majiayu000 /============================================================================/ /* 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:
- Detect Domain: Identify the domain for expertise management
- Check Expertise: Look for
.claude/expertise/meta-expertise.yaml - Load Context: If exists, load expertise schema and validation rules
- 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 historymcp__memory-mcp__vector_search: Find relevant expertise for current task
Activation:
claude mcp add memory-mcp npx @modelcontextprotocol/server-memory
Core Operations
Operation 1: Create Expertise File
Command: /expertise-create <domain>
SOP:
// 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:
// 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]