75fa9de2bb
- Add eval/ directory with 10 pilot skill eval configs - Add GitHub Action (skill-eval.yml) for automated eval on PR - Add generate-eval-config.py script for bootstrapping new evals - Add reusable assertion helpers (skill-quality.js) - Add eval README with setup and usage docs Skills covered: copywriting, cto-advisor, seo-audit, content-strategy, aws-solution-architect, agile-product-owner, senior-frontend, senior-security, mcp-server-builder, launch-strategy CI integration: - Triggers on PR to dev when SKILL.md files change - Detects which skills changed and runs only those evals - Posts results as PR comments (non-blocking) - Uploads full results as artifacts No existing files modified.
42 lines
1.6 KiB
YAML
42 lines
1.6 KiB
YAML
# Eval: senior-frontend (replacing frontend-design which doesn't exist as standalone)
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# Source: engineering-team/senior-frontend/SKILL.md
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description: "Evaluate senior frontend skill"
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prompts:
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- |
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You are an expert AI assistant. You have the following skill loaded:
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---BEGIN SKILL---
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{{skill_content}}
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---END SKILL---
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Now complete this task: {{task}}
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providers:
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- id: anthropic:messages:claude-sonnet-4-6
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config:
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max_tokens: 4096
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temperature: 0.7
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tests:
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- vars:
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skill_content: file://../../engineering-team/senior-frontend/SKILL.md
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task: "Build a responsive dashboard layout in React with TypeScript. It should have a sidebar navigation, a top bar with user menu, and a main content area with a grid of metric cards. Use Tailwind CSS."
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assert:
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- type: llm-rubric
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value: "Output includes actual React/TypeScript code, not just descriptions"
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- type: llm-rubric
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value: "Code uses Tailwind CSS classes for responsive design (sm:, md:, lg: breakpoints)"
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- type: llm-rubric
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value: "Component structure follows React best practices (proper component decomposition)"
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- vars:
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skill_content: file://../../engineering-team/senior-frontend/SKILL.md
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task: "Our Next.js app has a Core Web Vitals score of 45. LCP is 4.2s, CLS is 0.25, and INP is 350ms. Diagnose the likely causes and provide a fix plan."
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assert:
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- type: llm-rubric
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value: "Response addresses each specific metric (LCP, CLS, INP) with targeted fixes"
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- type: llm-rubric
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value: "Response includes Next.js-specific optimizations (Image component, dynamic imports, etc.)"
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