Introspect
A self-analysis pipeline that collects behavioral context, identifies patterns, and produces actionable insights as an HTML report. The pipeline has 4 phases, each building on the previous.
Pipeline Overview
| Phase | What | Mode | Output |
|-------|------|------|--------|
| 1. Collect | Gather data from 4 sources | 3 parallel inline Task invocations | Raw findings |
| 2. Analyze | Synthesize into profile | AI + user dialogue | Strengths, costs, conflicts |
| 3. Ground | Map to philosophical frameworks | Optional Analogia | Validated mapping |
| 4. Report | Generate HTML report | Automated | .html file |
If the user provides a specific question (e.g., "What are my curses?"), orient the analysis toward answering that question rather than producing a generic profile.
Phase 1: Data Collection
Launch 3 parallel ad-hoc inline Task(general-purpose) invocations. These are not pre-registered agent files — each is an inline prompt task launched for this pipeline only. Each collects from different sources and returns structured findings. All prompts are English per delegation rules; search keywords in quotes are exempt.
Agent 1: Rules & Configuration
PURPOSE: Extract the user's explicitly stated preferences and constraints from their
Claude Code configuration.
COLLECT:
1. Read ~/.claude/CLAUDE.md — extract all stated preferences, principles, and constraints
2. Read all files in ~/.claude/rules/ — extract each rule with its rationale
3. Read ~/.claude/projects/*/memory/MEMORY.md — extract persistent session memory
RETURN FORMAT:
## Stated Preferences
- [preference]: [source file]
## Constraints & Boundaries
- [constraint]: [source file]
## Rule Inventory
- Total rules: N
- Categories: [list]
- Potential redundancies: [if any rules overlap or subsume others]
## Memory Highlights
- [key patterns from session memory]
Agent 2: Usage Patterns (Quantitative)
PURPOSE: Extract quantitative behavioral patterns from usage data.
COLLECT:
1. Read ~/.claude/usage-data/report.html — extract key statistics (messages, tools,
friction types, outcomes, satisfaction, session types)
2. Sample 5-10 facet files from ~/.claude/usage-data/facets/ — extract
recurring themes, tool usage patterns, satisfaction signals
3. Sample 5-10 session-meta files from ~/.claude/usage-data/session-meta/ —
extract session types, durations, goal patterns
RETURN FORMAT:
## Quantitative Profile
- Messages: N across M sessions
- Top tools: [ranked list]
- Top goals: [ranked list]
- Outcome distribution: [fully/mostly/partially/not achieved]
## Behavioral Signals
- Session type distribution: [multi-task, iterative, single, exploration]
- Friction patterns: [top 3 with counts]
- Satisfaction distribution
## Notable Patterns
- [3-5 patterns that stand out from the quantitative data]
Agent 3: Session Behavior (Qualitative)
PURPOSE: Extract qualitative behavioral patterns from recent session transcripts.
COLLECT:
1. List session files in ~/.claude/projects/ (find recent, large sessions)
2. Sample 3-5 substantive sessions (>50KB) — use Grep to extract:
- User correction patterns (interruptions, redirections)
- Decision-making patterns (how user makes choices)
- Protocol usage patterns (which epistemic protocols, how often)
- Communication style (directive, collaborative, exploratory)
NOTE: COLLECT operates on session transcripts and protocol patterns only — cross-reference to user-personal analysis artifacts (curated insight files) is intentionally out of scope; the analysis remains substrate-agnostic and reproducible across users.
RETURN FORMAT:
## Interaction Style
- [3-5 observed patterns with session evidence]
## Decision Patterns
- [how the user approaches decisions, with examples]
## Correction Patterns
- [what the user corrects most often, what triggers corrections]
## Protocol/Tool Preferences
- [which tools/protocols are preferred and when]
Phase 2: Pattern Analysis
After all 3 agents return, synthesize findings across 5 dimensions.
