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DVNghiem
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patch-trust-score

Evaluate AI-generated patches with a 0–100 trust score and verdict.

20|3|Updated Apr 30, 2026
Search Tags:#automation#verification#safety#review#trust#patch#gate
One-click install
npx skills add https://github.com/DVNghiem/FlowDeck --skill patch-trust-score
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: patch-trust-score
Source: https://github.com/DVNghiem/FlowDeck/tree/main/src/skills/patch-trust-score
Command: npx skills add https://github.com/DVNghiem/FlowDeck --skill patch-trust-score

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Patch Trust Score assesses AI-generated changes to assign a safety-rated verdict, preventing unsafe patches from being auto-applied.

Core Features & Use Cases

  • Automated risk scoring for each patch with a clear verdict (safe, review-required, high-risk)
  • Gatekeeping in CI to route changes through review or block unsafe edits
  • Auditability with signals and decision logs for governance and compliance

Quick Start

Provide a patch description and content to be applied; the skill will compute a risk score and verdict.

Frequently Asked Questions about patch-trust-score

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate safety scoring for AI-generated code patches?▼

Automated safety scoring evaluates AI-generated code patches by analyzing prior failure history, scanning high-risk keywords, and checking constraints to compute a 0–100 trust score. This score determines whether the patch is safe, requires review, or is high-risk.

How does automated gatekeeping work for AI patches in CI pipelines?▼

Automated gatekeeping for AI patches in CI pipelines works by computing a trust score and routing changes based on a safety verdict. Patches are routed for auto-apply, flagged for warning, or blocked from merging depending on the computed risk level.

Can I use a trust score to block unsafe configuration changes?▼

Yes, you can use a trust score to block unsafe configuration changes. The evaluation assigns a verdict to patches touching critical files, preventing high-risk edits from being auto-applied and routing them to a blocked or review-required state.

What is the best way to audit AI patch decisions for compliance?▼

The best way to audit AI patch decisions for compliance is to use a trust score system that generates decision logs. The evaluation process records risk signals and safety verdicts, providing an auditable trail for governance of auto-applied or blocked changes.

When should I not auto-apply AI-generated code edits?▼

You should not auto-apply AI-generated code edits when the patch touches critical files or contains high-risk keywords. The trust score evaluation flags these changes with a high-risk or review-required verdict, preventing unsafe automatic application.

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