sophia

name	sophia
description	Discover your philosophical tradition through behavioral dimension analysis and philosopher matching.

Sophia (σοφία)

Discover your philosophical tradition through behavioral pattern analysis.

φιλο-σοφία = "love of wisdom" Your conversation patterns carry the fingerprint of a philosophical tradition.

When to Use

Invoke this skill when:

• Exploring which philosophical tradition your AI conversation patterns resemble
• Analyzing behavioral dimensions across sessions for epistemic style profiling
• Generating a visual philosopher match profile card

Skip when:

• Analyzing strengths and structural costs (use /curses 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 from sessions	dimension-profiler agent
2. Match	Map dimension profile to philosophers	AI analysis
3. Present	Dual-layer result + protocol affinity	Gate interaction
4. Report	Generate HTML profile card	Automated

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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: first run coverage-scanner for pre-aggregated data, then pass the result to dimension-profiler for dimension scoring. This avoids duplicate file reading and gives the profiler access to protocol usage counts.

Step 1: Run coverage-scanner agent (see agents/coverage-scanner.md):

Aggregate facets, session-meta, and slash command data across all sessions.
Return structured coverage data including protocol_counts, friction_summary,
session_type_distribution, tool_counts, and satisfaction_distribution.

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 coverage-scanner returns no data (new user with no sessions), skip Step 1 and run dimension-profiler with data_sources only (rules + CLAUDE.md). Note reduced confidence in results.

---

Phase 2: Philosopher Matching

Read references/philosophers.md for the full philosopher database.

Matching process

1. Compute similarity score for each philosopher against the user's profile
2. Identify the top match (highest similarity) and runner-up
3. For the top match, identify:
   • Primary alignment: Which dimension drives the match
   • Divergence points: Where the user differs from the philosopher
   • Protocol affinity: Which epistemic protocol aligns with this tradition

Confidence levels

Data quality	Match confidence
20+ facets sampled, all dimensions measured	High
10-19 facets, most dimensions measured	Medium
<10 facets or rules-only analysis	Low — note limitations

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Phase 3: Presentation

Present the match progressively — start with an accessible introduction, then build to detailed analysis. Users may not know the philosopher; the opening should stand on its own without assumed knowledge.

Step 1: Introduction (always show first)

A warm, 2-3 sentence introduction that explains the match in plain language:

Your thinking patterns most resemble the tradition of [Philosopher Name]
([dates], [tradition in one phrase]).

[1-2 sentences: what this philosopher is known for, in terms a non-philosopher
would understand. Connect to the user's actual behavior — not abstract philosophy.]

Similarity: 0.XX | Runner-up: [Name] (0.XX)

Step 2: Dimension profile with explanations

Show dimensions with human-readable explanations (from dimension-profiler output) so users understand what each bar means:

  ──────────────────────────────────────
  D1 How you approach problems:    ████████░░ 78  (hypothesis-first)
  D2 How much you check:          █████████░ 85  (thorough)
  D3 How you interact:            ██████░░░░ 62  (moderate)
  D4 How you govern work:         █████████░ 91  (systematic)
  D5 Where you focus:             ████████░░ 78  (exploring unknowns)
  D6 How you use AI:              █████████░ 88  (distributed thinking)
  ──────────────────────────────────────
  
  Protocol affinity: /[command] ([protocol name] — [Greek])

Step 3: User choice

What would you like to explore?
1. **Deep dive** — Why this tradition fits your patterns, and what it reveals
2. **Compare** — Side-by-side with the runner-up
3. **Protocol** — Try the suggested protocol now
4. **Report** — Generate HTML profile card

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Phase 4: Report Generation

If the user selects "Report", generate an HTML profile card.

Report structure

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 the existing CSS design system from {config_dir}/usage-data/report.html or use the design tokens from the cooperative's dashboard/report templates.

Sections:

1. Introduction: 2-3 sentence accessible summary (who is this philosopher, why you match) before the hero card
2. Hero: Philosopher name + tradition + archetype subtitle
3. Radar chart: 6-dimension profile as visual (CSS-only, no JS library)
4. Match analysis: Why this philosopher, in 3-4 bullet points
5. Dimension breakdown: Each dimension with score bar, human-readable explanation, measurement basis, and meaning. Use the explanation column from dimension-profiler output (e.g., "How you approach problems") as subtitle for each bar.
6. Protocol affinity: Recommended protocols with one-line rationale
7. Runner-up: Brief comparison showing where profiles diverge File: Save to {config_dir}/usage-data/sophia-profile.html Open in browser: open <filepath>

CSS radar chart (no JS dependency)

Use CSS clip-path: polygon(...) with computed vertices for a hexagonal radar chart. Each vertex position is calculated from the dimension score (0-100 mapped to center-to-edge).

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Edge Cases

• New user (<5 sessions): Analyze rules/CLAUDE.md only. Present as "Early profile — based on configuration, not yet behavioral data." Confidence: Low.
• Balanced profile (all 40-60): Use composite archetypes from philosophers.md. Present as "The Balanced Practitioner (Aristotelian phronesis)" with explanation that balance itself is a philosophical position.
• No clear match (all similarities <0.55): Present top 2 as "Your profile doesn't strongly align with a single tradition — you may be synthesizing multiple approaches." Offer composite archetype.
• Missing dimensions: If a dimension can't be computed (no data), mark as "unmeasured" and exclude from matching. Note which dimensions are missing.