership and status

Multiple projects can coexist. Agents can participate in multiple projects.


Contents

Reference files (read when needed):

  • references/project-files.md — Full specification of every project folder file
  • references/workflow.md — Universal workflow phases, escalation rules, queue formats
  • references/interview-questions.md — Full interview question banks for Pass 1 and Pass 2
  • references/team-archetypes.md — Common team patterns to draw on for examples
  • references/templates.md — Parameterized templates for every file this skill generates (PROJECT.md, project.json, queue files, etc.) plus a placeholder reference table

What This Skill Does

  1. Interviews the user through a structured three-pass discovery process to understand the team
  2. Drafts a comprehensive team plan — AI-rewrites the user's answers into a complete operational plan, filling gaps and tightening loose answers
  3. Reviews the plan with the user for fine-tuning and approval before building
  4. Checks agent capabilities against the planned work and surfaces any concerns (e.g., a vision-required task assigned to an agent without a vision-capable model)
  5. Creates the project folder at ~/.openclaw/projects/[project-id]/ with all coordination files
  6. Updates each participating agent's workspace with project references in their AGENTS.md
  7. Updates OpenClaw config to enable agent-to-agent communication between project participants
  8. Walks through a smoke test to verify the project is operational

What This Skill Does NOT Do

  • Create agents — agents must already exist (use OpenClaw's agent creation flow first)
  • Choose models for agents — that's the user's decision, made when creating the agent
  • Hold credentials — the task manager dependency skill handles that
  • Make task manager API calls directly — delegated to the user's Asana or ClickUp skill

Prerequisites

Must be installed before running this skill:

  • openclaw-administrator (EncryptShawn) — used to update OpenClaw config and write workspace files

Must already exist in OpenClaw:

  • Each agent that will participate in the project
  • Each agent must have a model and fallback configured (this skill verifies but does not set models)

Must be installed on the agents that will use it:

  • A task manager dependency skill — either Asana or ClickUp — installed on every agent that needs to read/write tasks. The user is responsible for installing this and configuring its credential (PAT, API key, or token) in their secret management system.

Strongly recommended:

  • openclaw-recovery-manager (EncryptShawn) — provides config snapshots and rollback

If the user has not yet created their agents, stop and tell them:

"Before we build a project, you need to create the agents that will participate in it. Each agent should have its model and fallback configured, and you should install the task manager skill (Asana or ClickUp) on each agent that will read or write tasks. Once your agents exist, come back and we'll set up the project."

Heartbeat Model and Behavior Rules

These rules apply to every agent on every project created by this skill. They must be reflected in each agent's HEARTBEAT.md (written in Step 8).

Heartbeat model selection

Heartbeat runs must use the cheapest available model, not the agent's primary or fallback model. Primary models are expensive for what a heartbeat is — a near-stateless task-manager queue check.

Selection priority:

  1. If OpenRouter is configured on the agent → use openrouter/minimax/minimax-m2.7
  2. If OpenRouter is NOT configured → use the cheapest model defined in that agent's config. Identify this during Step 8 and record it explicitly in HEARTBEAT.md.

Heartbeat reasoning level

Heartbeat reasoning must be kept minimal. Do not add a reasoning config key to openclaw.json — that is not a supported field. Control it through the heartbeat prompt instead. Every HEARTBEAT.md must begin with:

/think:minimal

Heartbeat failure — fail cheap, never escalate

If a heartbeat fails (task manager unreachable, bad model config, tool error, anything), the agent must stop immediately and fail cheaply. It must NOT:

  • Retry using the primary model
  • Start a troubleshooting loop
  • Use sessions_send to message itself
  • Reason about what went wrong

The correct behavior: log the failure if logging is available, and stop. The next scheduled heartbeat will try again. Most heartbeat failures are config problems (bad model path, missing credential, task manager connection error) that the operator must fix — not something the agent can resolve by spending primary model credits every 30 minutes.


Credential and Security Model

This skill never reads, stores, requests, or transmits credential values.

