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LangChain · Observability
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Helps instrument a custom Python or TypeScript agent to record events for Failproof AI, verify what gets written, and run an evaluator worker that scores the runs. | FailproofAI/ | 5.3k | — | ~6k | Automated safety check: Pass | Unknown | 4 days ago |
| 2 | Routes every LLM call in a repository through the Caveman Cloud gateway in record mode, so requests and costs are measured without changing behavior. | JuliusBrussee/ | 111k | 1 repo | ~2.6k | Automated safety check: Warn | Apache-2.0 | 2 days ago |
| 3 | Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover. | agentsope/ | 436 | — | ~4.4k | Automated safety check: Pass | MIT | 2 days ago |
| 4 | Trace, evaluate, and deploy AI agents and LLM applications with LangSmith. | langchain-ai/ | 426 | — | ~935 | Automated safety check: Pass | MIT | yesterday |
| 5 | Wire LangSmith tracing and custom metric callbacks into a LangChain 1.0 chain or LangGraph 1.0 agent correctly — env-var spelling, subgraph propagation, per-tenant dimensions, cost and latency… | jeremylongshore/ | 2.8k | — | ~3.9k | Automated safety check: Notes | MIT | yesterday |
| 6 | Wire LangChain 1.0 / LangGraph 1.0 traces into an OpenTelemetry-native backend (Jaeger, Honeycomb, Grafana Tempo, Datadog) with LLM-specific SLOs, safe prompt-content policy, and subgraph-aware span… | jeremylongshore/ | 2.8k | — | ~3.6k | Automated safety check: Pass | MIT | yesterday |
| 7 | Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration. | Kilo-Org/ | 190 | — | ~3.2k | Automated safety check: Pass | Apache-2.0 | 12 days ago |