Classify task outcomes from Git history and PR evidence into retrospective categories.
npx skills add https://github.com/nebinfra/nebcore-ai-skills --skill neb-retro
Please help me install this Agent Skill. Skill: neb-retro Source: https://github.com/nebinfra/nebcore-ai-skills/tree/main/neb-retro Command: npx skills add https://github.com/nebinfra/nebcore-ai-skills --skill neb-retro
The Initiative Retrospective helps teams analyze completed projects, extract patterns from task reports, identify failure modes, and capture durable learnings by updating a centralized MEMORY repository.
Provide the initiative name to begin the retrospective and follow the workflow to generate findings.
High-intent search queries and answers about installing and using this skill.
Extracting learning patterns from project execution histories involves gathering objective evidence like Git history and PR outcomes, classifying task outcomes into success or failure modes, and generating actionable learnings.
The best way to run a retrospective on completed tasks is to follow a guided workflow that collects objective artifacts, classifies them into clean success, retry, blocked, or failed categories, and produces structured findings.
Yes, Git history and PR outcomes provide objective execution evidence used to classify task outcomes into failure modes like blocked, failed, or abandoned, which helps identify patterns for future planning.
Task outcomes for root-cause analysis are classified into clean success, retry success, blocked then resolved, failed or abandoned, and gap-spawned categories based on objective execution evidence gathered from project artifacts.
A project retrospective updates institutional memory by capturing durable learnings from classified task outcomes and synchronizing them as memory updates to a centralized repository, ensuring institutional knowledge remains current.
To start an initiative retrospective, you need to provide the initiative name, which locates the relevant project artifacts and defines the tasks to review before gathering execution evidence and generating actionable learnings.
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