How does this skill save tokens?

By spending a few hundred tokens on a pre-check, you avoid generating thousands of tokens of incorrect or redundant code that would later need to be refactored or deleted.

Why do I need a 90% confidence score?

A high threshold ensures that the AI has fully understood the context and verified all dependencies, preventing 'wrong-direction' work that wastes time and tokens.

Does it search my local codebase?

Yes, it uses tools like Grep and Glob to scan your existing files for duplicate functionality and to ensure alignment with your current architectural patterns.

What happens if the confidence score is below 70%?

The skill will trigger a stop command, requesting more context or documentation from the user rather than attempting an implementation that is likely to fail.

Confidence Check

Name: Confidence Check
Author: Microck

byMicrock

•

Deployment & DevOps

Evaluates implementation readiness through a rigorous 90% confidence threshold to prevent redundant or architecturally misaligned development.

The Confidence Check skill acts as a critical guardrail for AI-driven development by assessing five key technical criteria before any code is written. By verifying architecture compliance, searching for existing duplicate implementations, and cross-referencing official documentation and open-source patterns, it ensures that Claude proceeds only when there is a 90% or higher probability of success. This preemptive assessment drastically reduces hallucination risks and token wastage by identifying root causes and potential blockers before they become costly implementation errors.

Key Features

01Calculates a weighted confidence score (0.0 - 1.0) based on five critical success factors

02Identifies underlying root causes to ensure developers solve problems, not just symptoms

03Cross-references implementation plans with official documentation and proven open-source examples

0481 GitHub stars

05Performs automated duplicate checks to prevent redundant code across the repository

06Verifies alignment with project architecture, CLAUDE.md guidelines, and existing tech stacks

Use Cases

01Before starting a major refactor or new feature implementation to ensure architectural consistency

02During bug fixing to confirm the root cause is understood before applying a patch

03When exploring new libraries to verify compatibility and reference proven community patterns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills confidence-check

For use in Claude.ai and ChatGPT

Download Skill