curses
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npx mdskill add jongwony/epistemic-protocols/cursesExpose hidden costs of strengths through behavioral analysis.
- Reveals structural costs embedded within user capabilities.
- Depends on dimension-profiler agent for behavioral data.
- Derives recommendations via strength-shadow extraction dialogue.
- Delivers attitude principles and practice matrix reports.
SKILL.md
.github/skills/cursesView on GitHub ↗
--- name: curses description: "Discover the structural costs hidden in your strengths through behavioral dimension analysis, strength-shadow extraction, and attitude recommendations." --- # Curses Discover the structural costs hidden in your strengths. > Every strength casts a shadow. The shadow is not a flaw — > it is the structural cost of a capability. Understanding the > cost transforms a curse into a conscious trade-off. ## When to Use Invoke this skill when: - Discovering structural costs hidden in your strengths - Analyzing behavioral patterns for self-improvement recommendations - Generating attitude principles and practice matrix - Reflective questions about working patterns and their trade-offs Skip when: - Exploring philosophical tradition match (use /sophia instead) - Quick single-protocol question (answer directly) - No session history exists and user prefers manual exploration ## Pipeline | Phase | What | Mode | |-------|------|------| | 1. Collect | Gather behavioral data | dimension-profiler agent | | 2. Analyze | Strength-Shadow extraction | AI + user dialogue | | 3. Recommend | Attitude principles + practice matrix | AI proposes | | 4. Report | Generate HTML report | Automated | If the user provides a specific question (e.g., "What are my curses?"), orient the analysis toward that question. --- ## Phase 1: Data Collection **Same-session reuse**: If dimension-profiler output is already available in this conversation (from a prior `/sophia` or `/curses` run), skip Phase 1 entirely and reuse that output. Both skills produce identical profiler results. Two-step delegation (same pipeline as `/sophia`): **Step 1**: Run `coverage-scanner` agent (see `agents/coverage-scanner.md`) to get pre-aggregated session data (protocol counts, friction, session types, tools). **Step 2**: Pass coverage output to `dimension-profiler` agent (see `agents/dimension-profiler.md`): ``` Analyze this user's behavioral dimensions from their session data. coverage_data: [paste coverage-scanner output here] data_sources: rules_dir: ~/.claude/rules/ claude_md: ~/.claude/CLAUDE.md settings_json: ~/.claude/settings.json data_context: session-enriched Return the dimension profile table with scores, confidence, and raw signals. ``` When `coverage_data` is provided, omit `sample_size` — the profiler derives dimensions from aggregate data and does not sample raw files. If a dimension's confidence is "low", include it in the analysis but mark it as provisional and note this in the report. --- ## Phase 2: Strength-Shadow Analysis From the dimension profile, identify strengths and their structural costs. ### Extraction method For each dimension scoring above 65 (or below 35 — extremes in either direction): 1. **Name the strength**: What capability does this extreme enable? 2. **Find the shadow**: What structural cost does this extreme create? 3. **Identify the mechanism**: Why does this strength produce this specific cost? 4. **Rate severity**: structural (inherent), recurring (frequent), or conditional (context-dependent) 5. **Cite evidence**: Link to specific data from the dimension profiler ### Common strength-shadow patterns These are heuristic starting points, not fixed outputs. Adapt based on actual data. | Dimension extreme | Strength | Shadow | |-------------------|----------|--------| | D2 high (Doubt) | Catches errors early | Verification depth becomes opportunity cost | | D4 high (Systematic) | Consistent governance | Rule accumulation creates complexity | | D5 high (UU) | Discovers new patterns | May defer KK maintenance | | D6 high (Extended Mind) | Effective delegation | Curse activates on delegation failure | | D1 high (Abductive) | Creative hypothesis | May skip systematic validation | | D3 high (Dialogical) | Deep understanding | Extended exchanges consume time | ### Cross-dimensional patterns Look for patterns that emerge from dimension COMBINATIONS: - **D2 high + D4 high**: "The cure-as-disease pattern" — each verification failure produces a new rule, which accumulates - **D5 high + D6 high**: "Extended Mind strategy" — UU preference + AI delegation may be a strategy, not a curse (validate with user) - **D1 high + D2 high**: "Bold conjecture + rigorous refutation" — Popperian pattern, strong if balanced ### Dual-interpretation guidance (cold-start awareness) When presenting strength-shadow pairs, some combinations may be either a curse OR a deliberate strategy. In context-rich sessions, the user may have already articulated this distinction. In cold-start sessions, the AI must proactively surface both interpretations before the