This skill collects only the *names* of env vars (e.g., PROJ_ASANA_PAT) — never their values. The dependency skills the user installed (Asana skill, ClickUp skill, any other domain-specific skill) hold and use credentials. This skill passes credential env var *names* to those skills so they know which value to pull from the agent runtime environment.

Credentials must be stored in the user's secret management system (Kubernetes ConfigMap/Secret, .env file, or equivalent) before this skill runs.


Step 0 — Safety First

  1. Check if openclaw-recovery-manager is installed.

- Yes: Take a snapshot. Label: pre-project-setup-[project-id]-[date] - No: Ask: > "I recommend installing openclaw-recovery-manager (EncryptShawn on ClawHub) before we proceed — it lets us roll back if anything goes wrong. Want to install it first, or proceed without it?"


Step 1 — Discover Existing Setup

Before interviewing, gather context using openclaw-administrator:

  1. List existing agents and their configured models
  2. List existing projects in ~/.openclaw/projects/ (if any)
  3. Check which task manager skills are installed on each agent (Asana, ClickUp, or both)

This context informs the interview — for example, if the user has 5 agents already, you can show them the list to pick from rather than asking them to type names.

If ~/.openclaw/projects/ doesn't exist yet, this is the first project. Note this — the agents won't have any "Active Projects" section in their AGENTS.md yet.


Step 2 — Pass 1: Team Identity Interview

Read references/interview-questions.md for the full question bank. The goal of Pass 1 is to understand who is on this team and what they each do.

Ask the user the questions in order. After each block, briefly summarize what they said back to confirm before moving on.

Core Pass 1 questions:

Pass 1 — Team Identity

1. What is this project for? (one-sentence purpose, e.g., "Build and maintain
   the EZBI analytics platform" or "Generate marketing content for client
   campaigns")

2. What kind of team is this?
   - Software development
   - Marketing / creative
   - Real estate
   - Content / editorial
   - Sales / outreach
   - Customer success / support
   - Operations
   - Research
   - Other (describe it briefly)

3. What should this project be called?
   - Display name (e.g., "EZBI Platform")
   - Project ID (lowercase, hyphens or underscores, used in folder names — e.g., "ezbi")

4. Which agents will be on this team? (You can pick from your existing agents.)
   For each agent, what is their role on this project?
   (One agent might be "Project Manager" on this project and "Researcher" on
   another — the role is per-project.)

5. Which agent is client-facing? (Equivalent of a PM — receives requirements,
   talks to clients, owns the intake. There should be exactly one.)

6. Which agent validates feasibility? (Domain expert who reviews whether the
   work is doable before committing — e.g., engineer for dev work, strategist
   for marketing, broker for real estate.)

7. Which agent does quality review? (Reviews completed work before delivery
   to the client — e.g., QA for dev, creative director for marketing.)

8. Is there a human operator? (Final authority for merges, unresolvable
   escalations, client engagement when agents can't reach the client.)
   Yes / No — if yes, what's their alias? (e.g., "operator")

9. Are there any other roles? (Specialized contributors — designers,
   researchers, copywriters, etc.)

Record all answers. Confirm back before moving on.


Step 3 — Pass 2: Work Structure Interview

The goal of Pass 2 is to understand how the team works together day-to-day.

Pass 2 — Work Structure

1. Task manager — which one?
   - Asana
   - ClickUp
   (You should already have the corresponding dependency skill installed on
   your agents. Confirm which one.)

2. What are the stages a piece of work goes through? (These become the
   task manager columns. Default suggestion based on team type — confirm
   or customize.)

3. What is the shared working medium?
   - Where does this team actually produce deliverables?
   - Examples: a git repo (devs), a Google Drive folder (marketing),
     a Notion workspace (content), a CRM system (sales/real estate),
     a shared file folder, or none / not applicable
   - If a git repo: SSH URL(s) for cloning
   - If a folder/workspace: path or link
   - If a CRM/external system: how do agents access it?

4. What does "done" look like before work goes to client review?
   - Devs: PR opened, all tests pass, QA reviewed
   - Marketing: copy approved by creative director, brand guidelines met
   - Real estate: listing complete, photos verified, pricing confirmed
   - Whatever fits this team

5. How does the team handle requirements?
   - One sprint at a time (recommended): one agreed scope completed before
     next is accepted
   - Continuous flow: new requirements can come in any time
   (One-sprint-at-a-time is strongly recommended for teams that need
   focused execution. Continuous flow is appropriate for teams handling
   high-volume small tasks.)

