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
63%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
High
Do not use without reviewing
Fix and improve this skill with Tessl
tessl review fix ./SKILL.mdSecurity
1 high severity finding. You should review these findings carefully before considering using this skill.
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.
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.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
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.
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.
SKILL.md
47039d0
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.