Agent Skill 生態治理
Series · 1 posts
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After the Party: Governing What a Viral Agent-Skill Ecosystem Left Behind
AdvancedA deep reading of After the Party’s OpenClaw and ClawHub ecosystem study: 91 days of explosive growth, download concentration, the reviewability gap, privilege evidence, scanner disagreement, and the governance method that can transfer without pretending the rates do.
Understand it in 90 seconds
- Research problem
- When an agent-skill registry expands rapidly, which signals can still support governance decisions across downloads, stars, versions, comments, declared capabilities, and executable privileges? The authors study OpenClaw and ClawHub through growth, association portability, reviewability, and scanner agreement.
- Core insight
- A skill does not live only in its text. The same SKILL.md or package can expose a different privilege surface under a different host, tool visibility, execution context, and policy. Registry metadata therefore cannot collapse popularity, reviewability, static evidence, and runtime behavior into one trust score.
- Strongest evidence
- RQ1 reconstructs stock growth from 33,399 to 65,175 over 91.11 days; the top 10% receive 46.93% of downloads and the Gini coefficient is 0.528. RQ3 finds at least one privilege signal in 85.06% of evaluable skills. RQ4 shows only 446 items flagged by all three scanners; on the small adjudicated reference set, the LLM scanner has 61.06% sensitivity versus 21.67% for the static scanner.
- Main boundary
- This is not an insecurity prevalence estimate for every registry, nor a general scanner benchmark. It is one ecosystem, a set of snapshots, partially reconstructed history, withdrawn data, missing fields, and no perfect ground truth.
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