6. Escalation thresholds:
   - How long should an agent be stuck on the same problem before stopping
     and surfacing to a human? (Default: 24 hours of active work)
   - How many times can an agent re-escalate the same issue before stopping?
     (Default: 2 escalations to the feasibility-reviewer)
   - How long with no client response before involving the operator?
     (Default: 48 hours)

7. Does this team produce or consume any visual / media assets?
   - Yes: describe (mockups, photos, video, audio, diagrams)
   - No
   (If yes: assets will be stored as task-manager attachments primarily,
   with a fallback location in the project workspace.)

8. Anything else specific to this team that other agents would need to know?
   (Free-form — house style, client communication preferences, specific
   tools/platforms, compliance requirements, etc.)

Record all answers. Confirm back before moving on.


Step 4 — Pass 3: AI-Drafted Team Plan for Review

This is the most important step. Take everything from Pass 1 and Pass 2 and produce a comprehensive, operational team plan — not a transcription of the user's answers, but an AI-rewritten, gap-filled version that any agent could read and immediately know how to operate.

The plan must include:

  • Team identity: project name, ID, purpose, kind
  • Roster: every agent, their role on this project, what they own, what they do not own
  • Task manager configuration: which one, the column structure with each column's meaning
  • Shared working medium: what it is, how agents access it, conventions for using it
  • Workflow phases: every phase from intake through close, with who owns each, what triggers transitions
  • Escalation rules: thresholds, who escalates to whom, when work stops
  • Communication protocol: queue files between agents, who reads which queue
  • Visual/media handling: if applicable, how assets are stored and referenced
  • What "done" means at each phase
  • Anything specific the user mentioned

Write this plan in clear, complete prose. Fill gaps the user didn't address explicitly — for example, if the user said "we have a designer" but didn't say what triggers the designer's involvement, infer reasonable defaults based on team type and write them in. Mark inferred items clearly so the user can correct them.

Present the plan to the user:

I've turned your answers into a full team plan. Read through it carefully —
this is what will go into PROJECT.md, which is what every agent on the team
reads to understand how to operate.

Items I inferred (not directly asked) are marked with [INFERRED].
Anything that doesn't match what you want, tell me and I'll revise.

[FULL PLAN HERE]

Does this match what you want? Anything to change before we build?

Do not move to Step 5 until the user explicitly approves the plan. This is the gate that prevents vague PROJECT.md files. Iterate as many times as needed.


Step 5 — Capability Check

Before building, look at the approved plan and check whether the assigned agents can actually do what the plan asks of them.

Using openclaw-administrator, fetch each agent's configured model. Cross-reference against the plan:

  • Vision required? If the plan involves the agent reviewing mockups, photos, screenshots, or any visual asset, check that the agent's model has vision capability. If not, flag it.
  • Long context required? If the agent needs to read large documents (long specs, full codebases, large research corpora), check the model's context window. If under 200k and the work seems heavy, flag it.
  • Code-heavy work? If the agent is doing software development, check the model has reasonable coding benchmarks. (If the user picked something obviously weak, mention it.)
  • Heartbeat model available? Check whether the agent has OpenRouter configured (for minimax-m2.7) or at least one cheap model available for heartbeat use. If the agent's only model is a high-cost primary and there's no OpenRouter or cheap fallback, flag it — heartbeat on a primary model every 30 minutes is a significant credit burn.

Output format:

Capability check on the assigned agents:

✅ [agent-id] (role: PM) — model [model-name]
   No concerns.

⚠️  [agent-id] (role: FE Designer) — model [model-name]
   Concern: This role will review visual mockups, but [model-name] does not
   support vision. Consider using a vision-capable model for tasks that
   involve images, or assigning that work to a different agent.

⚠️  [agent-id] (role: QA) — model [model-name]
   Concern: This model has a [X]% hallucination rate per public benchmarks,
   which is high for QA work that needs precise pass/fail judgment.
   This is advice — not a blocker.

