Skill: cyecho-io/feishu-agent-add (version 1.0.0)

--- name: feishu-agent-add description: Use this skill when users want to add a Feishu agent for OpenClaw, especially when they say things like “帮我增加一个名字叫xxx，用来做xxx的飞书agent”, want a guided prompt flow, or want a one-command way to generate the matching OpenClaw config. license: MIT --- # feishu-agent-add This skill is the conversational front end for the local script `scripts/add_feishu_agent.py`. This project is designed for OpenClaw users, but the skill name intentionally stays short: `feishu-agent-add`. ## When To Use Use this skill when the user wants to: - add a new Feishu-connected OpenClaw agent - avoid hand-editing `openclaw.json` - configure a new agent through a few follow-up questions - get a ready-to-run one-line command for advanced usage ## Core Rule Do not hand-edit `openclaw.json` unless the user explicitly asks for manual fallback. Prefer running: ```bash python3 scripts/add_feishu_agent.py ... ``` The script is the execution core. This skill should mainly: 1. understand the user's request 2. ask only for missing required fields 3. preview the plan 4. run the script 5. summarize the result and next steps ## Required Inputs Collect these fields before execution: - `agent_name` - `purpose` - `agent_id` - if missing, propose one derived from the name - `app_id` - `app_secret` These can use defaults unless the user says otherwise: - `workspace_path` - default: `~/.openclaw/workspace-{agent_id}` - `model` - default: inherit from the current OpenClaw config - `enable_agent_to_agent` - default: `true` - `workspace_mode` - default: `auto` - `init_templates` - default: `true` ## Conversational Flow ### 1. Parse what the user already gave For a request like: > 帮我增加一个名字叫小红书运营，用来做内容选题和文案生成的飞书agent extract: - `agent_name = 小红书运营` - `purpose = 内容选题和文案生成` - `agent_id = xiaohongshu` or another short slug candidate If `agent_id` is missing, propose one instead of asking an open-ended question. ### 2. Ask the minimum follow-up questions Only ask for the missing required fields. Prefer one compact message. Typical follow-up: - proposed `agent_id` - Feishu `App ID` - Feishu `App Secret` Only ask about optional fields if the user indicates they care. ### 3. Preview before execution Before running the script, summarize: - agent name - agent id - purpose - workspace path - whether agent-to-agent collaboration will be enabled ### 4. Run the script Run from the skill directory: ```bash python3 scripts/add_feishu_agent.py \ --agent-id <agent-id> \ --agent-name "<agent-name>" \ --purpose "<purpose>" \ --app-id <app-id> \ --app-secret <app-secret> \ --json-output \ --yes ``` Add optional flags only when needed: - `--model <model>` - `--workspace-path <path>` - `--disable-agent-to-agent` - `--workspace-mode cli|mkdir|auto` - `--no-init-templates` - `--dry-run` ## Advanced User Mode If the user prefers a single terminal command, give them a ready-to-run example instead of a manual JSON recipe. Use this pattern: ```bash python3 scripts/add_feishu_agent.py \ --agent-id trader \ --agent-name "交易小助手" \ --purpose "股票和 ETF 分析" \ --app-id cli_xxx \ --app-secret secret_xxx \ --yes ``` ## Output Expectations After execution, summarize: - whether config was written successfully - the workspace path - whether starter files were initialized - that OpenClaw should be restarted - where to refine the agent identity, usually `SOUL.md` If the script fails, report the concrete reason and do not improvise partial manual edits unless the user asks for that fallback. ## Notes - The script already handles validation, backup, and config updates. - Prefer `--dry-run` first when the user asks for a preview. - If the user asks how to install or use this project, point them to `README.md`.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)