Individual skill
agentsop-observability-setup
Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover. Each of those installs one backend; none of them help you DECIDE which backend fits your stack/scale/budget, nor give you a one-line autolog that turns it on fast. Use when starting any LM project, before the first deploy, or the moment someone asks "why did it do that?" and there are no traces to answer with. The skill picks a backend by stack (LangSmith for LangChain/LangGraph; Phoenix for OSS/local OpenTelemetry; MLflow for ML-shops already on MLflow; Langfuse for self-host), wires one-line autolog, verifies traces land, and adds eval hooks — instrumenting BEFORE you need it. Cross-links the first-debug-move skill [[agentsop-prompt-history-inspect]]. Do NOT activate to re-teach a backend you already chose (defer to its own skill), or for non-LM ML experiment tracking with no LLM calls (that is plain MLflow).
skills/agentsop-observability-setup/SKILL.md
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- Last checked
- Nov 6, 2026
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- Oct 24, 2026
- License
- MIT
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README.mddoc · 2,336 bytesSKILL.mdcore · 18,186 bytesSKILL.mdcore · 18,186 bytesintermediate/operation_candidates.jsonasset · 8,155 bytesreferences/R1-source-evidence.mddoc · 5,253 bytes
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# Observability Setup — Which Backend + One-Line Autolog
> *"Instrument before you need it. The cheapest debugging session is a trace you already have."*
This is an **ENHANCE overlay**. The local skills [[langsmith]], [[phoenix]] and [[mlflow]] each
teach **one** backend deeply. This skill sits one level up: it answers the question those skills
cannot — *which one, and how do I turn it on in a single line right now* — then hands off to the
chosen backend's own skill for depth.
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## 1. 何时激活 (When to activate)
Activate at one of three moments — earlier is always cheaper: