Pre-implementation confidence assessment (≥90% required). Use before starting any implementation to verify readiness with duplicate check, architecture compliance, official docs verification, OSS references, and root cause identification.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Prevents wrong-direction execution by assessing confidence BEFORE starting implementation.
Requirement: ≥90% confidence to proceed with implementation.
Test Results (2025-10-21):
Use this skill BEFORE implementing any task to ensure:
Calculate confidence score (0.0 - 1.0) based on 5 checks:
Check: Search codebase for existing functionality
# Use Grep to search for similar functions
# Use Glob to find related modules
✅ Pass if no duplicates found ❌ Fail if similar implementation exists
Check: Verify tech stack alignment
CLAUDE.md, PLANNING.md✅ Pass if uses existing tech stack (e.g., Supabase, UV, pytest) ❌ Fail if introduces new dependencies unnecessarily
Check: Review official docs before implementation
✅ Pass if official docs reviewed ❌ Fail if relying on assumptions
Check: Find proven implementations
✅ Pass if OSS reference found ❌ Fail if no working examples
Check: Understand the actual problem
✅ Pass if root cause clear ❌ Fail if symptoms unclear
Total = Check1 (25%) + Check2 (25%) + Check3 (20%) + Check4 (15%) + Check5 (15%)
If Total >= 0.90: ✅ Proceed with implementation
If Total >= 0.70: ⚠️ Present alternatives, ask questions
If Total < 0.70: ❌ STOP - Request more context
📋 Confidence Checks:
✅ No duplicate implementations found
✅ Uses existing tech stack
✅ Official documentation verified
✅ Working OSS implementation found
✅ Root cause identified
📊 Confidence: 1.00 (100%)
✅ High confidence - Proceeding to implementation
The TypeScript implementation is available in confidence.ts for reference, containing:
confidenceCheck(context) - Main assessment functionToken Savings: Spend 100-200 tokens on confidence check to save 5,000-50,000 tokens on wrong-direction work.
Success Rate: 100% precision and recall in production testing.
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