These are advisory only. You can proceed as-is, change agent models in
your OpenClaw config, or reassign work to different agents.
Proceed? (yes / make changes first)

Wait for the user. If they want to change agent models, that's their job — point them at openclaw-administrator. This skill does not set models.


Step 6 — Task Manager Setup

Based on the user's choice in Pass 2:

If task manager board does NOT exist yet

Create the task manager board manually:

1. Log into [Asana / ClickUp]
2. Create a new project / space named: [project_display_name]
3. Set up the columns in this exact order:
   [column list from the approved plan]
4. Invite all agent accounts as members
5. Copy the project ID / GID from the board URL
6. Share the ID here when ready

Once the project ID is confirmed

Using the task manager dependency skill (via the client-facing agent, since they own task creation), add a project description / pinned note with:

Project: [project_display_name]
Project ID: [project-id]
Client-facing agent: [agent-id]
Feasibility reviewer: [agent-id]
QA: [agent-id]
Operator: [operator-alias or N/A]
Shared workspace: [path or description]
Task manager column meanings: [brief column legend]

Record the task manager project ID — it goes in project.json.


Step 7 — Create Project Folder Structure

This creates the entire project at ~/.openclaw/projects/[project-id]/. Read references/project-files.md for the full specification of each file.

Folder layout

~/.openclaw/projects/[project-id]/
├── PROJECT.md                    ← Team rulebook from the approved plan
├── project.json                  ← Machine-readable config
├── project-lock.json             ← Phase tracker (initialized to "idle")
├── STATE.md                      ← Human-readable status
├── SHARED_MEMORY.md              ← Cross-agent knowledge store
├── DECISIONS.md                  ← Append-only decision log
├── KNOWN_ISSUES.md               ← Accepted limitations / debt
├── RUNBOOK.md                    ← Project operating guide (stub initially)
├── workspace/
│   ├── [shared medium]           ← Repo, folder, files, depending on team
│   ├── [media-folder/]           ← Only if team uses visual/media assets
│   ├── SPEC-CURRENT.md           ← Current accepted spec / brief
│   └── DELIVERABLES_GUIDE.md     ← Feasibility-reviewer's task plan (was IMPLEMENTATION_GUIDE.md)
└── queues/
    ├── to-[client-facing-role].md
    ├── to-[feasibility-reviewer-role].md
    ├── to-[feasibility-reviewer-role]-feasibility.md
    ├── to-[qa-role].md
    ├── to-[operator].md          ← Only if operator was specified
    └── to-[other-role].md         ← One per other role on the team

Building each file

PROJECT.md — generate from the PROJECT.md template in references/templates.md, filling every placeholder with the approved plan content from Step 4. This is the single most important file — it must be complete and operational. Use the placeholder reference table at the bottom of references/templates.md to map each placeholder to its source.

project.json — generate from the project.json template in references/templates.md. Validate the result is valid JSON before writing. Fill in:

  • id and name from Pass 1
  • task_manager block — type (asana / clickup), project ID, columns
  • participants — every agent with their project role and OpenClaw workspace path
  • client_facing_role, feasibility_reviewer_role, qa_role, operator — pointers to the right roles
  • shared_workspace and shared_medium — type and path/URL
  • visual_assets block — only if the team uses media (Pass 2 #7)
  • queues — file paths for each role's queue
  • escalation_rules — values from Pass 2 #6

project-lock.json — initialize:

{
  "phase": "idle",
  "sprint_id": null,
  "sprint_opened": null,
  "waiting_on": null,
  "last_updated": "[today]",
  "last_updated_by": "operator",
  "context": "Project initialized. Ready to receive first work.",
  "blocked_tasks": []
}

STATE.md — initialize:

# [project_display_name] — Current State
**Phase:** Idle — Ready for first work
**Last updated:** [today] by operator

Queue files — initialize each one with header:

# Queue: to-[role]
# Format: [YYYY-MM-DD HH:MM] [FROM: agent-id] [TO: agent-id] [TASK: task-id or N/A]
# Append-only. Never delete entries. Mark processed with [READ].

