Skill-Audit-Bericht
audit-ml-pipeline Audit-Bericht.
Owns the `audit/` folder: one `# %%` (jupytext percent) Python file per experiment, aligned 1:1 with `experiments/NN_<short_name>.py` and `journal/NN_<short_name>.md`, that loads the experiment's skore report **read-only** and uses bare-last-expression cells whose `__repr__` carries the audit's signal. The agent executes the audit file via the bundled in-process runner (`audit-ml-pipeline/scripts/run_cells.py` — IPython `InteractiveShell.run_cell`), which streams a markdown digest of each cell's stdout + last-expression repr to stdout (optionally also to a file). The digest fuels narrative work (the `JOURNAL.md` Status + History update, follow-up questions about a past experiment, cross-experiment comparison). Stops at "audit/NN_*.py is placed, executed, and the digest is available." Never calls `skore.evaluate(...)` or `project.put(...)`. TRIGGER — any of: - `iterate-ml-experiment` § 4 record-outcome — audit is dispatched FIRST (replaces scratch probes for metric extraction). - The us
OpenAgentSkill Trust Score
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub-Akzeptanz
Info62
119 GitHub-Stars
Star-/Fork-Aktivität
Warnung51
119 Stars und 7 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden88
2 Monate seit dem letzten Push
Lizenzklarheit
Bestanden86
BSD-3-Clause
README/SKILL.md-Vollständigkeit
Bestanden86
Metadaten enthalten ausreichend Nutzungs- und Workflow-Kontext
Abhängigkeits-/Laufzeitrisiko
Warnung46
command execution surface, credential or environment access
Installationsverfügbarkeit
Bestanden92
npx skills add probabl-ai/skills --skill audit-ml-pipeline
Sicherheit des Installationsbefehls
Bestanden92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
Fehlgeschlagen22
secrets or environment access, shell or command execution
Repository-Nachweis
Bestanden86
https://github.com/probabl-ai/skills/tree/main/skills/audit-ml-pipeline
Prüfstatus
Info66
KI-Prüfdaten verfügbar
Agent-validierte Ergebnisse
Info54
Noch keine Agent-Ergebnisdaten
Prüfungen
Installations- und Adoptionsprüfung
Installationspfad
92
npx skills add probabl-ai/skills --skill audit-ml-pipeline
Repository
88
https://github.com/probabl-ai/skills/tree/main/skills/audit-ml-pipeline
Lizenz
86
BSD-3-Clause
Wartung
88
2 Monate seit dem letzten Push
KI-Prüfung
55
The skill is tightly coupled to the skore ecosystem, which may limit its applicability outside that context, but this is not a defect for its intended use.
README/SKILL.md-Vollständigkeit
86
Usable description available
Abhängigkeitsrisiko
46
command execution surface, credential or environment access
Sicherheit des Installationsbefehls
92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
22
secrets or environment access, shell or command execution
Star-/Fork-Aktivität
51
119 Stars und 7 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Akzeptanz
68
119 GitHub-Stars
Warnungen
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- The skill is tightly coupled to the skore ecosystem, which may limit its applicability outside that context, but this is not a defect for its intended use.
- 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
Methode
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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