curses

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.

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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: {config_dir}/rules/
  claude_md: {config_dir}/CLAUDE.md
  settings_json: {config_dir}/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.

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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 "deliberate Extended Mind strategy with quality bridges" OR "KK neglect via over-delegation"
• D2 high + D4 high: Could be "systematic verification infrastructure that scales" OR "cure-as-disease accumulation"

For these dual-interpretation patterns specifically, retain a Constitution gate before downstream derivation: "This pattern admits two readings — [strategy interpretation] or [curse 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.

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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.

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Phase 4: Report Generation

Generate an HTML report following the cooperative's design system.

Design system source

Paths below written {config_dir}/… take {config_dir} = CLAUDE_CONFIG_DIR when set, else ~/.claude. Resolve it ONCE per invocation with Bash printf '%s\n' "${CLAUDE_CONFIG_DIR-$HOME/.claude}" and substitute the absolute result before any Read/Glob/Grep call.

Read one of:

• {config_dir}/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. 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 {config_dir}/usage-data/curses-profile.html Open in browser: open <filepath>

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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.