5-Dimension Framework
Analyze each dimension by cross-referencing data from all 3 agents:
| Dimension | What to look for | Sources | |-----------|-----------------|---------| | Communication Style | Directive vs collaborative, interruption patterns, feedback style | Agent 1 (rules), Agent 3 (sessions) | | Technical Preferences | Tool choices, language preferences, architecture patterns | Agent 1 (rules), Agent 2 (usage) | | Cognitive/Decision Patterns | Verification depth, risk tolerance, abstraction appetite | Agent 2 (friction), Agent 3 (decisions) | | Domain/Context | Primary work areas, domain switching patterns | Agent 2 (goals), Agent 3 (sessions) | | Premise | Core values, what drives engagement, what causes frustration | All agents |
Strength-Shadow Analysis
For each strength identified, find its structural cost (the "shadow"):
Pattern: [observed strength]
Evidence: [specific data from agents]
Shadow: [structural cost that comes with this strength]
Mechanism: [why the strength produces this specific cost]
The key insight: every strength has a shadow, and the shadows often share a common structure (precision creates new complexity, optimization creates blind spots).
Conflict Surface
Compare descriptive patterns (what the user actually does, from Agent 2/3) against prescriptive rules (what the user says to do, from Agent 1). Surface mismatches:
- Rules that the user's own behavior contradicts
- Patterns not captured by any rule
- Rules that may be redundant or subsumable
Present the analysis as text output (strengths, shadows, conflict surface) and proceed to Phase 3 directly — Phase 1 evidence already establishes pattern existence, so pre-validation is Extension-eligible for relay-eligible findings. End the Phase 2 output with a visible red-line discovery line so the correction pathway is explicit: "If any pattern seems misclassified or rules need adjusting, say so — I'll re-derive from there." Conflict-surface synthesis (rules the user contradicts, redundant rules) involves intent inference (deliberate exception vs drift), so the discovery line is required to surface this constitutive layer without a full pre-validation gate. The user may red-line via free response at any subsequent turn (refine, correct, dismiss a pattern, or add context); when that happens, regenerate affected downstream sections on the next turn.
Phase 3: Philosophical Grounding
Map identified patterns to philosophical frameworks, giving the user a conceptual vocabulary for understanding their cognitive style.
When to activate
Always offer this phase. If the user accepts, invoke /analogia:ground with the key
findings as the grounding target. The Analogia protocol handles mapping validation
through user dialogue.
Mapping candidates
Common correspondences to consider (not exhaustive):
| Pattern | Candidate frameworks | |---------|---------------------| | UU exploration preference | Popper (Critical Rationalism), Peirce (Abduction) | | AI delegation strategy | Clark & Chalmers (Extended Mind), Ricardo (Comparative Advantage) | | Openness to new problems | Zen Beginner's Mind, Socratic questioning | | Verification depth | Aristotelian phronesis, Cartesian doubt | | System building tendency | Kantian architectonic, Systems thinking |
The Analogia process may refine or reject these candidates. User counter-arguments are often the most valuable part — as when "curse" was reframed as "strategy" through an AI-delegation counter-hypothesis.
Phase 4: Report Generation
Generate an HTML report and save to ~/.claude/epistemic-cooperative/introspect/.
Design System
Read the existing ~/.claude/usage-data/report.html to extract the CSS design system.
Match its visual style: Inter font, #f8fafc background, white cards with #e2e8f0 border.
See references/report-guide.md for section templates and component patterns.
Required Sections
- At a Glance — 4-bullet summary (identity, strengths, costs, recommendations)
- Philosophical Identity — 2x2 grid of philosophy cards (if Phase 3 completed)
- Division of Labor — Human-AI role visualization (if applicable)
- Strengths — Green cards with evidence and source dimension tag
- Structural Costs — White cards with severity badge and mitigation strategy
- Attitude Recommendations — Gradient cards, ranked by ROI
- Practice Matrix — Table mapping situations to principles and actions
- Extended Mind Health — Green/yellow/red indicators for monitoring metrics
- Next Steps — Horizon cards with concrete next actions
Output
Save as ~/.claude/epistemic-cooperative/introspect/cognitive-partnership-profile.html
(date-stamped variant if previous report exists).
After saving, print the file path so the user can open it manually.
Edge Cases
- First-time run: If report.html missing, use CSS from
references/report-guide.md. - Missing data: Note limitations in the report, focus on available sources.
- Specific question: Orient entire analysis toward the question, not a generic profile.
- Skip grounding: If user declines Phase 3, proceed directly to Phase 4. Philosophical identity section becomes optional in the report.