| name | langsmith |
| description | Route LangSmith work into one workflow packet before touching SDK code. Use when the user needs LangSmith tracing, offline evals, annotation/review queues, prompt-registry decisions, audit/gap review, or cross-service trace propagation for an LLM app or agent workflow. Choose one packet: trace-debug, eval, review, prompt-registry, propagation, or audit. Triggers on: LangSmith, LangChain tracing, `@traceable` / `traceable`, `wrap_openai` / `wrapOpenAI`, datasets, experiments, annotation queues, feedback criteria, Prompt Hub, run trees, trace IDs, or production confidence for an AI feature. Not for generic SLO/alert design, non-LangSmith deployment orchestration, or runtime guardrails outside LangSmith.
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| allowed-tools | Bash Read Write Edit Glob Grep WebFetch |
| license | MIT |
| compatibility | Works best when LangSmith is already the chosen tracing/eval substrate or the user needs help deciding how to instrument, debug, evaluate, or review an LLM app. Best with Python or TypeScript projects plus access to `LANGSMITH_API_KEY`; self-hosted setups may also need `LANGSMITH_ENDPOINT` and `LANGSMITH_WORKSPACE_ID`.
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| metadata | {"tags":"langsmith, langchain, tracing, observability, evaluation, llm-monitoring, prompt-hub, datasets, openevals","version":"2.1.0","source":"https://docs.langchain.com/langsmith/home"} |
LangSmith
When to use this skill
- The user already chose LangSmith and needs the smallest useful packet for tracing, evals, review, prompt ownership, or trace propagation.
- A request mentions LangChain tracing,
@traceable / traceable, wrap_openai / wrapOpenAI, annotation queues, run trees, trace IDs, datasets, or experiment comparison.
- The team needs to decide whether a change needs debugging traces, an offline eval gate, an online review queue, Prompt Hub / prompt-registry work, or multi-service lineage.
- The user has some LangSmith setup already, but confidence is still low and they need an audit / gap review.
Do not use this skill as the main workflow when:
- The real job is generic dashboards / alerts / SLOs / telemetry ownership →
monitoring-observability
- The real job is existing-log root-cause triage →
log-analysis
- The real job is code-level reproduction / bug isolation →
debugging
- The real job is deployment / rollout choreography →
deployment-automation
- The real job is generic exported-metrics interpretation or KPI synthesis →
data-analysis
- The real job is runtime guardrails / approvals / policy middleware → the relevant security or policy skill
Core idea
langsmith should behave like a workflow packet router, not a giant SDK encyclopedia.
- Label the request before naming APIs.
- Choose one primary packet.
- Pick the smallest instrumentation / eval / review surface that answers the question.
- Return a compact operator brief.
- Route adjacent observability, debugging, deployment, and policy work outward fast.
Read these support docs before choosing the packet:
