confidence-check
Requires 90% confidence score via architectural and documentation checks before starting implementation tasks.
Install
mkdir -p .claude/skills/confidence-check && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/23" && unzip -o skill.zip -d .claude/skills/confidence-check && rm skill.zipInstalls to .claude/skills/confidence-check
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Verify duplicate implementations
- →Check architecture compliance
- →Validate against official documentation
- →Reference working OSS implementations
- →Identify root causes of issues
How it works
The skill calculates a confidence score based on five specific checks to ensure readiness before starting any implementation work.
Inputs & outputs
When to use confidence-check
- →Assess implementation readiness
- →Check for duplicate code
- →Verify architecture compliance
About this skill
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):
- Precision: 1.000 (no false positives)
- Recall: 1.000 (no false negatives)
- 8/8 test cases passed
When to Use
Use this skill BEFORE implementing any task to ensure:
- No duplicate implementations exist
- Architecture compliance verified
- Official documentation reviewed
- Working OSS implementations found
- Root cause properly identified
Confidence Assessment Criteria
Calculate confidence score (0.0 - 1.0) based on 5 checks:
1. 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
2. Architecture Compliance? (25%)
Check: Verify tech stack alignment
- Read
CLAUDE.md,PLANNING.md - Confirm existing patterns used
- Avoid reinventing existing solutions
✅ Pass if uses existing tech stack (e.g., Supabase, UV, pytest) ❌ Fail if introduces new dependencies unnecessarily
3. Official Documentation Verified? (20%)
Check: Review official docs before implementation
- Use Context7 MCP for official docs
- Use WebFetch for documentation URLs
- Verify API compatibility
✅ Pass if official docs reviewed ❌ Fail if relying on assumptions
4. Working OSS Implementations Referenced? (15%)
Check: Find proven implementations
- Use Tavily MCP or WebSearch
- Search GitHub for examples
- Verify working code samples
✅ Pass if OSS reference found ❌ Fail if no working examples
5. Root Cause Identified? (15%)
Check: Understand the actual problem
- Analyze error messages
- Check logs and stack traces
- 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:
confidenceCheck(context)- Main assessment function- Detailed check implementations
- 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.
When not to use it
- →When the task is trivial and does not require architectural verification
- →When the implementation is already verified
Limitations
- →Requires a minimum confidence score of 90% to proceed
- →Dependent on the availability of official documentation and OSS references
How it compares
It forces a formal readiness assessment before execution to prevent wasted effort, unlike manual planning which may skip verification steps.
Compared to similar skills
confidence-check side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| confidence-check (this skill) | 13 | 4mo | Review | Beginner |
| specification-architect | 13 | 9mo | Review | Advanced |
| drift-analysis | 2 | 5mo | No flags | Intermediate |
| flow-next-plan-review | 1 | 2mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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