Analyze completed development cycles and incidents to extract lessons and action items.
npx skills add https://github.com/lalulali/vespyr --skill retro-lalulali
Please help me install this Agent Skill. Skill: retro Source: https://github.com/lalulali/vespyr/tree/main/.agents/skills/retro Command: npx skills add https://github.com/lalulali/vespyr --skill retro-lalulali
This Skill helps teams learn from completed development cycles, incidents, and launches so they can improve estimates, processes, product quality, and shared knowledge instead of repeating the same mistakes.
Use the retro skill to review the last release cycle, summarize what changed, and produce actionable improvements for the next iteration.
High-intent search queries and answers about installing and using this skill.
A blameless retrospective analyzes completed development cycles and incidents through structured evidence gathering and multi-role review. It extracts lessons without assigning blame, producing owned action items and memory updates to improve the next iteration.
Extracting actionable improvements from a launch review involves collecting quantitative and qualitative evidence from delivery and QA. Cross-functional analysis synthesizes these findings into owned action items that feed directly into your next planning cycle.
Cross-functional analysis during a cycle review examines execution, process, product, and architecture from multiple agent perspectives. This multi-role approach ensures comprehensive evaluation of the development cycle to calibrate processes and validate product quality.
Incident analysis can update team memory by extracting lessons from post-incident reviews. It synthesizes findings into memory updates and traceable action-item outputs, preventing the team from repeating the same process or architecture mistakes.
Process calibration and architecture follow-up require structured evidence gathering from delivery, QA, launches, and incident follow-up. Both quantitative metrics and qualitative findings are necessary to produce accurate improvement actions for the next development cycle.
ptreezhIntegrate quantitative findings with qualitative insights into a dialectical synthesis.
MajesteitBartExtract reusable lessons from project evidence and update decision records with prioritized improvements.
mkalhitti-cloudCoordinate multi-session agent projects with persistent, dependency-aware task tracking.
jassicsAutomate forensic triage by collecting disk, memory, and log evidence to build an incident timeline.
