Generate a retrospective markdown document for archived mumei features from cost-log.jsonl.
npx skills add https://github.com/iroha924/mumei --skill muse-iroha924
Please help me install this Agent Skill. Skill: muse Source: https://github.com/iroha924/mumei/tree/main/skills/muse Command: npx skills add https://github.com/iroha924/mumei --skill muse-iroha924
This Skill automates the generation of retrospective markdowns for archived mumei features, ensuring team knowledge retention and enhancing feature evaluation.
/mumei:muse <feature> creates a comprehensive muse.md file that can be reviewed for future reference.Generate a retrospective markdown for the feature 'feature-name' by running: /mumei:muse feature-name
High-intent search queries and answers about installing and using this skill.
To generate a feature retrospective in markdown, run the `/mumei:muse <feature-name>` command. This creates a comprehensive `muse.md` file summarizing the archived feature's metrics, patterns, and lessons learned for future reference.
Automating a feature retrospective requires access to feature-related documents, including requirements, design, tasks, spec-reviews, reviews, and the `cost-log.jsonl` file. These sources provide the data needed to analyze and summarize the archived feature.
You should generate a retrospective markdown immediately after a feature is shelved or archived. This ensures team knowledge retention by documenting metrics, patterns, and lessons learned while the feature context is still fresh.
Yes, generating the retrospective markdown requires a bash environment and access to the `CLAUDE_PLUGIN_ROOT`. These dependencies support the scripts that analyze feature documents and the cost-log.jsonl file to produce the output.
No, the `cost-log.jsonl` file is a required input for analysis. Without it, the tool cannot generate a comprehensive retrospective markdown containing the expected metrics, patterns, and lessons learned for the archived feature.
The best way to summarize metrics and lessons learned is to automate the process using a retrospective tool that reads multiple project documents. This generates a structured markdown file capturing patterns and cost data for future evaluation.
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