Skill-Audit-Bericht
debug-slow-spark-job Audit-Bericht.
Diagnose slow, expensive, or regressed Apache Spark and PySpark applications by comparing runtime evidence against a healthy run. Use for long stages, stragglers, skew, shuffle, spill, garbage collection, poor parallelism, small files, slow scans, scheduler delay, executor imbalance, and unexplained compute-cost growth.
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
Warnung48
51 GitHub-Stars
Star-/Fork-Aktivität
Warnung48
51 Stars und 13 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden88
2 Monate seit dem letzten Push
Lizenzklarheit
Bestanden86
Apache-2.0
README/SKILL.md-Vollständigkeit
Bestanden86
Metadaten enthalten ausreichend Nutzungs- und Workflow-Kontext
Abhängigkeits-/Laufzeitrisiko
Fehlgeschlagen38
command execution surface, credential or environment access
Installationsverfügbarkeit
Bestanden92
npx skills add EmbrasureAI/spark-observability-skills --skill debug-slow-spark-job
Sicherheit des Installationsbefehls
Bestanden92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
Fehlgeschlagen18
secrets or environment access, shell or command execution
Repository-Nachweis
Bestanden86
https://github.com/EmbrasureAI/spark-observability-skills/tree/main/skills/debug-slow-spark-job
Prüfstatus
Info66
KI-Prüfdaten verfügbar
Agent-validierte Ergebnisse
Info54
Noch keine Agent-Ergebnisdaten
Prüfungen
Installations- und Adoptionsprüfung
Installationspfad
92
npx skills add EmbrasureAI/spark-observability-skills --skill debug-slow-spark-job
Repository
88
https://github.com/EmbrasureAI/spark-observability-skills/tree/main/skills/debug-slow-spark-job
Lizenz
86
Apache-2.0
Wartung
88
2 Monate seit dem letzten Push
KI-Prüfung
55
SKILL.md says that when SPARK_HISTORY_URL is unset the agent should try localhost:18080/4040 and Spark config before asking the user, but spark_history_api.py only exits with 'Set --base-url or SPARK_HISTORY_URL'. The discovery behavior is described but not implemented in the script, so the agent must manually probe or pass --base-url to match the documented workflow.
README/SKILL.md-Vollständigkeit
86
Usable description available
Abhängigkeitsrisiko
38
command execution surface, credential or environment access
Sicherheit des Installationsbefehls
92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
18
secrets or environment access, shell or command execution
Star-/Fork-Aktivität
48
51 Stars und 13 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Akzeptanz
68
51 GitHub-Stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnungen
- 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
- SKILL.md says that when SPARK_HISTORY_URL is unset the agent should try localhost:18080/4040 and Spark config before asking the user, but spark_history_api.py only exits with 'Set --base-url or SPARK_HISTORY_URL'. The discovery behavior is described but not implemented in the script, so the agent must manually probe or pass --base-url to match the documented workflow.
- The skill has no explicit Setup/Requirements section. It assumes Python 3, jq, network access to the history server, and the script directory as the working directory. These prerequisites should be stated directly in SKILL.md.
- 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
- GitHub adoption: 51 GitHub stars
- Stars/forks activity: 51 stars, 13 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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