- 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
1.7 KiB
YAML
42 lines
1.7 KiB
YAML
# Eval: launch-strategy
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# Source: marketing-skill/launch-strategy/SKILL.md
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description: "Evaluate launch strategy 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://../../marketing-skill/launch-strategy/SKILL.md
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task: "Plan a Product Hunt launch for an AI writing assistant. We have 2,000 email subscribers, 500 Twitter followers, and the product has been in beta for 3 months with 200 active users. Budget: $0 (bootstrapped)."
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assert:
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- type: llm-rubric
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value: "Response includes a phased timeline (pre-launch, launch day, post-launch) with specific actions"
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- type: llm-rubric
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value: "Strategy leverages existing assets (2K email list, 200 beta users, Twitter) concretely"
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- type: llm-rubric
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value: "Response includes Product Hunt-specific tactics (hunter selection, timing, asset preparation)"
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- vars:
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skill_content: file://../../marketing-skill/launch-strategy/SKILL.md
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task: "We're launching a major feature update (AI-powered analytics) to our existing SaaS product with 5,000 paying customers. How should we announce it to maximize adoption and upsell opportunities?"
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assert:
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- type: llm-rubric
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value: "Response distinguishes between existing customer communication and new user acquisition"
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- type: llm-rubric
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value: "Response includes specific channels and messaging for the announcement"
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