langgraph-testing-evaluation

langgraph-testing-evaluation is a skill for Claude Code, Codex from soba-labs/langchain-agent-skills. It costs 99 tokens per session (2,000 once invoked), scanned A, original, MIT.

A testing and evaluation guide for LangGraph and LangChain agents. LangGraph and LangChain are tools for building software agents; TDD means writing tests to check expected behavior during development.

In plain words
What is it for?
It supports unit and integration tests, multi-step behavior checks, dataset-based evaluations in LangSmith, and comparisons between agent versions.
Why use it?
It helps find broken steps, tool interactions, and changes in agent quality before release.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It supports unit and integration tests, multi-step behavior checks, dataset-based evaluations in LangSmith, and comparisons between agent versions.

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Install with agentmods
npx agentmods add skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add soba-labs/langchain-agent-skills --skill langgraph-testing-evaluation
Clone the repo
git clone --depth 1 https://github.com/soba-labs/langchain-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for langgraph-testing-evaluation

README.md
[![agentmods](https://agentmods.dev/badge/skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation/github.svg)](https://agentmods.dev/skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation)
Your own site
<a href="https://agentmods.dev/skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation"><img src="https://agentmods.dev/badge/skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for langgraph-testing-evaluation

Your own site · 80×15
<a href="https://agentmods.dev/skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation"><img src="https://agentmods.dev/badge/skills/soba-labs/langchain-agent-skills/langgraph-testing-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,000 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.02000
Opus 5 $0.00049 $0.01000
Sonnet 5 $0.00020 $0.00400
Haiku 4.5 $0.00010 $0.00200

Measured 9d ago against content hash 2d4818b80193, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

langgraph-testing-evaluation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 11 executable files (assets/templates/test_template.py, scripts/compare_agents.js, scripts/compare_agents.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/langgraph-testing-evaluation/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LangGraph Testing & Evaluation

Practical workflows for validating agent quality with:

  • Unit/integration tests
  • Trajectory evaluation
  • LangSmith dataset evaluations
  • A/B-style comparisons between versions

Use this file for high-level flow. Load references/* for detailed implementation.

Start Here

Choose the smallest approach that answers your question:

Goal Primary method Load first
Validate node logic quickly Unit tests with mocks references/unit-testing-patterns.md
Validate multi-step agent behavior Trajectory evaluation references/trajectory-evaluation.md
Track quality over datasets over time LangSmith evaluation references/langsmith-evaluation.md
Compare old vs new agent versions A/B comparison references/ab-testing.md

Recommended order:

  1. Unit tests
  2. Integration/trajectory checks
  3. Dataset evaluation in LangSmith
  4. A/B comparison before deployment

Quick Commands

Run from repo root.

Generate test scaffolding

# Python (preferred)
uv run skills/langgraph-testing-evaluation/scripts/generate_test_cases.py my_agent:graph --output tests/ --framework pytest

# JavaScript/TypeScript
node skills/langgraph-testing-evaluation/scripts/generate_test_cases.js ./my-agent.ts:graph --output tests/ --framework vitest

Run trajectory evaluation

# Python: LLM-as-judge
uv run skills/langgraph-testing-evaluation/scripts/run_trajectory_eval.py my_agent:run_agent my_dataset --method llm-judge --model openai:o3-mini

# Python: trajectory match
uv run skills/langgraph-testing-evaluation/scripts/run_trajectory_eval.py my_agent:run_agent dataset.json --method match --trajectory-match-mode strict --reference-trajectory reference.json

# JavaScript/TypeScript
node skills/langgraph-testing-evaluation/scripts/run_trajectory_eval.js ./agent.ts:runAgent my_dataset --method llm-judge --model openai:o3-mini --max-concurrency 4

Run LangSmith dataset evaluation

# Python
uv run skills/langgraph-testing-evaluation/scripts/evaluate_with_langsmith.py my_agent:run_agent my_dataset --evaluators accuracy,latency --max-concurrency 4

# Python (do not upload experiment results)
uv run skills/langgraph-testing-evaluation/scripts/evaluate_with_langsmith.py my_agent:run_agent my_dataset --evaluators accuracy --no-upload

# JavaScript/TypeScript
node skills/langgraph-testing-evaluation/scripts/evaluate_with_langsmith.js ./agent.ts:runAgent my_dataset --evaluators accuracy,latency --max-concurrency 4

Read the full file on GitHub · 259 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 259 lines · 99 tokens per session scan A 2d4818b80193

Subscribe to this mod's changes

langgraph-testing-evaluation is a skill published in the GitHub repository soba-labs/langchain-agent-skills (106 stars, last pushed 23d ago), licensed MIT. It adds 99 tokens to every session and 2,000 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.