Session Retrospective

Session Retrospective is an AI Engineering skill for Claude Code, published by jpicklyk in task-orchestrator.

206 stars20 forkson jpicklyk/task-orchestratorAdded 2026/09/05Repository updated 2026/08/04

ai-coding-assistantai-developmentai-harnessai-memoryai-toolsclaudeclaude-codeclaude-desktopcontext-persistencedeveloper-toolsharness-engineeringharness-frameworkmcpmcp-servermodel-context-protocoltask-managementvibe-codingworkflow-automation

Install in seconds

Install Session Retrospective

Copy Session Retrospective into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/session-retrospective ~/.claude/skills/session-retrospective

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/jpicklyk/task-orchestrator.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: claude-plugins/task-orchestrator/skills/session-retrospective/SKILL.md in jpicklyk/task-orchestrator
Installs to: ~/.claude/skills/session-retrospective
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 3101 skills

What Session Retrospective does

Session Retrospective analyzes an implementation run by checking schema quality, delegation alignment, note effectiveness, and plan-to-execution fit. Use it after a run or when you want a session review and improvement notes.

Session Retrospective is cataloged under AI Engineering on DirSkills. Session Retrospective comes from a repository tagged ai-coding-assistant, ai-development, ai-harness, ai-memory and ai-tools.

Documentation

README

Excerpt

Session Retrospective

Structured post-implementation analysis. Evaluates the current run across five dimensions, persists findings in MCP, and maintains cross-session trend memory to surface actionable improvement proposals.

Step 0 — Mode Check

If $ARGUMENTS contains --dry-run, set DRY_RUN = true. In dry-run mode, perform steps 1-4 and render the report (step 9) but skip steps 5-8 (no MCP item creation, no memory updates). Announce at the top of the report: **Dry run** — no items created, no memory updated.

This is the opening of the README. Read the full README on GitHub.

Commands Session Retrospective provides

Slash commands named in this skill’s SKILL.md, listed in the order they first appear.

/implement

Frequently asked about Session Retrospective

What else does jpicklyk publish alongside Session Retrospective?
Session Retrospective is one of 25 skills that DirSkills catalogs from jpicklyk/task-orchestrator, the repository it ships in. Its siblings there include API Compatibility Review, Adopt Project Scope and Batch Complete. Each one is a separate skill with its own page in this directory, installs the same way Session Retrospective does, and is maintained by jpicklyk in that same repository. The rest of the collection is listed on the jpicklyk/task-orchestrator page.
How does Session Retrospective compare to other AI Engineering skills?
Session Retrospective ranks #2794 by stars among the 3101 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Session Retrospective against them. Open each page to compare what they document and how they install.