speckit-ai-self-acceptance

Evaluate AI-driven code changes against acceptance rubrics and report PASS, FAIL, or BLOCKED outcomes.

95|39|Updated Dec 15, 2025

Search Tags:#electron #cdp #ai validation #evidence collection #acceptance testing #rubric scoring

Ready to run

npx skills add https://github.com/liuminxin45/auto-podcast --skill speckit-ai-self-acceptance

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: speckit-ai-self-acceptance
Source: https://github.com/liuminxin45/auto-podcast/tree/main/.agents/spec-kit/skills/speckit-ai-self-acceptance
Command: npx skills add https://github.com/liuminxin45/auto-podcast --skill speckit-ai-self-acceptance

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill gives AI teams a consistent way to verify code changes before human acceptance, so validation is evidence-based instead of guesswork.

Core Features & Use Cases

Collects build, test, CDP, log, and runtime evidence based on the plan and selected gates.
Scores each rubric row as PASS, FAIL, BLOCKED, or N/A and records concrete blockers when they exist.
Use it after implementation to decide whether to continue to acceptance or return to fixes and revalidation.

Quick Start

Ask the AI to run the self-acceptance loop for the current change set, gather the required evidence, evaluate the rubric, and report the next workflow stage.

Frequently Asked Questions about speckit-ai-self-acceptance

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

FAQPage Schema

How do I validate AI code changes before human acceptance testing?▼

To validate AI code changes before human acceptance, run a self-acceptance loop that gathers build, test, CDP, and runtime evidence to score against a rubric. This evaluates changes systematically and returns PASS, FAIL, or BLOCKED outcomes.

What is rubric-based evidence collection for AI validation?▼

Rubric-based evidence collection for AI validation is the process of gathering build, test, CDP, log, and runtime data to score each rubric row. It records concrete blockers and produces PASS, FAIL, BLOCKED, or N/A outcomes to guide stage continuation decisions.

How do I collect CDP and runtime evidence for acceptance testing?▼

To collect CDP and runtime evidence for acceptance testing, trigger the self-acceptance loop for your current change set. The process automatically gathers logs, runtime data, and Chrome DevTools Protocol evidence based on your plan and selected gates.

Does spec-kit self-acceptance work with Electron projects?▼

Spec-kit self-acceptance works with Electron projects by gathering CDP evidence and runtime logs to evaluate changes. It requires a plan, acceptance rubric, gate evidence, and validation records to produce PASS, FAIL, or BLOCKED outcomes.

When should I use automated acceptance testing for AI-driven code changes?▼

You should use automated acceptance testing for AI-driven code changes immediately after implementation to decide workflow continuation. It determines whether to proceed to human acceptance or return to fixes and revalidation based on evidence.

What happens if a rubric row fails during AI self-acceptance?▼

If a rubric row fails during AI self-acceptance, the evaluation records a FAIL or BLOCKED outcome and reports concrete blockers. This directs the workflow to return to fixes and revalidation rather than continuing to the next stage.