Curses

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.

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"

When presenting these, frame as: "This pattern admits two readings — [curse interpretation] or [strategy interpretation]. Which better describes your experience?" The user's response determines downstream recommendations.

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 the top 3-4 strength-shadow pairs and ask the user to validate. The user may:

• Confirm a finding
• Reframe it (e.g., re-categorize a "curse" as a deliberate "strategy")
• Dismiss it as not applicable
• Add context that changes the analysis

User counter-evidence that changes the structural category (e.g., flaw to strategy) requires re-derivation of downstream recommendations.

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:

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.