Laporan audit skill
autoskill Laporan audit.
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.
Trust Score OpenAgentSkill
Trust Score OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adopsi GitHub
Lulus100
34K star GitHub
Aktivitas star/fork
Lulus97
34K star dan 3.3K fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus100
3 hari sejak push
Kejelasan lisensi
Lulus86
MIT license
Kelengkapan README/SKILL.md
Lulus86
Metadata memuat konteks penggunaan dan alur kerja yang cukup
Risiko dependensi/runtime
Peringatan46
command execution surface, credential or environment access
Ketersediaan pemasangan
Lulus92
npx skills add K-Dense-AI/scientific-agent-skills --skill autoskill
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Gagal22
secrets or environment access, shell or command execution
Bukti repositori
Lulus86
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/autoskill
Status peninjauan
Info66
Data tinjauan AI tersedia
Hasil terbukti Agent
Info54
Belum ada data hasil Agent
Pemeriksaan
Tinjauan pemasangan dan adopsi
Jalur pemasangan
92
npx skills add K-Dense-AI/scientific-agent-skills --skill autoskill
Repositori
88
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/autoskill
Lisensi
86
MIT license
Pemeliharaan
100
3 hari sejak push
Tinjauan AI
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.
Kelengkapan README/SKILL.md
86
Usable description available
Risiko dependensi
46
command execution surface, credential or environment access
Keamanan perintah pemasangan
92
Jalur pemasangan paket atau runtime standar
Cakupan izin
22
secrets or environment access, shell or command execution
Aktivitas star/fork
97
34K star dan 3.3K fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
88
34K star GitHub
Peringatan
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- 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.
- Cloud backends (Claude/Foundry) are optional but require the user to supply API keys; the skill does not perform additional runtime validation of the endpoint beyond the cleartext check, so a misconfigured (but HTTPS) remote endpoint could receive data. This is acceptable given the user explicitly configures it, but the documentation could emphasise the privacy implications more strongly.
- Permission surface needs review: secrets or environment access, shell or command execution
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Metode
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.
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