ClawHub

Economic Incentive Misalignment Detector

v1.0.0

Helps identify when marketplace economic incentives systematically favor quantity over quality — creating structural pressure toward publishing unsafe skills...

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by@andyxinweiminicloud
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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Benign
high confidence
✓
Purpose & Capability
Name/description (detect economic incentive misalignment in a marketplace) align with the declared runtime needs: curl to fetch marketplace data and python3 to run analyses. No unrelated binaries, env vars, or config paths are requested.
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Instruction Scope
SKILL.md is high-level and directs the agent to analyze marketplace data, publisher metrics, and policy documents. It does not instruct the agent to read system files, environment secrets, or other unrelated data. Because instructions are abstract (no concrete data sources or constrained commands), the agent will have broad discretion about which endpoints or datasets to fetch — reasonable for this analyzer but worth noting as a behavioral surface.
✓
Install Mechanism
No install spec and no code files — lowest-risk category. The skill is instruction-only, so nothing is written to disk or auto-installed by the registry.
✓
Credentials
The skill requests no environment variables, no credentials, and no config paths. That is proportionate: analyzing marketplace economics typically requires datasets rather than platform credentials.
✓
Persistence & Privilege
always is false and the skill does not request persistent system presence or modify other skills. Model invocation is allowed (the platform default), which is normal for an analysis skill.
Assessment
This skill is internally consistent and doesn't request secrets or install code. Before using it, consider: (1) If you want analysis of a private marketplace, supply the dataset or export yourself rather than handing over credentials — the skill does not request them but the agent might fetch endpoints if you instruct it to. (2) Because SKILL.md is high-level, review any external URLs or data sources the agent attempts to access during a run. (3) Run sensitive analyses in a controlled environment (local agent or sandbox) if the data contains non-public metrics.

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.
Termshttps://spdx.org/licenses/MIT-0.html

Runtime requirements

💰 Clawdis
Binscurl, python3

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