spec-writing

Solid

Create clear, testable specifications from feature descriptions with user stories, acceptance criteria, and success metrics.

Testing & QA 294 stars 26 forks Updated today MIT

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Quality Score: 95/100

Stars 20%
82
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Spec Writing ## Overview Create clear, complete, and testable specifications from natural language feature descriptions. Specifications focus on user value and business needs, avoiding implementation details. ## When To Use - Creating new feature specifications - Refining existing specifications - Writing user stories and acceptance criteria - Defining success criteria ## When NOT To Use - Generating implementation tasks - use task-planning ## Core Principles Focus on user value and business needs rather than implementation details. Avoid specifying technology choices in requirement definitions unless strictly necessary. Ensure every requirement is testable and verifiable with measurable criteria. Limit clarification markers; make informed assumptions based on industry standards and document them explicitly. ## Specification Structure ### Mandatory Sections 1. **Overview/Context**: What problem does this solve? 2. **User Scenarios**: Who uses it and how? 3. **Functional Requirements**: What must it do? 4. **Success Criteria**: How do we know it works? ### Optional Sections - Success Criteria (when performance/security critical) - Edge Cases (when special handling needed) - Dependencies (when external systems involved) - Assumptions (when decisions made with incomplete info) **See**: `modules/specification-structure.md` for detailed templates and guidelines ## Quality Checklist - [ ] No implementation details present - [ ] Requirements are testable and unambigu...

Details

Author
athola
Repository
athola/claude-night-market
Created
6 months ago
Last Updated
today
Language
Python
License
MIT

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