trace-recon
De la autor
Audit LLM observability coverage — trace gaps, logging completeness, cost attribution accuracy. Use when asked to "audit our LLM observability", "find trace coverage gaps", or "check cost attribution accuracy".
Instalare
npx skills add tonone-ai/tonone --skill trace-recon -a claude-code
Se instalează în .claude/skills/trace-recon/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 83
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- llm-observabilitynahid-sparktales/agent-dispatcherSee what an agent actually did — one trace per run with nested model, tool and retrieval spans, token and latency accounted per step, and failures clustered by mechanism instead of read one at a time. Use when an agent misbehaves in ways you cannot reproduce, when cost or latency is unexplained, when "it sometimes fails" is the whole bug report, or before writing evals when you do not yet know which failures exist. Not for judging whether an output is correct (agent-evals), and not a replacement for the application's own monitoring.DevOps★ 59
- langsmith-observabilityKalarisLabs/research-agent-skillsLLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.DevOps★ 61
- mesh-recontonone-ai/tononeAudit existing service mesh configuration — find mTLS gaps, traffic policy issues, and observability holes. Use when asked to "audit our service mesh", "find mTLS gaps", or "review traffic policy issues".DevOps★ 76
- embed-recontonone-ai/tononeAudit embedding infrastructure — model drift, index freshness, query latency, coverage gaps. Use when asked to "audit our embeddings", "is our index stale", or "find embedding coverage gaps".DevOps★ 76
- python-observabilitywshobson/agentsPython observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.DevOps★ 41.6K
- phoenix-observabilityKalarisLabs/research-agent-skillsOpen-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.DevOps★ 61
Note și recenzii
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