langsmith-trace-analyzer

Original：🇺🇸 English

Translated

3 scripts

Fetch, organize, and analyze LangSmith traces for debugging and evaluation. Use when you need to: query traces/runs by project, metadata, status, or time window; download traces to JSON; organize outcomes into passed/failed/error buckets; analyze token/message/tool-call patterns; compare passed vs failed behavior; or investigate benchmark and production failures.

2installs

Sourcelubu-labs/langchain-agent-skills

Added on2026-03-01

NPX Install

npx skill4agent add lubu-labs/langchain-agent-skills langsmith-trace-analyzer

SKILL.md Content

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LangSmith Trace Analyzer

Use this skill to move from raw LangSmith traces to actionable debugging/evaluation insights.

Quick Start

bash

# Install dependencies
uv pip install langsmith langsmith-fetch

# Auth
export LANGSMITH_API_KEY=<your_langsmith_api_key>

Fast workflow

Download traces with

scripts/download_traces.py

(or

scripts/download_traces.ts

).

Analyze downloaded JSON with
```
scripts/analyze_traces.py
```
.
Load targeted references only when needed:
- ```
references/filtering-querying.md
```
  for query/filter syntax
- ```
references/analysis-patterns.md
```
  for deeper diagnostics
- ```
references/benchmark-analysis.md
```
  for benchmark-specific workflows

Decision Guide

Known trace IDs
Use
```
langsmith-fetch trace <id>
```
directly, or
```
--trace-ids
```
in downloader scripts.
Need to discover traces first
Use LangSmith SDK
```
list_runs/listRuns
```
with filters, then download selected trace IDs.
Need aggregate insights
Run
```
analyze_traces.py
```
for summary stats, patterns, and passed-vs-failed comparisons.

Core Workflows

1) Download and organize traces

Python:

bash

uv run skills/langsmith-trace-analyzer/scripts/download_traces.py \
  --project "my-project" \
  --filter "job_id=abc123" \
  --last-hours 24 \
  --limit 100 \
  --output ./traces \
  --organize

TypeScript:

bash

ts-node skills/langsmith-trace-analyzer/scripts/download_traces.ts \
  --project "my-project" \
  --filter "job_id=abc123" \
  --last-hours 24 \
  --limit 100 \
  --output ./traces

Output layout:

text

traces/
├── manifest.json
└── by-outcome/
    ├── passed/
    ├── failed/
    └── error/
        ├── GraphRecursionError/
        ├── TimeoutError/
        └── DaytonaError/

Notes:

Python script supports
```
--organize/--no-organize
```
.
Both scripts use SDK filtering plus
```
langsmith-fetch
```
for full trace payload export.

2) Analyze downloaded traces

bash

# Markdown report
uv run skills/langsmith-trace-analyzer/scripts/analyze_traces.py ./traces --output report.md

# JSON output
uv run skills/langsmith-trace-analyzer/scripts/analyze_traces.py ./traces --json

# Compare passed vs failed (expects by-outcome folders)
uv run skills/langsmith-trace-analyzer/scripts/analyze_traces.py ./traces --compare --output comparison.md

The analyzer reports:

message/tool-call/token/duration summaries
top tool usage
anomaly patterns (high message count, repeated tools, quick failures)
passed-vs-failed metric deltas when comparison is enabled

3) Query traces correctly (SDK)

Use official LangSmith run filter syntax via

filter

and/or

start_time

:

python

from datetime import datetime, timedelta, timezone
from langsmith import Client

client = Client()

start = datetime.now(timezone.utc) - timedelta(hours=24)
filter_query = 'and(eq(metadata_key, "job_id"), eq(metadata_value, "abc123"))'

runs = client.list_runs(
    project_name="my-project",
    is_root=True,
    start_time=start,
    filter=filter_query,
)

For TypeScript:

ts

import { Client } from "langsmith";

const client = new Client();
for await (const run of client.listRuns({
  projectName: "my-project",
  isRoot: true,
  filter: 'and(eq(metadata_key, "job_id"), eq(metadata_value, "abc123"))',
})) {
  console.log(run.id, run.status);
}

Accuracy and Schema Notes

LangSmith run fields are commonly top-level (
```
status
```
,
```
error
```
,
```
total_tokens
```
,
```
start_time
```
,
```
end_time
```
).
Some exported traces also include nested metadata (
```
metadata
```
or
```
extra.metadata
```
) and/or
```
messages
```
.
```
analyze_traces.py
```
is resilient to multiple payload shapes, including raw array payloads.
For full conversation content, prefer downloaded trace payloads over bare
```
list_runs
```
results.

Troubleshooting

Issue	Likely Cause	Action
`LANGSMITH_API_KEY` missing	Auth not configured	`export LANGSMITH_API_KEY=<your_langsmith_api_key>`
No runs returned	Wrong project/filter/time range	Verify project name and filter syntax
Empty/partial message arrays	Run schema differs or incomplete data	Use downloaded trace JSON and inspect `status/error` fields
JSON parse error on downloaded files	Bad/incomplete export	Re-download trace; use `--format raw` paths in scripts
Re-downloading same traces repeatedly	Existing files in nested folders	Use current scripts (they check existing files across output tree)

Safety for Open Source

Do not commit downloaded trace artifacts (
```
manifest.json
```
, trace JSON dumps) unless sanitized.
Trace payloads can contain user prompts, outputs, metadata, and other sensitive runtime data.
Keep this skill repository focused on scripts/templates, not production trace exports.

langsmith-trace-analyzer

NPX Install

Tags

SKILL.md Content

LangSmith Trace Analyzer

Quick Start

Fast workflow

Decision Guide

Core Workflows

1) Download and organize traces

2) Analyze downloaded traces

3) Query traces correctly (SDK)

Accuracy and Schema Notes

Troubleshooting

Safety for Open Source

Resources

scripts/

references/