ai-development-guide

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Applies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend implementation choices, code smells, failures, or implementation completeness.

AI & Automation 668 stars 102 forks Updated 2 days ago MIT

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Quality Score: 91/100

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80
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Description 5%
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# AI Developer Guide - Technical Decision Criteria and Anti-pattern Collection ## Value-First Engineering Explore broadly, then converge on the lowest-lifecycle-cost solution that delivers the required user, operator, or maintainer value while keeping the system correct and maintainable. - Resolve verified problems within confirmed scope or dependencies required for the outcome; report other findings with evidence for a scope decision. - Introduce capabilities, infrastructure, abstractions, or speculative edge-case handling when a current outcome, verified constraint, or evidence-backed material risk requires them. ## Technical Anti-patterns (Red Flag Patterns) Pause the affected decision and review the design when detecting the following patterns: ### Code Quality Anti-patterns 1. **Writing similar code 3 or more times** - Violates Rule of Three 2. **Multiple responsibilities mixed in a single file** - Violates Single Responsibility Principle (SRP) 3. **Defining same content in multiple files** - Violates DRY principle 4. **Making changes without checking dependencies** - Potential for unexpected impacts 5. **Disabling code with comments** - Should use version control 6. **Error suppression** - Hiding problems creates technical debt 7. **Bypassing safety mechanisms (type systems, validation, contracts)** - Circumventing language's correctness guarantees ### Design Anti-patterns - **"Make it work for now" thinking** - Accumulation of technical debt - **Patchwork impleme...

Details

Author
shinpr
Repository
shinpr/claude-code-workflows
Created
10 months ago
Last Updated
2 days ago
Language
JavaScript
License
MIT

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