evaluate-issue

Evaluate enriched GitHub issues to keep, complete, or split them.

11|Updated Dec 28, 2024
One-click install
npx skills add https://github.com/wadvanced/aurora_uix --skill evaluate-issue
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: evaluate-issue
Source: https://github.com/wadvanced/aurora_uix/tree/main/.claude/skills/evaluate-issue
Command: npx skills add https://github.com/wadvanced/aurora_uix --skill evaluate-issue

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns an already-enriched GitHub issue into a clear decision on whether the work is correctly sized for a single coding pass, should be marked completed, or needs to be split into smaller child issues.

Core Features & Use Cases

  • Completion & progress detection: Determines whether the issue is completed, partially done, or fresh by inspecting the enriched spec and review-gaps markers.
  • Remaining-work slicing: For partially completed issues, focuses evaluation only on the unticked acceptance criteria and the files they implicate, avoiding re-evaluating already-done work.
  • Evidence-backed sizing & model tier recommendation: Produces a file/spread-driven assessment and recommends a model tier for KEEP decisions, or proposes split strategies when oversized/complex.

Quick Start

Evaluate an already-enriched issue by asking the AI to run evaluate-issue on issue number N, after confirming the issue body already includes the enriched-spec marker block.

Frequently Asked Questions about evaluate-issue

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

FAQPage Schema
How do I decide whether to split or keep a GitHub issue for a single coding pass?▼

Evaluate an enriched GitHub issue to decide whether to keep it for a single implementation pass, mark it completed, or recommend splitting it into smaller children based on remaining scope. The assessment produces evidence-backed sizing and model tier recommendations.

How does issue evaluation handle partially completed work on GitHub?▼

Issue evaluation for partially completed work focuses only on unticked acceptance criteria and their implicated files. This remaining-work slicing avoids re-evaluating already done work by inspecting enriched specs and review-gaps markers to determine completion status.

What prerequisites are required before evaluating an issue for task sizing?▼

Evaluating an issue requires the GitHub issue body to already include an enriched-spec marker block. The Skill enforces this strict precondition and re-reads the issue via GitHub issue view and comments before applying file and layer driven tiering.

Does the issue evaluation process recommend an AI model tier for implementation?▼

Yes, the issue evaluation produces an evidence-backed file and spread-driven assessment that recommends a specific model tier for KEEP decisions. When an issue is oversized or complex, it proposes split strategies instead of a model recommendation.

Can I evaluate large cross-layer issues that have already been enriched?▼

Yes, this issue evaluation applies to scenarios where issues are already decorated with enriched-spec and optional review-gaps sections, including large, cross-layer, or partially completed work. It performs an idempotent assessment and persists the results directly to the issue body.