Skill audit report
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS100
34K GitHub stars
Stars/forks activity
PASS97
34K stars, 3.3K forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
MIT license
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN46
command execution surface, credential or environment access
Install availability
PASS92
npx skills add K-Dense-AI/scientific-agent-skills --skill autoskill
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL22
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/autoskill
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add K-Dense-AI/scientific-agent-skills --skill autoskill
Repository
88
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/autoskill
License
86
MIT license
Maintenance
88
2mo since push
AI review
55
The skill depends on the screenpipe daemon and a SCREENPIPE_TOKEN; if the daemon is not running or the token is invalid, the skill will fail. Documentation covers this, but a more explicit error-handling section in SKILL.md could help.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
Compare nearby options
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K Stars · Audit report
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
62K Stars · Audit report
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38K Stars · Audit report
86
Usable description available
Dependency risk
46
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
22
secrets or environment access, shell or command execution
Stars/forks activity
97
34K stars, 3.3K forks; issue activity unavailable in current metadata
Adoption
88
34K GitHub stars