user validates. Patterns that require dual-interpretation: - **D5 high + D6 high**: Could be "KK neglect via over-delegation" OR "deliberate Extended Mind strategy with quality bridges" - **D2 high + D4 high**: Could be "cure-as-disease accumulation" OR "systematic verification infrastructure that scales" For these dual-interpretation patterns specifically, retain a Constitution gate before downstream derivation: "This pattern admits two readings — [curse interpretation] or [strategy interpretation]. Which better describes your experience?" The user's intent here is project-profile category (a) — user IS the measurement target — and cannot be auto-resolved regardless of profile; downstream recommendations depend on this choice. Single-interpretation pairs (e.g., D1+D2, isolated dimensions) bypass this gate and proceed via the relay path described under "User dialogue" below. ### User dialogue When presenting dimensions to the user, always include the human-readable explanation from the dimension-profiler output (e.g., "D4 Rule Orientation — how you govern work") so users unfamiliar with the framework understand what each dimension measures. Present single-interpretation strength-shadow pairs (the majority — those without the dual-interpretation gate above) as text output and proceed directly to Phase 3 recommendations. End the Phase 2 output with a visible red-line discovery line so the correction pathway is explicit: "If any pair seems misclassified, say so — I'll re-derive from there." The user may red-line via free response at any subsequent turn — confirm, reframe, dismiss, or add context. Counter-evidence that changes the structural category triggers re-derivation of downstream recommendations on the next turn. --- ## Phase 3: Recommendations From validated strength-shadow pairs, derive: ### Attitude principles (max 4) Each principle addresses a specific shadow: ``` Principle N — [Title] [2-3 sentence explanation of the principle and why it addresses this shadow] Application: [Concrete, actionable guidance for daily practice] ``` Rank by ROI — which principle would have the highest impact if adopted? Mark the highest-ROI principle explicitly. ### Practice matrix Map principles to concrete situations: | Situation | Principle | Action | Trigger | |-----------|-----------|--------|---------| | When X happens | Principle N | Do Y | Z condition | Include 4-6 rows covering the most common situations. --- ## Phase 4: Report Generation Generate an HTML report following the cooperative's design system. ### Design system source Read one of: - `~/.claude/usage-data/report.html` — extract CSS - Cooperative's `skills/report/references/html-template.md` — use as template basis - `skills/curses/references/report-template.md` — curses-specific components ### Context awareness Check the dimension-profiler's `Data Context` field: - **session-enriched**: Report may reference protocol chaining results, prior /sophia output, or session-specific observations. Include these in relevant sections. - **data-only**: Report is generated purely from behavioral data. Do not reference protocol interactions or session-specific context that doesn't exist. Keep analysis grounded in the dimension scores and raw signals. Mark the report subtitle with the context tier (e.g., "708 sessions | data-only" or "708 sessions | session-enriched"). ### Required sections 1. **At a Glance** — 3-4 bullet summary with section links 2. **Dimension Profile** — 6 horizontal bars with scores and human-readable explanation per dimension 3. **Strengths** — Green cards with evidence and dimension tag 4. **Structural Costs** — White cards with severity badge and mitigation 5. **Attitude Recommendations** — Gradient cards ranked by ROI 6. **Practice Matrix** — Situation to principle to action table 7. **Health Indicators** — Green/yellow/red dots for monitored vs unmonitored areas 8. **Next Steps** — 2-3 concrete horizon cards ### Optional sections (if /sophia was run in same session) If the dimension profile and philosopher match are available from a prior `/sophia` run in this session, include: - **Philosophical Identity** — 2x2 grid of philosophy cards - **Division of Labor** — Human-AI role visualization ### Output Save to `~/.claude/usage-data/curses-profile.html` Open in browser: `open <filepath>` --- ## Edge Cases - **New user (<5 sessions)**: Analyze rules only. Present as "Configuration-based profile — behavioral data will improve accuracy over time." - **No extreme dimensions (all 35-65)**: "Your profile is notably balanced. This is itself a strength (Aristotelian phronesis) with its own shadow: you may lack the specialization that comes from extreme focus." - **User reframes curse as strategy**: Accept the reframe. Update the strength-shadow pair to reflect the new category. Re-derive recommendations from the updated structure. - **Specific question provided**: Orient the entire analysis toward answering that question. The report sections should reflect the specific inquiry.
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