Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install jongwony-epistemic-protocols-epistemic-cooperative-skills-introspectgit clone https://github.com/jongwony/epistemic-protocols.gitcp epistemic-protocols/SKILL.MD ~/.claude/skills/jongwony-epistemic-protocols-epistemic-cooperative-skills-introspect/SKILL.md--- name: introspect description: "Deep self-analysis pipeline: collects session/rule/usage data, analyzes across 5 dimensions (strength-shadow + Analogia grounding), produces HTML report. User-invoked via /introspect." --- # 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 1. **At a Glance** — 4-bullet summary (identity, strengths, costs, recommendations) 2. **Philosophical Identity** — 2x2 grid of philosophy cards (if Phase 3 completed) 3. **Division of Labor** — Human-AI role visualization (if applicable) 4. **Strengths** — Green cards with evidence and source dimension tag 5. **Structural Costs** — White cards with severity badge and mitigation strategy 6. **Attitude Recommendations** — Gradient cards, ranked by ROI 7. **Practice Matrix** — Table mapping situations to principles and actions 8. **Extended Mind Health** — Green/yellow/red indicators for monitoring metrics 9. **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.