SHARED_MEMORY.md, DECISIONS.md, KNOWN_ISSUES.md — each gets a header and an empty body.

RUNBOOK.md — generate a stub with section headers appropriate for the team type, plus a note:

This is a starting stub. The feasibility-reviewer should expand each section
as they learn the project. Devs / contributors read this before starting work.

Shared medium initialization:

  • Git repo: cd ~/.openclaw/projects/[project-id]/workspace && git clone [ssh-url] [repo-name]
  • Folder/Drive: create workspace/[folder-name]/ and add a LINKS.md file with the external URL if not local
  • CRM/external: skip — write a workspace/EXTERNAL_SYSTEM.md describing where work happens
  • None: skip

Media folder — only if Pass 2 #7 was yes:

mkdir -p ~/.openclaw/projects/[project-id]/workspace/[media-folder-name]

Step 8 — Update Agent Workspaces

For each participating agent, write two files: update their AGENTS.md with the project reference, and write their HEARTBEAT.md with direct queue lookup instructions.

AGENTS.md — append Active Projects entry

Append (or update) an Active Projects section in each agent's AGENTS.md:

## Active Projects
- **[project_display_name]** — I am the [role] on this project.
  - Full rules: ~/.openclaw/projects/[project-id]/PROJECT.md
  - My queue: ~/.openclaw/projects/[project-id]/queues/to-[my-role].md
  - Shared workspace: ~/.openclaw/projects/[project-id]/workspace/
  - Check my queue at the start of every session before doing anything else.
  - Check ~/.openclaw/projects/[project-id]/project-lock.json to know what
    phase we are in before acting.

If the agent is already on other projects, append — do not overwrite. The agent should see all their active projects.

HEARTBEAT.md — write per agent

Write (or update) HEARTBEAT.md for each agent. The heartbeat model is:

  • openrouter/minimax/minimax-m2.7 if OpenRouter is configured on this agent
  • Otherwise: the cheapest model in this agent's config (identify it now and fill it in below)

Get the task manager section/column GID for each agent's queue from the task manager board confirmed in Step 6. If unavailable at setup time, leave the GID blank — the agent will discover it on first heartbeat and write it in.

/think:minimal

# HEARTBEAT

## Task Manager Queue (read this, do not rediscover)
- Project: [project_display_name]
- Project ID / GID: [task_manager_project_id]
- My Queue / Section: [Agent Role] Queue
- Queue / Section GID: [section_gid_if_known]
- Heartbeat model: [minimax-m2.7 via OpenRouter OR cheapest-available-model-id]

## On each heartbeat
1. Read the project ID and queue/section above — do not browse the task manager to find your queue.
2. Query only that exact project + section.
3. Filter for tasks assigned to you only.
4. If no actionable task is assigned → reply HEARTBEAT_OK and stop.
5. If a task is assigned → report it and proceed per your role workflow in PROJECT.md.
6. If queue metadata above is missing or invalid → do one-time discovery, record the
   project ID and section GID here, then use that direct path from then on.

## Hard rules
- Never use sessions_send to message yourself.
- Never browse other projects, sections, or columns unless queue metadata is missing.
- Never reason about missed or old heartbeats.
- If this heartbeat fails for any reason (tool error, bad model config, task manager
  unreachable): log the failure and STOP. Do not retry. Do not escalate to your primary
  model. Do not troubleshoot. The next scheduled heartbeat will try again.

If an agent participates in multiple projects, include a queue block per project in HEARTBEAT.md — one per project — and check each queue in sequence.


Step 9 — Update OpenClaw Config

Use openclaw-administrator to update each participating agent's agent_to_agent allow list so agents on this project can communicate. The allow list should include every other agent on the project.

Be careful: if the agent is already on other projects, they may already have entries in their allow list for those project members. Merge, don't replace.

Example: if agent engineer is on projects A and B:

  • Project A members: pm-agent-a, dev-fe, dev-be, qa
  • Project B members: pm-agent-b, designer, copywriter, qa
  • Final allow list for engineer: pm-agent-a, dev-fe, dev-be, qa, pm-agent-b, designer, copywriter

After updating, verify:

openclaw agents list --verbose
Confirm each agent's allow list includes all project members.

