Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrornpx agentmods add skills/gabrielmoreira/agent-skills-mirror/feishu-setupWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/feishu-setup)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/feishu-setup"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/feishu-setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/feishu-setup"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/feishu-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00087 | $0.00664 |
| Opus 5 | $0.00044 | $0.00332 |
| Sonnet 5 | $0.00017 | $0.00133 |
| Haiku 4.5 | $0.00009 | $0.00066 |
Grade A, and why
feishu-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Feishu Auto Setup
Automate the creation and configuration of a Feishu (Lark) bot application on the Feishu Open Platform. The user only needs to scan a QR code to log in; all other steps are handled automatically by the one-shot script feishu_full_setup.py running in the sandbox.
Prerequisites
- The sandbox container must be running (provides the built-in browser via MCP).
- The backend service must be reachable from the sandbox at
http://backend:8000.
Execution
该 skill 只支持使用总控脚本 feishu_full_setup.py 一次性完成全部流程,不再支持单独执行 feishu_auto_setup.py。
python3 /builtin-skills/feishu-setup/scripts/feishu_full_setup.py --name "ScienceClaw 助手"
使用 agent 的 execute 工具执行上面的总控命令时,必须显式设置 timeout=900。不要使用 timeout=300,因为飞书页面自动化、扫码等待、权限导入和事件配置可能持续数分钟。
注意:总控脚本执行时间较长。若执行过程中遇到超时或失败,不要再单独执行 feishu_auto_setup.py 的任一步骤,否则会打乱 feishu_full_setup.py 的页面状态与执行顺序。如果检测到执行失败,则等待 3 分钟后退出。如果已经完成到第 7 步骤,可以视为成功。
脚本会自动完成以下步骤:
- 打开飞书开放平台并等待扫码登录
- 创建应用、添加机器人、首次发布
- 获取
app_id/app_secret - 回写系统
LARK_APP_ID/LARK_APP_SECRET并建立长连接 - 配置应用身份权限
- 配置用户身份权限
- 配置事件与回调
- 第二次发布
如需跳过某些步骤,可使用:
--skip-app-permissions--skip-user-permissions--skip-step2-publish
如需在 workspace 中执行,只复制总控脚本即可:
cp /builtin-skills/feishu-setup/scripts/feishu_full_setup.py {workspace_dir}/feishu_full_setup.py
python3 {workspace_dir}/feishu_full_setup.py --name "ScienceClaw 助手"
总控脚本会在同一条命令执行过程中等待用户扫码登录飞书。
如果 feishu_full_setup.py 执行失败,则等待 3 分钟后退出, 如果已经完成到第 7 步骤,可以视为成功。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 55 lines · 87 tokens per session scan A 47868820b76a
feishu-setup is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed yesterday), licensed MIT. It adds 87 tokens to every session and 664 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
agentmail
Use your assigned AgentMail inbox to read email tasks, explicitly send or reply, and check delivery. Provided automatically by your inbox assignment.
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
pinchtab-mcp
Use this skill when a task requires browser automation through PinchTab's MCP server connected to a remote browser instance. Covers navigation, element interaction, data extraction, form filling, multi-step flows, and session management via MCP tools.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
peekaboo
Capture and automate macOS UI with the Peekaboo CLI.