From superclaude
Assesses pre-implementation confidence (≥90% required) via checks for duplicate code, architecture compliance, official docs, OSS references, and root cause identification.
How this skill is triggered — by the user, by Claude, or both
Slash command
/superclaude:confidence-checkThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Prevents wrong-direction execution by assessing confidence **BEFORE** starting implementation.
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.
npx claudepluginhub kushal9889/claude-plugins --plugin superclaudeValidates implementation plans against codebase reality, architecture, quality, risks, and conventions before execution using four parallel specialized reviewers.
Validates factual claims in code reviews, system analysis, documentation, and test reports using tools; prohibits superlatives and unverified metrics.
Applies adversarial fresh-context review to non-trivial decisions in code. Use when correctness matters more than speed, in unfamiliar code, or for high-stakes operations.