Step 10 — Smoke Test

SMOKE TEST

Step 1: Manually create a test task in the [task-manager] [first-stage column]:
  Title: [TEST] Smoke test — verify [project-id]
  Description: Test task. The [client-facing role] agent should pick this up,
  acknowledge it, and either move it forward or post to a queue.

Step 2: Wait for the [client-facing role] agent's next heartbeat (up to 30 min).
  Watch for: task gaining a comment, or moving to another column.

Step 3: Confirm the agent is reading from the project folder.
  - Check [client-facing role] agent's session log
  - Should see references to ~/.openclaw/projects/[project-id]/PROJECT.md
    and the agent's queue file

Step 4: Confirm queue files are writable.
  - Either: trigger a small interaction that produces a queue entry
  - Or: manually write a test entry to one queue file and verify the
    receiving agent picks it up next session

Heartbeat confirmed working? (yes / no — describe what happened)

If something fails here, do not move to Step 11. Diagnose:

  • Agent didn't pick up task → check their AGENTS.md has the project reference, check their task manager skill is installed and authenticated
  • Agent picked up task but didn't write to queue → check project-lock.json is readable and queues/ files exist with correct permissions
  • Agent-to-agent message didn't arrive → check OpenClaw config allow list from Step 9

Step 11 — Post-Setup Snapshot and Handoff

Snapshot

If openclaw-recovery-manager is installed:

Take post-setup snapshot.
Label: post-project-setup-[project-id]-[date]-confirmed

Handoff Summary

PROJECT SETUP COMPLETE

Project: [project_display_name] ([project-id])
Type: [team_type]
Folder: ~/.openclaw/projects/[project-id]/

ROSTER:
[role]               | [agent-id]              | [model]
[client-facing role] | [agent-id]              | [model]
[feasibility role]   | [agent-id]              | [model]
[qa role]            | [agent-id]              | [model]
[operator]           | human

TASK MANAGER:
Type: [Asana / ClickUp]
Project ID: [id]
Stages: [column list]

SHARED WORKSPACE:
[path or description]
[Repo SSH URL if applicable]

HOW TO START WORK:
Send your first requirements / brief / intake to [client-facing-agent-id].
The team will:
  1. Validate feasibility through [feasibility-reviewer]
  2. Get your sign-off on the plan
  3. Execute through [executing-roles]
  4. Quality-review through [qa-role]
  5. Notify [operator or you] when ready for sign-off

ESCALATION:
Stuck > [X]h or [Y] re-escalations → work stops, [operator] notified
Client no response > [Z]h → [operator] gets a message

ADD ANOTHER PROJECT:
Run this skill again. Same agents can join multiple projects without conflict.

RECOVERY:
Pre-setup snapshot:  pre-project-setup-[project-id]-[date]
Post-setup snapshot: post-project-setup-[project-id]-[date]-confirmed

If Anything Goes Wrong

Option 1 — Recover using openclaw-recovery-manager:
  Restore: pre-project-setup-[project-id]-[date]
  Returns config to the state before setup began.

Option 2 — Diagnose with openclaw-administrator:
  Run diagnostics, identify what failed, retry just that step.

Option 3 — Describe what step failed and what error appeared.
  I can walk through the failed step again.

Adding Agents to an Existing Project Later

If the user runs this skill against an existing project with the same project ID:

  1. Detect the existing project folder
  2. Ask: "Project [id] already exists. Are you adding agents, changing the structure, or something else?"
  3. If adding agents: run only Pass 1 question 4 (agent assignment), check capabilities, update participants in project.json, append to AGENTS.md for new agents only, update allow lists in OpenClaw config
  4. If changing structure: walk through the relevant interview sections, regenerate PROJECT.md, leave history files (DECISIONS.md, SHARED_MEMORY.md) intact

Do not overwrite history files (DECISIONS.md, SHARED_MEMORY.md, queue archives) under any circumstance.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

OpenClaw

76.87%
按下载量换算535

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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