Pre-implementation confidence assessment (ā„90% required)...
Prevents wrong-direction execution by assessing confidence BEFORE starting implementation.
Requirement: ā„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
ā Pass if no duplicates found ā Fail if similar implementation exists
Check: Verify tech stack alignment
CLAUDE.md, PLANNING.mdā Pass if uses existing tech stack (e.g., Supabase, UV, pytest) ā Fail if introduces new dependencies unnecessarily
Check: Review official docs before implementation
ā Pass if official docs reviewed ā Fail if relying on assumptions
Check: Find proven implementations
ā Pass if OSS reference found ā Fail if no working examples
Check: Understand the actual problem
ā Pass if root cause clear ā Fail if symptoms unclear
Total = Check1 (25%) + Check2 (25%) + Check3 (20%) + Check4 (15%) + Check5 (15%)
If Total >= 0.90: ā
Proceed with implementation
If Total >= 0.70: ā ļø Present alternatives, ask questions
If Total < 0.70: ā STOP - Request more context
š Confidence Checks:
ā
No duplicate implementations found
ā
Uses existing tech stack
ā
Official documentation verified
ā
Working OSS implementation found
ā
Root cause identified
š Confidence: 1.00 (100%)
ā
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.