Log project observations, failures, and successes into structured JSONL files.
npx skills add https://github.com/ambrovia/agent-skills-pipeline --skill retro-ambrovia
Please help me install this Agent Skill. Skill: retro Source: https://github.com/ambrovia/agent-skills-pipeline/tree/main/skills/retro Command: npx skills add https://github.com/ambrovia/agent-skills-pipeline --skill retro-ambrovia
This skill solves the issue of institutional amnesia in software development by systematically recording successes, frictions, and failures at the end of every work package.
Run the retro skill for the current work package to log observations and identify potential process improvements.
High-intent search queries and answers about installing and using this skill.
Run a retro on the current work package to log observations and identify potential process improvements. It systematically records successes, frictions, and failures by applying to all pipeline phases to track technical debt and workflow friction.
Track technical debt and workflow friction by logging project observations into structured JSONL files. This feeds data into the pipeline's compounding engine to identify recurring patterns and process bottlenecks across all pipeline phases.
Yes, generating actionable post-mortem data requires access to version control history, pipeline logs, and work package artifacts. These inputs allow the skill to accurately track technical debt, workflow friction, and team performance metrics.
Structured observation logging avoids merge conflicts by writing project outcomes into per-work-package JSONL files. This isolates retrospective entries, allowing parallel documentation of successes and frictions without overwriting shared team files.
Use structured JSONL files for continuous process improvement at the end of every work package. This timing systematically records technical hurdles and institutional knowledge, feeding data into the pipeline to prevent recurring errors.
k97Generate structured release notes from git commit history and pull request data.
strawgateAnalyze agent-user conversation transcripts to identify skill gaps and failure patterns.
mylukinGenerate ARCHITECTURE.md documentation from codebase analysis.
bmdhodlQuery Azure resources and propose confirmed changes via Azure CLI.
