plugins/ce/skills/post-mortem/SKILL.md
Review a completed session to extract actionable improvements. Identifies DX friction, documentation gaps, architectural confusion, anti-patterns, process failures, and skill/config improvements. Uses progressive disclosure for targeted investigation types.
npx skillsauth add rileyhilliard/claude-essentials post-mortemInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Review a completed session or task to assess how it went and extract improvements. This covers both "how did we do" evaluation and "what can we learn" investigation.
After completing any non-trivial task or session. The goal is continuous improvement:
Load the relevant reference based on what you're investigating:
| Situation | Load | File |
|-----------|------|------|
| Agent hit friction during execution (wrong files, bad assumptions, unclear conventions) | DX Friction | references/dx-friction.md |
| Documentation (READMEs, comments, API docs) was wrong, incomplete, or misleading | Documentation Gaps | references/documentation-gaps.md |
| Code was hard to understand or things were in unexpected places | Architecture Clarity | references/architecture-clarity.md |
| A bug was fixed but the root cause suggests a process gap | Bug Prevention | references/bug-prevention.md |
| Code works but diverges from best practices, idioms, or established conventions | Anti-Patterns | references/anti-patterns.md |
| Skills, hooks, commands, agents, or .claude/ configs need updating | Tooling Improvements | references/tooling-improvements.md |
Load multiple references when the session spans investigation types.
Every post-mortem follows four steps regardless of investigation type.
Walk through the session timeline. For each significant step, note:
Don't editorialize yet. Just document the sequence.
Evaluate how the session went overall:
Flag anything that felt harder than it should have been, even if it ultimately succeeded.
For each friction point, ask: "What would have prevented this?"
Push past the first answer. "I should have read the file more carefully" is a symptom. "The file's name doesn't indicate what it contains" or "there's no convention documented for where this type of code lives" is a systemic cause.
Good root causes point to something fixable:
Bad root causes are just descriptions of what went wrong:
Every finding should produce one of these:
Each action should have a specific file path and description of the change. Vague actions like "improve documentation" are not useful.
## Session Post-Mortem
### What Happened
[Timeline of the session with key decision points]
### Execution Assessment
- **Outcome:** [What was delivered vs what was asked]
- **Efficiency:** [Direct path or detours? Where and why?]
- **What worked well:** [Patterns, skills, or approaches worth repeating]
### Findings
#### Finding 1: [Title]
**What happened:** [The friction or issue, stated factually]
**Root cause:** [The systemic issue underneath]
**Action:** [Specific change with file path]
**Priority:** [High/Medium/Low based on how often this would recur]
#### Finding 2: [Title]
...
### Summary
[1-2 sentences: biggest takeaway and what should change first]
development
Selects and applies professional journalistic story structures (WSJ Formula, Inverted Pyramid, Hourglass, Tick-Tock, etc.) based on the content being written. Use when writing articles, blog posts, features, essays, long-form content, news stories, trend pieces, investigative reports, profiles, or any narrative prose longer than a few paragraphs. Also use when the user asks for help structuring a piece, choosing a story framework, organizing a draft, outlining an article, or wants to know which article format fits their content. Trigger on requests like "help me structure this," "what format should I use," "write a feature about," "draft a blog post on," or any mention of story structure, article architecture, or narrative frameworks. Complements the writer skill (which handles tone and anti-AI rhetoric) by providing the structural blueprint.
testing
Writing style and tone guide for human-sounding content. Use when writing documentation, READMEs, commit messages, PR descriptions, blog posts, LinkedIn posts, social media content, or any user-facing content.
data-ai
Create implementation plans with tasks grouped by subsystem. Related tasks share agent context; groups parallelize across subsystems.
development
Debugging framework that finds root causes before proposing fixes. Use when investigating bugs, errors, unexpected behavior, failed tests, or when previous fixes haven't worked.