aim-manager-guide

Compare README goals against origin/main and generate coordinator handoff signals.

4|1|Updated Apr 18, 2026
One-click install
npx skills add https://github.com/zccz14/AIM --skill aim-manager-guide
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aim-manager-guide
Source: https://github.com/zccz14/AIM/tree/main/.agents/skills/aim-manager-guide
Command: npx skills add https://github.com/zccz14/AIM --skill aim-manager-guide

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The AIM Manager guide skill helps teams evaluate how README goals align with the latest baseline (origin/main), define iteration directions, and prepare Coordinator-consumable evaluation signals without creating tasks or executing work.

Core Features & Use Cases

  • Define and maintain evaluation dimensions (dimensions) and implement quantitative/qualitative criteria for milestone-based reviews.
  • Produce coherent coordinator handoff content that distills gaps, risks, and open questions for task planning, without touching the Task Pool directly.
  • Aggregate observable data, issues, and historical evaluations to support decision-making and iteration planning.

Quick Start

Provide evaluation signals by comparing README goals to the latest origin/main baseline and generate dimension definitions and a coordinator handoff without creating tasks.

Frequently Asked Questions about aim-manager-guide

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

FAQPage Schema
How do I align README goals with the latest origin/main baseline for iteration planning?

To align README goals with the origin/main baseline, you identify and communicate gaps between them to guide iteration direction. This process produces evaluation signals for task pool planning without directly modifying code or documentation.

What is a coordinator handoff signal in milestone-based reviews?

A coordinator handoff signal is a packaged evaluation output that distills gaps, risks, and open questions from baseline comparisons. It provides coherent, consumable input for task pool planning without creating tasks or executing work directly.

How do I define evaluation dimensions and concrete criteria for project baseline reviews?

You define evaluation dimensions by comparing README goals against the latest origin/main baseline and establishing quantitative or qualitative criteria. This aggregates observable data, issues, and historical evaluations to support milestone-based decision-making.

Can I use this approach to automatically create tasks in the Task Pool?

No, you cannot automatically create tasks in the Task Pool. This approach specifically avoids direct task creation and runtime state modification, focusing solely on packaging evaluation signals for a coordinator to consume later.

What's the best way to aggregate observable data and historical evaluations for iteration planning?

The best way to aggregate observable data and historical evaluations is to compare README goals against the origin/main baseline. This identifies gaps and open questions, packaging them into a coordinator-handoff signal to guide task planning.