/reflect — Deep Reflection

You are performing a deep reflection on accumulated experience. This is a read-only analysis — you will NOT modify any files.

Purpose

Analyze the event log and current rules to identify patterns, recurring issues, and opportunities for improvement. This gives the user (and the agent) insight into the evolution trajectory.

Procedure

Step 1: Read the Event Log

Read .claude/path-kernel/event-log.jsonl in full. Parse each line as JSON. Group events by type. Common types include:

• •system:init — Session initialization (hook-produced)
• •system:session-end — Session end bookend (hook-produced)
• •perception:situation — User prompt capture (hook-produced)
• •modification:applied — Rule file changes (hook-produced)
• •modification:proposal — Proposed change before applying (agent-produced, /evolve)
• •feedback:human — Feedback input logged (agent-produced, /evolve)
• •evolve:analysis — Gap analysis results (agent-produced, /evolve)
• •reflection:analysis — Deep reflection results (agent-produced, /reflect)
• •system:export — State snapshots (agent-produced, /export-state)

Not all types may be present in early logs. Report what you find rather than expecting specific types.

Step 2: Read Current Rules

Read .claude/path-kernel/config.json for the authoritative list of mutable rule files (agentCanModify). Read each file listed there. These span three domains under .claude/rules/: world, valence, and skill.

Step 3: Analyze Patterns

Identify and report on:

1. •Feedback themes: Are there recurring types of feedback? What keeps coming up?
2. •Modification trajectory: How have the rules evolved? Is there a direction?
3. •Domain distribution: Are modifications concentrated in one domain (world/valence/skill) or spread evenly? What does this suggest?
4. •Gaps: Are there feedback items that haven't been addressed? Rules that seem stale or contradictory?
5. •Self-model accuracy: Does the self-model (.claude/rules/world/self-model.md) match the actual performance patterns visible in the log?
6. •Version progression: How many evolution cycles have occurred? What's the rate?

Step 4: Recommendations

Based on the analysis, suggest (but do NOT apply):

• •Specific rule changes that might help
• •Rules that could be consolidated or removed
• •Domains that need more attention
• •Whether the agent might be ready for the next step in capability progression

Step 5: Report

Present the analysis in a structured format:

## Reflection Summary

### Event Log Stats
- Total events: N
- Feedback events: N
- Modifications applied: N
- Modifications rejected: N
- Evolution cycles completed: N

### Feedback Themes
- [theme]: [frequency] — [example]

### Modification Trajectory
- [domain]: [count] changes — [direction/trend]

### Recommendations
1. [recommendation]
2. [recommendation]

Step 5b: Log Reflection Event

After presenting the report, emit a reflection:analysis event to the event log. This is observability (append-only log), not state mutation — it does not violate the read-only constraint.

PROMPT_VERSION=$(jq '.cycleCount // 0' .claude/path-kernel/state.json 2>/dev/null || echo 0)
bash .claude/hooks/append-event.sh "reflection:analysis" \
  '{"summary":"<themes identified>","recommendations_count":<N>}' "$PROMPT_VERSION"

Replace <themes identified> with a brief summary of themes from Step 3, and <N> with the number of recommendations from Step 4.

Constraints

• •This skill is read-only with respect to rules and state files. Do NOT modify any rules, state, or config files.
• •Emitting events to the append-only event log (via append-event.sh) is permitted — it is observability, not state mutation.
• •Do NOT invoke /evolve — present recommendations for the user to decide.
• •Be honest about limitations: if there's insufficient data, say so.
• •If the event log is empty or very small, note that the agent is too early in its evolution to identify meaningful patterns.