Hmbown/CodeWhale is an open-source coding agent that runs in the terminal and is written in Rust. Developers use it to inspect repositories, edit files, run commands, and coordinate work with configurable model providers, skills, MCP servers, and approval controls; the catalogue entries extend its available workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/hmbown/codewhale/feishunpx skills add Hmbown/CodeWhale --skill feishugit clone --depth 1 https://github.com/Hmbown/CodeWhaleWrote 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/hmbown/codewhale/feishu)<a href="https://agentmods.dev/skills/hmbown/codewhale/feishu"><img src="https://agentmods.dev/badge/skills/hmbown/codewhale/feishu.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00033 | $0.00400 |
| Opus 5 | $0.00016 | $0.00200 |
| Sonnet 5 | $0.00007 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
feishu 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 5d 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 / Lark
Use this skill when the user asks for Feishu, Lark, or "飞书" integration work.
Ground Rules
- Feishu China APIs use
open.feishu.cn; Lark international APIs useopen.larksuite.com. - Never hardcode app secrets, webhook secrets, tenant tokens, or user tokens.
Use environment variables such as
FEISHU_APP_ID,FEISHU_APP_SECRET,FEISHU_WEBHOOK_URL, andFEISHU_WEBHOOK_SECRET. - If credentials are unavailable, produce setup instructions or a local stub instead of pretending the integration is live.
Common Use Cases
- Bot webhook messages
- App access token and tenant access token flows
- Docs, Sheets, Wiki, and Bitable reads/writes
- Approval or workflow status updates
- Feishu/Lark MCP server configuration
Workflow
- Clarify whether the target is Feishu or Lark.
- Identify the credential type: webhook, internal app, marketplace app, or OAuth user token.
- Prefer official OpenAPI endpoints and signed webhooks when secrets are configured.
- For MCP, build or configure a server that exposes narrow tools such as
send_message,read_doc,append_sheet_row, orquery_bitable. - Register the MCP server with
codewhale mcp add, then runcodewhale mcp validateandcodewhale mcp tools. - Verify with a dry run, sandbox document, or read-back call before sending externally visible messages.
Ask for confirmation before sending messages, writing production documents, or changing approval/workflow state.
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.
- 5d ago First seen · 45 lines · 33 tokens per session scan A e3e20a53c526
feishu is a skill published in the GitHub repository Hmbown/CodeWhale (40,889 stars, last pushed 3d ago), licensed MIT. It adds 33 tokens to every session and 400 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
gog
Work with Google Workspace surfaces such as Gmail, Calendar, Drive, Docs, Sheets, and contacts through configured local tools.
gog
Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs.
feishu-drive
Feishu cloud storage file management. Activate when user mentions cloud space, folders, drive.
recipe-sync-contacts-to-sheet
Export Google Contacts directory to a Google Sheets spreadsheet.
computer-use
See the screen and operate it. Use when the user asks to click, type, or check something visually on this machine.
google-workspace
Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.