thinking-model-enhancer

v1.0.0

Advanced thinking model that improves decision-making speed and accuracy. Integrates with memory system to compare and integrate previous thinking models for continuous enhancement.

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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
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Benign
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
Name/description align with included Python modules: the package implements thinking-model logic, memory integration, performance tracking and an initialization script that creates ~/.claude/thinking_models. Required binaries (python3, bash) and listed files are appropriate and proportionate for this purpose.
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Instruction Scope
SKILL.md instructs the agent to 'gather relevant data and context from memory and external sources' and to search ClawHub/GitHub/community solutions; that gives the agent broad discretion to access external sites. The SKILL.md also contains a detected prompt-injection pattern (see scan_findings_in_context) which may attempt to manipulate runtime behavior. Some README/PUBLISH_GUIDE steps instruct login/publishing flows (clawdhub login) — these are outside runtime needs and could prompt credential use if followed.
Install Mechanism
No install spec / no external downloads. This is instruction-only from the registry perspective; the code is bundled in the skill (no network-install step found in provided files). That reduces supply-chain risk compared to remote downloads.
Credentials
The skill requests no environment variables or external credentials, which is appropriate. It does, however, persist data and metadata under user home (~/.claude/thinking_models) and will read/write local snapshot/index/metrics files — this is expected for a memory-integrated skill but is persistent local access the user should be aware of.
Persistence & Privilege
always:false (good). The skill creates and maintains persistent state in the user's home directory and can run autonomously when invoked by the agent (default platform behavior). It does not request elevated/system-wide privileges or modify other skills' configs based on the provided files.
Scan Findings in Context
[prompt-injection: you-are-now] unexpected: A prompt-injection pattern was detected inside SKILL.md. This is not necessary for a decision-making helper and may indicate an attempt to influence or override agent behavior. Review SKILL.md and any truncated portions for hidden directives before trusting autonomous runs.
What to consider before installing
What to consider before installing: - The skill appears to do what it claims: Python modules implement model selection, memory storage, metrics, and a CLI entrypoint. It will create and use ~/.claude/thinking_models to store snapshots, indices, and metrics — expect persistent local files. - Review SKILL.md and all code yourself (or in a safe environment). A prompt-injection pattern was detected in the SKILL.md content; that could try to change the agent's behavior or instructions. Do not run the skill with autonomous privileges until you are comfortable with the full SKILL.md and source. - The docs include publishing/login commands (clawdhub login / publish). Those are for publishing and will open a browser for auth; you don't need to run them to use the skill. Avoid running publishing flows unless you intend to publish and trust the origin. - Network behavior: the SKILL.md encourages searching external sources (ClawHub/GitHub); the visible code uses only standard library and local filesystem. Verify the omitted/truncated files for any HTTP/remote endpoints before allowing network access. - Recommended safe steps: 1) Inspect all source files (including the truncated ones) for outbound network calls, hard-coded endpoints, or subprocess invocations. 2) Run the initialization script in a sandbox/throwaway account to confirm it only creates ~/.claude directories and config.json. 3) If you must run it on your main environment, back up important data and restrict the agent's filesystem/network access if possible. 4) Do not grant this skill 'always:true' or persistent elevated privileges until code and docs are fully reviewed. If you want, I can: (A) list the specific files/lines that mention external access or subprocesses (if you provide the omitted file contents), or (B) point out exact SKILL.md locations of suspicious instructions so you can edit them before use.

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.

Runtime requirements

🧠 Clawdis
Binspython3, bash
Any binpython3, python

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