Expertise Manager

---
name: expertise-manager
description: /============================================================================/
---

/*============================================================================*/
/* EXPERTISE-MANAGER SKILL :: VERILINGUA x VERIX EDITION                      */
/*============================================================================*/

---
name: expertise-manager
version: 2.1.0
description: |
  [assert|neutral] Manages domain expertise files for Agent Experts-style learning. Handles expertise creation, validation, pre-action loading, and post-build auto-updates. Enables agents to accumulate persistent domain [ground:given] [conf:0.95] [state:confirmed]
category: foundry
tags:
- expertise
- learning
- mental-model
- self-improve
- agent-experts
author: system
cognitive_frame:
  primary: aspectual
  goal_analysis:
    first_order: "Execute expertise-manager workflow"
    second_order: "Ensure quality and consistency"
    third_order: "Enable systematic foundry processes"
---

/*----------------------------------------------------------------------------*/
/* S0 META-IDENTITY                                                            */
/*----------------------------------------------------------------------------*/

[define|neutral] SKILL := {
  name: "expertise-manager",
  category: "foundry",
  version: "2.1.0",
  layer: L1
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S1 COGNITIVE FRAME                                                          */
/*----------------------------------------------------------------------------*/

[define|neutral] COGNITIVE_FRAME := {
  frame: "Aspectual",
  source: "Russian",
  force: "Complete or ongoing?"
} [ground:cognitive-science] [conf:0.92] [state:confirmed]

## Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.

/*----------------------------------------------------------------------------*/
/* S2 TRIGGER CONDITIONS                                                       */
/*----------------------------------------------------------------------------*/

[define|neutral] TRIGGER_POSITIVE := {
  keywords: ["expertise-manager", "foundry", "workflow"],
  context: "user needs expertise-manager capability"
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S3 CORE CONTENT                                                             */
/*----------------------------------------------------------------------------*/

# Expertise Manager

## Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.



## Phase 0: Expertise Loading

Before managing expertise:

1. **Detect Domain**: Identify the domain for expertise management
2. **Check Expertise**: Look for `.claude/expertise/meta-expertise.yaml`
3. **Load Context**: If exists, load expertise schema and validation rules
4. **Apply Configuration**: Use meta-expertise for management operations

## Purpose

Enable Agent Experts-style learning in the ruv-sparc three-loop system by managing domain expertise files - persistent mental models that agents read BEFORE acting and auto-update AFTER successful builds.

**Key Innovation**: Agents don't just execute and forget. They execute, learn, and reuse their expertise.

## When to Use This Skill

Activate this skill when:
- Creating a new domain expertise file for a codebase area
- Validating existing expertise against current code
- Loading domain context BEFORE implementation tasks
- Auto-updating expertise AFTER successful Loop 2 builds
- Analyzing expertise accuracy and learning history

**DO NOT** use this skill for:
- Quick one-off tasks (expertise overhead not worth it)
- Non-code tasks (expertise is code-focused)
- Tasks outside defined expertise domains

## MCP Requirements

### Memory MCP (Required)

**Purpose**: Persist expertise across sessions, enable cross-agent knowledge sharing.

**Tools Used**:
- `mcp__memory-mcp__memory_store`: Store expertise state and learning history
- `mcp__memory-mcp__vector_search`: Find relevant expertise for current task

**Activation**:
```bash
claude mcp add memory-mcp npx @modelcontextprotocol/server-memory
```

---

## Core Operations

### Operation 1: Create Expertise File

**Command**: `/expertise-create <domain>`

**SOP**:
```javascript
// PHASE 1: DISCOVERY - Scan codebase for domain
Task("Codebase Scanner",
  `Scan codebase to discover ${domain} domain structure:
   1. Find primary source directory (src/${domain}/, lib/${domain}/, etc.)
   2. Find test directory (tests/${domain}/, __tests__/${domain}/, etc.)
   3. Find config files related to ${domain}
   4. Identify key files (index, main exports, types)

   Output: .claude/.artifacts/expertise-discovery-${domain}.json`,
  "code-analyzer")

// PHASE 2: PATTERN EXTRACTION - Understand how domain works
Task("Pattern Extractor",
  `Extract patterns from ${domain} codebase:
   1. Architecture pattern (MVC, Clean Architecture, etc.)
   2. Data flow patterns (how data moves)
   3. Error handling patterns
   4. Validation patterns
   5. Key entities (classes, functions, types)

   Output: .claude/.artifacts/expertise-patterns-${domain}.json`,
  "analyst")

// PHASE 3: RELATIONSHIP MAPPING - Find dependencies
Task("Dependency Mapper",
  `Map relationships for ${domain}:
   1. What domains does ${domain} depend on?
   2. What domains depend on ${domain}?
   3. What external services does ${domain} use?
   4. What are the coupling strengths?

   Output: .claude/.artifacts/expertise-relationships-${domain}.json`,
  "analyst")

// PHASE 4: SYNTHESIS - Create expertise file
Task("Expertise Synthesizer",
  `Synthesize expertise file for ${domain}:
   1. Load discovery, patterns, relationships from artifacts
   2. Generate .claude/expertise/${domain}.yaml
   3. Create initial validation rules
   4. Set metadata (created_by, timestamps)
   5. Store in Memory MCP: expertise/${domain}

   Output: .claude/expertise/${domain}.yaml`,
  "knowledge-manager")
```

---

### Operation 2: Validate Expertise (Pre-Action)

**Command**: `/expertise-validate <domain>`

**Purpose**: Verify expertise file matches current code reality BEFORE acting.

**SOP**:
```javascript
// PHASE 1: LOAD EXPERTISE
const expertise = loadExpertiseFile(domain);
if (!expertise) {
  console.log("No expertise file found. Run /expertise-create first.");
  return;
}

// PHASE 2: RUN VALIDATION RULES
Task("Validation Runner",
  `Validate expertise for ${domain}:

   For each validation_

/*----------------------------------------------------------------------------*/
/* S4 SUCCESS CRITERIA                                                         */
/*----------------------------------------------------------------------------*/

[define|neutral] SUCCESS_CRITERIA := {
  primary: "Skill execution completes successfully",
  quality: "Output meets quality thresholds",
  verification: "Results validated against requirements"
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S5 MCP INTEGRATION                                                          */
/*----------------------------------------------------------------------------*/

[define|neutral] MCP_INTEGRATION := {
  memory_mcp: "Store execution results and patterns",
  tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"]
} [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S6 MEMORY NAMESPACE                                                         */
/*----------------------------------------------------------------------------*/

[define|neutral] MEMORY_NAMESPACE := {
  pattern: "skills/foundry/expertise-manager/{project}/{timestamp}",
  store: ["executions", "decisions", "patterns"],
  retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]

[define|neutral] MEMORY_TAGGING := {
  WHO: "expertise-manager-{session_id}",
  WHEN: "ISO8601_timestamp",
  PROJECT: "{project_name}",
  WHY: "skill-execution"
} [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S7 SKILL COMPLETION VERIFICATION                                            */
/*----------------------------------------------------------------------------*/

[direct|emphatic] COMPLETION_CHECKLIST := {
  agent_spawning: "Spawn agents via Task()",
  registry_validation: "Use registry agents only",
  todowrite_called: "Track progress with TodoWrite",
  work_delegation: "Delegate to specialized agents"
} [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S8 ABSOLUTE RULES                                                           */
/*----------------------------------------------------------------------------*/

[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* PROMISE                                                                     */
/*----------------------------------------------------------------------------*/

[commit|confident] <promise>EXPERTISE_MANAGER_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]