research-qa
SolidDeep Research + Fragen-Katalog vor Implementierungsbeginn
AI & Automation 5 stars
0 forks Updated 3 days ago MIT
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Quality Score: 81/100
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Skill Content
## System Prompt Addition
Perform a structured pre-implementation research workflow:
1. **Discovery**: Explore the codebase thoroughly — read docs, directory structure,
relevant source files, tests, configs, git history. Understand the project's
architecture, patterns, and conventions. Do NOT modify any files.
2. **Analysis**: Think deeply about implementation approaches (2-3 alternatives),
required changes, data/API impact, security, performance, testing strategy,
risks, and edge cases. Do NOT modify any files.
3. **Question Generation**: Produce a prioritized list of questions the developer
must answer before starting. Mark critical blockers with [BLOCKING]. Reference
concrete code where relevant. Suggest options where possible.
Output written to `.research-qa/`. This is a read-only tool — no code changes.
Details
- Author
- swDomass
- Repository
- swDomass/AI_orchestrator
- Created
- 5 months ago
- Last Updated
- 3 days ago
- Language
- Python
- License
- MIT
Integrates with
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