muse

Name: muse
Availability: InStock
Author: iroh4-labs

Generate markdown retrospectives summarizing archived mumei features and their metrics.

2|1|Updated May 2, 2026

Search Tags:#code review #markdown #retrospective #feature management #mumei

Ready to run

npx skills add https://github.com/iroh4-labs/mumei --skill muse-iroh4-labs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: muse
Source: https://github.com/iroh4-labs/mumei/tree/main/skills/muse
Command: npx skills add https://github.com/iroh4-labs/mumei --skill muse-iroh4-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the generation of retrospective markdown documents for archived mumei features, ensuring that institutional knowledge is preserved without manual effort.

Core Features & Use Cases

Automated Retrospective Generation: Automatically creates a markdown document summarizing the development process and key metrics for an archived feature.
Feature-specific Metrics: Includes AC count, Wave count, review iter counts, fix-spiral detection, token cost, cache hit rate, and hook firing breakdown.
User Triggered: Requires user invocation after shelving a feature with the command /mumei:muse <feature>.

Quick Start

Generate a retrospective for the feature 'new-feature' by running the command: /mumei:muse new-feature

Frequently Asked Questions about muse

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

FAQPage Schema

How do I automate feature retrospectives for archived mumei features?▼

Automate feature retrospectives by running the `/mumei:muse <feature>` command, which generates a markdown document summarizing development metrics and the process for the archived mumei feature.

What metrics are included in a generated mumei retrospective markdown?▼

A mumei retrospective includes AC count, Wave count, review iteration counts, fix-spiral detection, token cost, cache hit rate, and hook firing breakdown to summarize the feature development process.

When do I need to generate a retrospective markdown document for a feature?▼

You need to generate a retrospective markdown document after shelving or archiving a mumei feature to preserve institutional knowledge without manual effort.

Do I need specific log files to create a feature retrospective?▼

Yes, creating a feature retrospective requires access to the specific feature directories and their associated log files to accurately calculate metrics like token cost and cache hit rate.

Can I trigger retrospective generation automatically instead of using a command?▼

No, retrospective generation is strictly user-triggered and requires manual invocation of the `/mumei:muse <feature>` command after a feature has been shelved.

What is the best way to document development metrics for shelved features?▼

The best way to document development metrics is using an automated retrospective tool that parses feature logs to output a structured markdown summary of review iterations and token costs.