Does it work with any programming language?

Yes, it uses universal search patterns and documentation lookups that are language-agnostic, making it suitable for any software project.

Why does this skill require a 90% confidence score?

The 90% threshold ensures maximum precision, preventing the AI from proceeding with 'hallucinated' solutions or redundant implementations that could introduce technical debt.

What happens if the confidence score is low?

If the score is below 70%, the skill instructs Claude to stop and request more context or clarification from the user rather than guessing.

How does Confidence Check save on token usage?

By spending 100-200 tokens on a preliminary check, you avoid spending 5,000+ tokens on an incorrect implementation that would eventually need to be reverted or fixed.

Confidence Check

Name: Confidence Check
Author: swcstudiospace

byswcstudiospace

0•

生産性とワークフロー

Validates implementation readiness through a rigorous 90% confidence threshold to prevent architectural drift and redundant code.

Confidence Check is a strategic pre-implementation safeguard designed for Claude Code to ensure that every development task is well-founded before execution begins. By evaluating tasks against five critical criteria—duplicate detection, architectural compliance, official documentation verification, open-source references, and root cause identification—it enforces a strict 90% confidence score requirement. This proactive approach saves significant token costs and developer time by preventing 'wrong-direction' work and ensuring that all changes align perfectly with existing project patterns and verified technical standards.

主な機能

01Automated duplicate implementation search to prevent redundant code

020 GitHub stars

03Architectural alignment verification against project standards like CLAUDE.md

04Root cause analysis to ensure fixes address the core problem, not just symptoms

05Quantitative readiness scoring (0-1.0) with a 90% success threshold

06Real-time documentation and OSS reference validation using MCP tools

ユースケース

01Preventing redundant utility functions in large, multi-contributor codebases

02Ensuring new features adhere to specific tech stacks like Supabase or UV

03Verifying complex bug fixes before modifying core library logic

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add swcstudiospace/superggc-toolkit confidence-check

For use in Claude.ai and ChatGPT

主な機能

01Automated duplicate implementation search to prevent redundant code

020 GitHub stars

03Architectural alignment verification against project standards like CLAUDE.md

04Root cause analysis to ensure fixes address the core problem, not just symptoms

05Quantitative readiness scoring (0-1.0) with a 90% success threshold

06Real-time documentation and OSS reference validation using MCP tools

ユースケース

01Preventing redundant utility functions in large, multi-contributor codebases

02Ensuring new features adhere to specific tech stacks like Supabase or UV

03Verifying complex bug fixes before modifying core library logic

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add swcstudiospace/superggc-toolkit confidence-check

For use in Claude.ai and ChatGPT