build-eval
CommunityBuild rigorous evals for LLM agents and prompts.
Authoryzavyas
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill provides a structured framework to design, validate, and compare evaluations for LLM agents, multi-agent systems, skills, MCP servers, and prompts, reducing ambiguity in measurement and alignment.
Core Features & Use Cases
- Support for end-to-end evaluation metrics (TaskCompletion, ToolCorrectness, pass@k, iterative metrics)
- Frameworks integration: DeepEval, Braintrust, RAGAS, Promptfoo for flexible scoring
- Use cases include: validating agent coordination, benchmarking MCP server reliability, and developing reusable eval templates.
Quick Start
Run a baseline evaluation harness against your codebase by assembling a dataset of test cases, choosing a framework, and executing the evaluator. For example: create a dataset with agent tasks, select DeepEval metrics, and run your evaluation harness.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: build-eval Download link: https://github.com/yzavyas/claude-1337/archive/main.zip#build-eval Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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