Evaluate confidence in code, plans, or bug analyses with multi-signal scoring and rule checks.
npx skills add https://github.com/mthines/agent-skills --skill confidence
Please help me install this Agent Skill. Skill: confidence Source: https://github.com/mthines/agent-skills/tree/main/skills/confidence Command: npx skills add https://github.com/mthines/agent-skills --skill confidence
It helps developers and reviewers rapidly evaluate the confidence level in code correctness and completeness, streamlining quality assurance processes.
Ask the AI to check the confidence level of your current code review plan to get an instant assessment.
High-intent search queries and answers about installing and using this skill.
To assess code confidence levels before deployment, use an automated evaluation skill that applies multi-signal scoring and rule checks to rate how thoroughly your work meets requirements.
Yes, you can use automated confidence validation for bug analysis. The evaluation mechanism rates the correctness and completeness of your bug analysis using multi-signal scoring and deterministic rule checks.
Multi-signal evaluation for code review works by combining AI judgment with deterministic rule checks. This dual approach ensures thorough validation and generates quantifiable confidence metrics for the assessed code or plan.
The best way to automate quality gate checks is to implement a confidence evaluation skill that runs automatic assessments before committing code. This provides rapid validation and quantifiable confidence metrics for your delivery.
No, you do not need external dependencies to run automatic code evaluation. The skill operates independently with scripts and references to provide multi-signal scoring and validation without requiring external libraries.
You should avoid using automated confidence scoring when a task requires subjective validation that cannot be measured by deterministic rule checks, as the evaluation relies on multi-signal scoring to ensure correctness and completeness.
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