Deep Cognition

v1.0.0

提供文章创作中的深层认知指导,强调主观态度、本质揭示和范式升华,帮助传达“为什么这样做”的核心理念。

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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Benign
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
The name/description promise 'deep cognition' writing guidance and the SKILL.md contains templates, checklists, and examples for that purpose. It does not request unrelated binaries, credentials, or config paths.
Instruction Scope
SKILL.md is limited to prose templates, thinking paths, and editorial checklists for crafting articles. It does not instruct the agent to read files, access environment variables, call external endpoints, or execute commands.
Install Mechanism
No install spec and no code files — lowest-risk instruction-only skill. Nothing will be written to disk or downloaded by the skill itself.
Credentials
The skill declares no required environment variables, credentials, or config paths; the content contains only writing guidance and example references (OpenClaw/Claude Code) — these are examples, not requirements.
Persistence & Privilege
Skill is not forced-always; model invocation is allowed (platform default). That autonomous invocation is normal and not concerning here because the skill requests no extra privileges or secrets.
Assessment
This skill is essentially a style/template guide and appears internally consistent and low-risk: it asks for no credentials, installs nothing, and its instructions stay within writing guidance. Before installing, consider: 1) confirm you trust the (unknown) source if provenance matters to you; 2) if you let agents run autonomously, be aware the agent could apply these templates in contexts you didn't intend — test in a sandbox first; 3) the skill references OpenClaw and Claude Code as examples only; it does not by itself integrate with or require those services. Overall it is coherent for its stated purpose, but benign ≠ vetted — review any outputs produced by the agent for accuracy and policy compliance.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

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