Laporan audit skill
python-api Laporan audit.
Look up the public API of a Python package against the *installed version* and cache what's worth keeping. Four shapes by question type: (0) cache hit under `scratch/api/<lib>/<version>/`; (1) `inspect.signature` + `pydoc.render_doc` for a symbol; (2) `dir` / `pkgutil.iter_modules` for a module surface; (3) WebSearch + WebFetch of versioned docs for narrative ("how", "which", "what does X return when Y"). Never write a symbol from training-data memory — recognition is not a lookup. TRIGGER — any of: - About to name a symbol (function / class / method / arg) in code. - User asks "what's the signature of X?", "what's in module Y?", "how do I call X?", "which of A/B should I use?". - User asks "what does X return when <condition>?" (Shape 3 — see decision table). - Another workflow skill (`build-ml-pipeline`, `evaluate-ml-pipeline`, `iterate-from-skore`, `smoke-test-ml-pipeline`) says "consult the API skill". - About to reach for a library's "obvious" pattern from memory. SKIP when: the s
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
Info62
119 star GitHub
Aktivitas star/fork
Peringatan51
119 star dan 7 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus88
2 bulan sejak push
Kejelasan lisensi
Lulus86
BSD-3-Clause
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 probabl-ai/skills --skill python-api
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/probabl-ai/skills/tree/main/skills/python-api
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 probabl-ai/skills --skill python-api
Repositori
88
https://github.com/probabl-ai/skills/tree/main/skills/python-api
Lisensi
86
BSD-3-Clause
Pemeliharaan
88
2 bulan sejak push
Tinjauan AI
55
The skill relies on WebSearch/WebFetch for narrative documentation (Shape 3), which could theoretically expose the agent to untrusted content if the search results are manipulated. However, the skill does not instruct executing code from web content, so risk is low.
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
51
119 star dan 7 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
68
119 star GitHub
Peringatan
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- The skill relies on WebSearch/WebFetch for narrative documentation (Shape 3), which could theoretically expose the agent to untrusted content if the search results are manipulated. However, the skill does not instruct executing code from web content, so risk is low.
- The skill references other skills (e.g., build-ml-pipeline) that may not be present in all environments, but this is a dependency issue rather than a flaw in the skill itself.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 119 stars, 7 forks; issue activity unavailable in current metadata
- 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.
Bandingkan opsi sekitar
Skill terkait untuk diaudit berikutnya
mono-color
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 Star · Laporan audit
Last30days Skill
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.
64K Star · Laporan audit
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38K Star · Laporan audit