langsmith-trace-analyzer: Data & Analytics for AI Agents | OpenAgentSkill

Overview

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.

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LangSmith Trace Analyzer

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

Quick Start

# 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:

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:

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:

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

# 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:

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:

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.

Resources

scripts/

scripts/download_traces.py: Python downloader + organizer
scripts/download_traces.ts: TypeScript downloader + organizer
scripts/analyze_traces.py: Offline analysis and reporting

references/

references/filtering-querying.md: LangSmith query/filter examples
references/analysis-patterns.md: Diagnostic patterns and heuristics
references/benchmark-analysis.md: Benchmark-oriented analysis

View source ↗

File metadata

name: langsmith-trace-analyzer
description: "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."

View original text

---
name: langsmith-trace-analyzer
description: "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."
---

# 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

1. Download traces with `scripts/download_traces.py` (or `scripts/download_traces.ts`).
2. Analyze downloaded JSON with `scripts/analyze_traces.py`.
3. 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

1. **Known trace IDs**  
Use `langsmith-fetch trace <id>` directly, or `--trace-ids` in downloader scripts.

2. **Need to discover traces first**  
Use LangSmith SDK `list_runs/listRuns` with filters, then download selected trace IDs.

3. **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.

## Resources

### scripts/

- `scripts/download_traces.py`: Python downloader + organizer
- `scripts/download_traces.ts`: TypeScript downloader + organizer
- `scripts/analyze_traces.py`: Offline analysis and reporting

### references/

- `references/filtering-querying.md`: LangSmith query/filter examples
- `references/analysis-patterns.md`: Diagnostic patterns and heuristics
- `references/benchmark-analysis.md`: Benchmark-oriented analysis

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The SKILL.md excerpt provided is truncated, but the full content appears comprehensive based on the repository structure and included files.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 106 stars, 15 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3

Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: soba-labs/langchain-agent-skills
License: MIT
Version: 1.0.0
Last GitHub push: Aug 17, 2026
Registry updated: Sep 7, 2026
Instruction path: skills/langsmith-trace-analyzer/SKILL.md @ a2d4a1011bd7

Version reported in registry metadata; check source releases before relying on it.

Quality

64/100

Promising

Trust

58/100

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "soba-labs-langsmith-trace-analyzer",
      "task": "Use langsmith-trace-analyzer in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/soba-labs-langsmith-trace-analyzer",
    "api": "https://www.openagentskill.com/api/agent/skills/soba-labs-langsmith-trace-analyzer",
    "audit": "https://www.openagentskill.com/skills/soba-labs-langsmith-trace-analyzer/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=soba-labs-langsmith-trace-analyzer&task=Use%20langsmith-trace-analyzer%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20langsmith-trace-analyzer%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20langsmith-trace-analyzer%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/soba-labs-langsmith-trace-analyzer/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/soba-labs-langsmith-trace-analyzer"
  }
}

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Creator: soba-labs
Source: soba-labs/langchain-agent-skills
Indexed by: OpenAgentSkill community index

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