llo-feedback

Collect LLO feedback and document responses in ACE closeout files.

1|2|Updated Apr 1, 2026
One-click install
npx skills add https://github.com/jjackson/ace --skill llo-feedback
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llo-feedback
Source: https://github.com/jjackson/ace/tree/main/skills/llo-feedback
Command: npx skills add https://github.com/jjackson/ace --skill llo-feedback

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Collects and documents LLO feedback after opportunities to enable learning and improvement.

Core Features & Use Cases

  • Archetype-aware feedback prompts for atomic-visit, focus-group, and multi-stage opportunities.
  • Automated drafting of feedback requests, distribution, and monitoring for responses.
  • Structured documentation layout: ACE/<opp-name>/closeout/llo-feedback.md with explicit archetype, responses, themes, and improvement suggestions.

Quick Start

Invite LLOs to provide feedback and save the responses to the closeout folder.

Frequently Asked Questions about llo-feedback

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

FAQPage Schema
How do I collect structured feedback after an opportunity closeout?▼

Structured feedback collection uses archetype-aware prompts to request input after an opportunity closeout, storing responses in a markdown file with sections for archetype, responses, themes, and improvement suggestions.

What is an archetype-aware debrief prompt for post-opp reviews?▼

An archetype-aware debrief prompt tailors feedback requests to specific opportunity types like atomic-visit, focus-group, or multi-stage, ensuring questions match the context of the post-opp review.

Can I automate feedback documentation for multi-stage opportunities?▼

Yes, feedback documentation automates drafting requests, distribution, and monitoring for responses across multi-stage opportunities, saving structured output to the closeout folder.

How do I document LLO feedback themes and improvement suggestions?▼

LLO feedback themes and improvement suggestions are documented in a structured markdown file within the closeout directory, organizing responses by archetype for clear learning and improvement tracking.

Does this feedback process work for focus-group and atomic-visit archetypes?▼

Yes, the feedback process applies to focus-group and atomic-visit archetypes, using tailored prompts to gather relevant responses and store them in the closeout documentation.

What is the best way to structure opportunity debriefs for learning and improvement?▼

The best way to structure opportunity debriefs is using archetype-aware prompts that capture responses, identify themes, and suggest improvements, all stored in a dedicated closeout markdown file.