Confidence Check Skill
Purpose
Prevents wrong-direction execution by assessing confidence BEFORE starting implementation.
Requirement: ≥90% confidence to proceed with implementation.
Test Results (2025-10-21):
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Precision: 1.000 (no false positives)
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Recall: 1.000 (no false negatives)
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8/8 test cases passed
When to Use
Use this skill BEFORE implementing any task to ensure:
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No duplicate implementations exist
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Architecture compliance verified
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Official documentation reviewed
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Working OSS implementations found
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Root cause properly identified
Confidence Assessment Criteria
Calculate confidence score (0.0 - 1.0) based on 5 checks:
- No Duplicate Implementations? (25%)
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
- Architecture Compliance? (25%)
Check: Verify tech stack alignment
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Read CLAUDE.md , PLANNING.md
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Confirm existing patterns used
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Avoid reinventing existing solutions
✅ Pass if uses existing tech stack (e.g., Supabase, UV, pytest) ❌ Fail if introduces new dependencies unnecessarily
- Official Documentation Verified? (20%)
Check: Review official docs before implementation
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Use Context7 MCP for official docs
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Use WebFetch for documentation URLs
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Verify API compatibility
✅ Pass if official docs reviewed ❌ Fail if relying on assumptions
- Working OSS Implementations Referenced? (15%)
Check: Find proven implementations
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Use Tavily MCP or WebSearch
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Search GitHub for examples
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Verify working code samples
✅ Pass if OSS reference found ❌ Fail if no working examples
- Root Cause Identified? (15%)
Check: Understand the actual problem
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Analyze error messages
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Check logs and stack traces
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Identify underlying issue
✅ Pass if root cause clear ❌ Fail if symptoms unclear
Confidence Score Calculation
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
Output Format
📋 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
Implementation Details
The TypeScript implementation is available in confidence.ts for reference, containing:
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confidenceCheck(context)
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Main assessment function
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Detailed check implementations
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Context interface definitions
ROI
Token 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.