agentleFS
noah-1106noah-1106/Skills_Repo/skills/coze-workflow-1.1.3/SKILL.md

coze_workflow

Skill32 starsChanged 7 days agoMITView on GitHub

Coze Workflow Executor | Coze 工作流执行技能 Execute Coze workflows with workflow_id and parameters. 接收参数调用工作流,返回执行结果。 Pure invocation layer with no business logic. 纯净的调用层,不处理业务逻辑。 Base skill for all Coze workflow integrations. 所有 Coze 工作流集成的基础技能。

  • Reads credentials
  • Sends data out

The file

Files
SKILL.md

Coze Workflow | Coze 工作流执行技能

纯净的调用层技能。接收 workflow_id 和 parameters,执行工作流,返回结果。这是其他 Coze 工作流技能依赖的基础技能。

Pure invocation layer skill. Receives workflow_id and parameters, executes the workflow, and returns results. This is the base skill that other Coze workflow skills depend on.


依赖关系 / Dependencies

本技能被以下技能依赖 / This skill is a dependency for:

  • image-gen-coze - 图像生成 / Image generation via Coze workflows
  • 其他自定义 Coze 工作流技能 / Other custom Coze workflow skills

配置 / Configuration

~/.openclaw/skills/coze_workflow/config.json:

{
  "api_key": "pat_xxx",
  "base_url": "https://api.coze.cn"
}

职责边界 / Responsibility Boundaries

职责 / Responsibilitycoze_workflow业务技能 / Business Skill
执行工作流 / Execute workflow✅❌
参数构建 / Parameter building❌✅
结果解析 / Result parsing❌✅

调用方式 / Usage

输入 / Input

{
  "workflow_id": "string",
  "parameters": {}  // 任意 JSON / Any JSON
}

输出 / Output

返回 Coze API 的原始响应 / Returns Coze API raw response:

{
  "execute_id": "string",
  "status": "Success|Fail|Running",
  "output": "string",  // 工作流输出(JSON字符串)/ Workflow output (JSON string)
  "debug_url": "string"
}

执行方法 / Execution Methods

方法 1:流式执行(推荐)/ Method 1: Stream (Recommended)

curl -X POST "${COZE_BASE_URL}/v1/workflow/stream_run" \
  -H "Authorization: Bearer ${COZE_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "workflow_id": "xxx",
    "parameters": {...}
  }'

响应 / Response:SSE 流,提取 event: Message 的 data.content 字段

方法 2:轮询查询 / Method 2: Polling

curl "${COZE_BASE_URL}/v1/workflows/{workflow_id}/run_histories/{execute_id}" \
  -H "Authorization: Bearer ${COZE_API_KEY}"

版本历史 / Changelog

  • v1.1.3: 添加中英文对照 / Add bilingual support
  • v1.1.1: 明确职责边界 / Clarify responsibility boundaries
  • v1.1.0: 流式执行 + 轮询 / Stream + Polling
  • v1.0.0: 初始版本 / Initial version

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.