CtrlK
BlogDocsLog inGet started
Tessl Logo

dot-skill

Unified meta-skill engine for distilling colleague, relationship, or celebrity characters into reusable Skills. | 统一的 meta-skill 引擎,把 colleague、relationship、celebrity 三类对象蒸馏成可复用 Skill。

55

Quality

63%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

High

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./SKILL.md
SKILL.md
Quality
Evals
Security

Security

1 high severity finding. You should review these findings carefully before considering using this skill.

High

W007: Insecure credential handling detected in skill instructions.

What this means

The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.

Why it was flagged

The skill asks users to supply app_id/app_secret and OAuth/user tokens and shows examples that embed them verbatim in CLI flags and HTTP headers (e.g., --user-token {user_access_token}, Authorization: Bearer {user_access_token}), which requires the LLM to handle and output secret values directly.

Report incorrect finding

Low

Low-risk findings.

1 low severity finding. Worth noting, but not necessarily harmful.

Low

W011: Third-party content exposure detected (indirect prompt injection risk).

What this means

The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.

Why it was flagged

SKILL.md describes runtime collection of outsider-authored free text from Feishu/DingTalk chats/docs and Feishu/MCP/browser outputs (messages.txt/docs.txt) via tools/feishu_auto_collector.py, tools/feishu_browser.py, tools/feishu_mcp_client.py, etc., which are then read into the LLM analysis context; this is an indirect prompt-injection path from non-user text sources.

Repository
titanwings/colleague-skill
Audited
Security analysis
Snyk

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.