Evaluate AI coding agents against skill framework checklists and tool usage.
npx skills add https://github.com/forwardimpact/monorepo --skill eval-forwardimpact
Please help me install this Agent Skill. Skill: eval Source: https://github.com/forwardimpact/monorepo/tree/main/.claude/skills/eval Command: npx skills add https://github.com/forwardimpact/monorepo --skill eval-forwardimpact
This Skill provides a structured process for evaluating how well AI coding agents adhere to predefined skill frameworks, ensuring they perform tasks as intended and identifying areas for improvement.
Use the eval skill to evaluate the 'software_engineering' agent for the 'forward_deployed' track.
High-intent search queries and answers about installing and using this skill.
To evaluate AI coding agents against a skill framework, you need to analyze their execution against defined checklists, tool usage, and workflow instructions. This process requires detailed observation of agent interactions and comparison against skill definitions.
Skill adherence assessment is the process of verifying if AI coding agents correctly interpret and execute instructions from predefined skill files. It ensures agents perform tasks as intended and identifies specific deviations from expected behavior or incorrect tool usage.
You test if an AI agent followed engineering checklists correctly by systematically checking its execution against defined practices, verifying it used the correct libraries, and ensuring it completed all required steps before handing off to the next stage.
Yes, you can use this evaluation process for debugging agent workflow deviations. It pinpoints specific deviations from expected behavior, checklist failures, or incorrect tool usage, making it applicable for quality assurance in agent development and skill refinement.
To check AI agent performance in software engineering tasks, you need a defined skill framework and detailed observation of agent interactions. The evaluation compares these interactions against skill definitions to ensure consistent AI performance.
VjayRamDefine DSPy signatures and modules with deterministic evaluation across splits.
marinvchDraft, evaluate, and iterate on AI skills with structured evals.
modu-aiAutomate end-to-end development workflows with TDD, debugging, and code review.
TeiNamIntegrate AI agents into engineering workflows for code generation and review.
