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 skills add kngwyc3/Agent-Learning-Hub --skill lark-skillgit clone --depth 1 https://github.com/kngwyc3/Agent-Learning-HubWrote 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.
![agentmods badge for [object Object]](/badge/skills/kngwyc3/agent-learning-hub/lark-skill/github.svg?v=0-8-A){kind=icon}
[](https://agentmods.dev/skills/kngwyc3/agent-learning-hub/lark-skill)<a href="https://agentmods.dev/skills/kngwyc3/agent-learning-hub/lark-skill"><img src="https://agentmods.dev/badge/skills/kngwyc3/agent-learning-hub/lark-skill/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.
![agentmods 80×15 button for [object Object]](/badge/skills/kngwyc3/agent-learning-hub/lark-skill.svg?v=A-x){kind=icon}
<a href="https://agentmods.dev/skills/kngwyc3/agent-learning-hub/lark-skill"><img src="https://agentmods.dev/badge/skills/kngwyc3/agent-learning-hub/lark-skill.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00008 | $0.00319 |
| Opus 5 | $0.00004 | $0.00160 |
| Sonnet 5 | $0.00002 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
[object Object] 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
Lark / Feishu Integration Skill
Use this skill when the user needs to interact with Feishu (Lark) APIs: docs, sheets, calendar, IM, or Base tables via lark-cli or Open API.
When To Use
- The user mentions 飞书, Lark, lark-cli, 多维表格, 云文档, or Feishu bot workflows.
- Tasks involve reading/writing Feishu resources, auth setup, or permission errors.
- The user wants to automate Feishu workflows from an agent.
When Not To Use
- The user needs generic HTTP API help unrelated to Feishu.
- Required scopes or tenant admin approval are missing and cannot be obtained.
Steps
- Check lark-cli auth:
lark-cli auth status(or guide user throughlark-cli auth login). - Identify resource type: doc, sheet, base, calendar, im, task.
- Read the matching lark-* skill for command patterns before calling APIs.
- Use
--as useror--as botconsistently; handle Permission denied with scope checklist. - Return structured results with resource IDs and links.
Output
- Commands run (redact tokens).
- Resource identifiers (doc_token, spreadsheet_token, etc.).
- Next steps if permission or scope is missing.
Verification
- No secrets in output.
- Links use full https:// URLs.
- Errors include actionable fix (scope name, admin approval path).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 40 lines · 8 tokens per session scan A c18eb3fc15bc
[object Object] is a skill published in the GitHub repository kngwyc3/Agent-Learning-Hub (128 stars, last pushed 2mo ago), licensed MIT. It adds 8 tokens to every session and 319 once invoked, about $0.0000 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
google-workspace
Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
wecomcli-sheet
A tool for managing WeCom online spreadsheets, including spreadsheet files, data, and subtables. WeCom is an enterprise collaboration platform.
google-workspace
Access Google Workspace APIs (Drive, Docs, Calendar, Gmail, Sheets, Slides, Chat, People) via local helper scripts without MCP. Handles OAuth login and direct API calls.
gog-workspace
Use the gog CLI for Google Workspace tasks across Gmail, Calendar, Drive, Docs, Sheets, Contacts, and related services. Use when the user asks to check email, search Gmail, inspect calendar events, find Drive files, read Docs or Sheets, or manage Google Workspace data through gog.
googleworkspace
Manage Google Drive, Gmail, Calendar, Sheets, Docs, and Chat via the gws CLI.