Laporan audit skill
python-env-manager Laporan audit.
Single source of truth for "which Python environment manager does this project use, and how do I install a package with it?". Owns the detection table (pixi / uv / poetry / hatch / conda+mamba / pip+venv), the install / remove / upgrade commands per manager, and the bootstrap path when no manager is in place (default recommendation: pixi). Stops at "the install command was issued with the right manager and the package is importable". TRIGGER when (any of these): (1) **about to install / add / pin / upgrade / remove a Python package** — `pip install`, `pixi add`, `uv add`, `poetry add`, `conda install`, etc. — under any framing; (2) `data-science-python-stack` § "Missing dependency" surfaced a missing import and an install is the next step; (3) a workflow skill's Stop condition fired on a missing dependency (`build-ml-pipeline`, `evaluate-ml-pipeline`, `organize-ml-workspace`, `audit-ml-pipeline`); (4) starting a new Python project and no manager is in place yet (bootstrap with pixi unl
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
Peringatan44
command execution surface, credential or environment access
Ketersediaan pemasangan
Lulus92
npx skills add probabl-ai/skills --skill python-env-manager
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Gagal36
secrets or environment access, shell or command execution
Bukti repositori
Lulus86
https://github.com/probabl-ai/skills/tree/main/skills/python-env-manager
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-env-manager
Repositori
88
https://github.com/probabl-ai/skills/tree/main/skills/python-env-manager
Lisensi
86
BSD-3-Clause
Pemeliharaan
88
2 bulan sejak push
Tinjauan AI
55
The skill references gates (G-ENV-MGR, G-ENV-SCOPE, etc.) that are defined in other skills; ensure those are available when this skill is used in isolation.
Kelengkapan README/SKILL.md
86
Usable description available
Risiko dependensi
44
command execution surface, credential or environment access
Keamanan perintah pemasangan
92
Jalur pemasangan paket atau runtime standar
Cakupan izin
36
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
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Peringatan
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- The skill references gates (G-ENV-MGR, G-ENV-SCOPE, etc.) that are defined in other skills; ensure those are available when this skill is used in isolation.
- The SKILL.md is very long and dense; it may be challenging for an agent to parse all rules quickly, though the structure is logical.
- Financial research output is not financial advice; require human review before any live investment decision.
- 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.
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