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Get Started Free →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.
.claude/skills/microck-confidence-check/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 15% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 73% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -38% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -28% | 0% |
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
bash# 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 implementationThe 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.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 14,747 | 13,100 | -11% | 1 | 1 | 0% | 2,614 | 3,015 | +15% | 0 | 0 | — |
case-02 | fail→pass | 12,585 | 12,219 | -3% | 1 | 1 | 0% | 2,084 | 2,652 | +27% | 0 | 0 | — |
case-03 | fail→pass | 10,661 | 13,376 | +25% | 1 | 1 | 0% | 1,723 | 2,978 | +73% | 0 | 0 | — |
case-04 | pass→pass | 11,362 | 4,995 | -56% | 1 | 1 | 0% | 1,904 | 1,654 | -13% | 0 | 0 | — |
case-05 | pass→pass | 7,521 | 4,780 | -36% | 1 | 1 | 0% | 1,370 | 1,558 | +14% | 0 | 0 | — |
case-06 | fail→pass | 20,037 | 7,279 | -64% | 1 | 1 | 0% | 3,332 | 2,055 | -38% | 0 | 0 | — |
case-07 | fail→pass | 15,991 | 6,776 | -58% | 1 | 1 | 0% | 2,660 | 1,928 | -28% | 0 | 0 | — |
case-08 | fail→pass | 16,185 | 6,679 | -59% | 1 | 1 | 0% | 2,499 | 1,903 | -24% | 0 | 0 | — |
case-09 | fail→pass | 12,986 | 3,647 | -72% | 1 | 1 | 0% | 1,939 | 1,372 | -29% | 0 | 0 | — |
case-10 | fail→pass | 8,201 | 2,361 | -71% | 1 | 1 | 0% | 1,224 | 1,082 | -12% | 0 | 0 | — |
case-11 | fail→pass | 11,502 | 5,226 | -55% | 1 | 1 | 0% | 1,847 | 1,603 | -13% | 0 | 0 | — |
case-12 | pass→pass | 13,984 | 7,038 | -50% | 1 | 1 | 0% | 2,376 | 1,959 | -18% | 0 | 0 | — |
case-13 | pass→pass | 9,788 | 4,577 | -53% | 1 | 1 | 0% | 1,468 | 1,526 | +4% | 0 | 0 | — |
case-14 | fail→pass | 10,520 | 4,114 | -61% | 1 | 1 | 0% | 1,593 | 1,455 | -9% | 0 | 0 | — |
case-15 | pass→pass | 11,512 | 5,984 | -48% | 1 | 1 | 0% | 1,749 | 1,714 | -2% | 0 | 0 | — |
case-16 | pass→pass | 4,617 | 1,822 | -61% | 1 | 1 | 0% | 720 | 1,018 | +41% | 0 | 0 | — |
case-17 | pass→pass | 3,601 | 3,294 | -9% | 1 | 1 | 0% | 728 | 1,314 | +80% | 0 | 0 | — |
case-18 | pass→pass | 11,201 | 2,542 | -77% | 1 | 1 | 0% | 1,953 | 1,089 | -44% | 0 | 0 | — |
case-19 | fail→pass | 8,842 | 2,531 | -71% | 1 | 1 | 0% | 1,418 | 1,159 | -18% | 0 | 0 | — |
case-20 | fail→fail | 9,472 | 6,733 | -29% | 1 | 1 | 0% | 1,520 | 1,374 | -10% | 0 | 0 | — |
case-21 | pass→pass | 17,945 | 12,250 | -32% | 1 | 1 | 0% | 3,060 | 2,753 | -10% | 0 | 0 | — |
case-22 | fail→fail | 6,649 | 6,637 | -0% | 1 | 1 | 0% | 1,102 | 1,853 | +68% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +50 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.