verify-loop-delivery

Audit AI agent task outputs against project contracts and checklists.

3|Updated Jun 27, 2026

Search Tags:#automation #verification #governance #quality-assurance #code-review #agent-loops

Ready to run

npx skills add https://github.com/XinAloha/skills --skill verify-loop-delivery

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: verify-loop-delivery
Source: https://github.com/XinAloha/skills/tree/main/loop-engineering/verify-loop-delivery
Command: npx skills add https://github.com/XinAloha/skills --skill verify-loop-delivery

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves the "self-approval" trap in AI agent loops, where agents tend to overestimate their own success, leading to hidden technical debt and failed deployments. It enforces a strict separation of duties between the implementer and the verifier.

Core Features & Use Cases

Independent Verification: Ensures the verifier is a distinct entity from the implementer, preventing bias.
Evidence-Based Auditing: Requires verifiable proof (test results, logs, static analysis) rather than subjective claims of completion.
Use Case: Use this during a complex refactoring loop to ensure that the code produced by an agent meets all project standards and passes all regression tests before it is ever merged into the main branch.

Quick Start

Use the verify-loop-delivery skill to independently audit the current implementation against the project contract and checklist.

Frequently Asked Questions about verify-loop-delivery

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

FAQPage Schema

How do I stop AI agents from self-approving their code in automated loops?▼

To prevent AI agent self-approval, you need independent verification that enforces a strict separation of duties between the implementer and the verifier, requiring evidence-based auditing of task outputs.

How do I verify AI agent task outputs against project contracts?▼

Verify AI agent task outputs by independently auditing implementation evidence, such as test results and logs, against predefined project contracts and checklists to ensure objective pass, reject, or escalate decisions.

What is evidence-based auditing for automated software engineering workflows?▼

Evidence-based auditing for automated software engineering workflows is the process of requiring verifiable proof like static analysis and regression test results rather than subjective claims to validate code quality and governance.

Does independent verification work for complex refactoring loops before merging to the main branch?▼

Yes, applying independent verification during complex refactoring loops ensures that agent-generated code meets all project standards and passes regression tests before it is merged into the main branch.

Why does my AI agent overestimate task success and cause hidden technical debt?▼

AI agents overestimate task success and cause hidden technical debt due to the self-approval trap, which is solved by enforcing a strict separation of duties and objective evidence-based checks in the loop.

When do I need independent verification in AI agent loops?▼

You need independent verification in AI agent loops when your automated software engineering workflows require strict quality control, non-repudiation, verifiable testing, and objective pass or reject decision-making.