Post Mortem

Post-Mortem

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.

When to Use

After completing any non-trivial task or session. The goal is continuous improvement:

• Routine review: How smooth was execution? Where did friction occur?
• Problem sessions: Things took longer than expected, multiple corrections needed
• Bug fixes: What caused it and what would prevent it next time?
• New patterns: Something worked well that should be codified

Investigation Types

Load the relevant reference based on what you're investigating:

Load multiple references when the session spans investigation types.

Core Process

Every post-mortem follows four steps regardless of investigation type.

1. Reconstruct What Happened

Walk through the session timeline. For each significant step, note:

• What was attempted
• What actually happened
• Where corrections were needed and why
• What went smoothly (worth noting what worked, not just what didn't)

Don't editorialize yet. Just document the sequence.

2. Assess Execution Quality

Evaluate how the session went overall:

• Efficiency: Did we take a direct path or wander? Where were the detours?
• Accuracy: Were initial approaches correct, or did we need multiple corrections?
• Tooling fit: Did skills, commands, and configs help or get in the way?
• Communication: Was intent clear between user and agent throughout?
• Outcome: Did we deliver what was asked for? Is it solid or just "works for now"?

Flag anything that felt harder than it should have been, even if it ultimately succeeded.

3. Identify Systemic Causes

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:

• A missing or misleading piece of documentation
• An architectural pattern that's inconsistent or undiscoverable
• A skill/config that gives wrong guidance
• A convention that exists but isn't written down
• A test gap that allowed a regression
• A workflow that worked well but isn't codified

Bad root causes are just descriptions of what went wrong:

• "I made a mistake"
• "The code was complex"
• "It took a while to figure out"

4. Propose Concrete Actions

Every finding should produce one of these:

• Documentation update - Fix incorrect docs, add missing docs, clarify ambiguous docs
• Skill/config update - Modify an existing skill or CLAUDE.md instruction
• New skill/hook - Create a new skill or hook to codify a pattern
• Architecture improvement - Refactor to make the system more discoverable
• Test addition - Add tests that would catch this class of issue
• Codify a win - Something that worked well should be made repeatable

Each action should have a specific file path and description of the change. Vague actions like "improve documentation" are not useful.

Output Format

## 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]

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