Agent skill

expertise-manager

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Install this agent skill to your Project

npx add-skill https://github.com/DNYoussef/context-cascade/tree/main/skills/specialists/expertise-manager

SKILL.md

/============================================================================/ /* 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]

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