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langsmith-trace-analyzer

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;

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Preis unbestätigt★ 106 GitHub-StarsVerzeichnis aktualisiert · 7. Sept. 2026agent-skill

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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

Quelle ansehen ↗

Dateimetadaten

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."

Originaltext anzeigen

---
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

Quelle prüfen

Preis und Betriebskosten

Skill beziehen: Preis unbestätigt
Ausführen: Anforderungen unbestätigt. Agenten-, API- und Dienstkosten an der Quelle prüfen.
Lizenz: MIT
Preis unbestätigt: Der Preis ist noch nicht bestätigt. Vorhandene Quell- und Installationslinks bleiben verfügbar.

Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →

Skill-Quelle erfasst

Ein Anleitungspfad ist erfasst. Das ist kein Ausführungstest und keine Sicherheits- oder Kompatibilitätsgarantie.

Vor Installation prüfen: Automatische Installation vermeiden

Lizenz: 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

Vollständiges Audit öffnen

Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.

Mit einer kleinen Aufgabe beginnen

1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.

Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.

Quelle und Nutzungshinweise

Erfasst

Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.

Quell-Repository: soba-labs/langchain-agent-skills
Lizenz: MIT
Version: 1.0.0
Letzter GitHub-Push: 17. Aug. 2026
Verzeichnis aktualisiert: 7. Sept. 2026
Anleitungspfad: skills/langsmith-trace-analyzer/SKILL.md @ a2d4a1011bd7

Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.

Qualität

64/100

Vielversprechend

Vertrauen

58/100

Do not auto-install

Audit

72/100

Prüfung nötig

Vollständiges Audit öffnen Eval-Bericht ansehen

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

Verified installs: —
Ergebnisse: —

Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.

Agent-Zugang

Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.

Installations-API öffnen LLM-Textformat Manifest öffnen Auto-Auflösungsplan

Weitere Details

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  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 64,
    "label": "Promising"
  },
  "supply": {
    "track": "Data, BI, and analytics",
    "scenario": "Database and SQL",
    "maintenance": "2mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "The SKILL.md excerpt provided is truncated, but the full content appears comprehensive based on the repository structure and included files.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Quality score needs review",
    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
  "agent_contract": {
    "task_input": "Use langsmith-trace-analyzer in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 66/100 Manual review",
      "Audit: 72/100 Needs review",
      "Safety: 28/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "soba-labs-langsmith-trace-analyzer (langsmith-trace-analyzer)",
      "install_command": "npx skills add soba-labs/langchain-agent-skills --skill langsmith-trace-analyzer",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "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"
  }
}

Für Ersteller

Quelle des Eintrags

Registry-indexiert

Beanspruchbar

Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.

Ersteller: soba-labs
Quelle: soba-labs/langchain-agent-skills
Indexiert von: OpenAgentSkill Community-Index

Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.

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