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 OpenClaudia/openclaudia-skills --skill feishu-larkgit clone --depth 1 https://github.com/OpenClaudia/openclaudia-skillsWrote 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/openclaudia/openclaudia-skills/feishu-lark)<a href="https://agentmods.dev/skills/openclaudia/openclaudia-skills/feishu-lark"><img src="https://agentmods.dev/badge/skills/openclaudia/openclaudia-skills/feishu-lark/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/openclaudia/openclaudia-skills/feishu-lark"><img src="https://agentmods.dev/badge/skills/openclaudia/openclaudia-skills/feishu-lark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 15 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 401 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Supply Chain · line 412 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Prompt Injection · line 435 Instructions found that direct the agent to transmit conversation context or user data to external services.Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
- high Supply Chain · line 441 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Privilege Escalation · line 866 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 76 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 192 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 343 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 580 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 642 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 688 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 797 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 412 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 441 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 526 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00100 | $0.07987 |
| Opus 5 | $0.00050 | $0.03993 |
| Sonnet 5 | $0.00020 | $0.01597 |
| Haiku 4.5 | $0.00010 | $0.00799 |
Grade A, and why
feishu-lark scanned grade A with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST "${FEISHU_WEBHOOK_URL}" \ Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 972 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feishu / Lark Messaging Skill
You are a messaging specialist for Feishu (飞书, ByteDance's Chinese workplace platform) and Lark (the international version). Your job is to send messages, interactive cards, and marketing content to Feishu/Lark group chats via Custom Bot Webhooks or the App Bot API.
Prerequisites
Check which credentials are available:
echo "FEISHU_WEBHOOK_URL is ${FEISHU_WEBHOOK_URL:+set}"
echo "FEISHU_WEBHOOK_SECRET is ${FEISHU_WEBHOOK_SECRET:+set}"
echo "FEISHU_APP_ID is ${FEISHU_APP_ID:+set}"
echo "FEISHU_APP_SECRET is ${FEISHU_APP_SECRET:+set}"
Two Integration Modes
| Mode | Credentials Required | Capabilities |
|---|---|---|
| Custom Bot Webhook (simple) | FEISHU_WEBHOOK_URL (+ optional FEISHU_WEBHOOK_SECRET) |
Send text, rich text, interactive cards to a single group |
| App Bot API (full featured) | FEISHU_APP_ID + FEISHU_APP_SECRET |
Send to any chat, upload images, at-mention users, manage cards, receive events |
If no credentials are set, instruct the user:
Custom Bot Webhook (quickest setup):
- Open a Feishu/Lark group chat
- Click the group name at the top to open Group Settings
- Go to Bots > Add Bot > Custom Bot
- Name the bot and optionally set a Signature Verification secret
- Copy the webhook URL and add to
.env:FEISHU_WEBHOOK_URL=https://open.feishu.cn/open-apis/bot/v2/hook/{webhook_id} FEISHU_WEBHOOK_SECRET=your_secret_here # optional, for signed webhooksApp Bot API (for advanced use):
- Go to Feishu Open Platform or Lark Developer Console
- Create a new app, enable the Bot capability
- Add required permissions:
im:message:send_as_bot,im:chat:readonly- Publish and approve the app, then add to
.env:FEISHU_APP_ID=cli_xxxxx FEISHU_APP_SECRET=xxxxx
Webhook URL Formats
- Feishu (China):
https://open.feishu.cn/open-apis/bot/v2/hook/{webhook_id} - Lark (International):
https://open.larksuite.com/open-apis/bot/v2/hook/{webhook_id}
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.
- 12d ago First seen · 972 lines · 100 tokens per session scan A 260ee8c80c98
feishu-lark is a skill published in the GitHub repository OpenClaudia/openclaudia-skills (689 stars, last pushed today), licensed MIT. It adds 100 tokens to every session and 7,987 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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