# Agent Selector > Agent Selector - Skill: `dnyoussef/agent-selector` (Agent Skill, multi-file: 5 files) - Install (CLI): `npx skillmds@latest add dnyoussef/agent-selector` - Raw SKILL.md: https://api.skillmd.com/api/skills/dnyoussef/agent-selector/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: DNYoussef (https://skillmd.com/u/dnyoussef) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dnyoussef/agent-selector --- /*============================================================================*/ /* AGENT-SELECTOR SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: agent-selector version: 2.1.0 description: | [assert|neutral] Intelligent agent selection from 203-agent registry using semantic matching and capability analysis [ground:given] [conf:0.95] [state:confirmed] category: orchestration tags: - general author: System cognitive_frame: primary: evidential goal_analysis: first_order: "Execute agent-selector workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic orchestration processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "agent-selector", category: "orchestration", version: "2.1.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Evidential", source: "Turkish", force: "How do you know?" } [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: ["agent-selector", "orchestration", "workflow"], context: "user needs agent-selector capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # Agent Selector Micro-Skill ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. ## Phase 0: Expertise Loading Before selecting agents: 1. **Detect Domain**: Identify task domain from request 2. **Check Expertise**: Look for `.claude/expertise/agent-selection.yaml` 3. **Load Context**: If exists, load agent performance history and preferences 4. **Apply Configuration**: Use expertise for optimal agent matching ## Purpose Intelligently selects the most appropriate specialized agent from the 203-agent registry based on: - Task requirements and complexity - Agent capabilities and specializations - Domain expertise (category/subcategory) - Tool and MCP requirements - Phase alignment (planning, development, testing, etc.) **Critical for Phase 4 routing** to ensure Claude Code uses specialized agents instead of generic ones. ## When to Use - **Before any Task() invocation** in Phase 5 execution - When planning multi-agent workflows and need optimal agent assignment - When you're unsure which specialized agent to use for a task - To validate that a generic agent name has a specialized alternative ## How It Works **4-Step Process:** 1. **Parse Task Requirements** - Extract domain (backend, frontend, database, testing, etc.) - Identify key capabilities needed (Express.js, PostgreSQL, TDD, etc.) - Determine phase (planning, development, testing, deployment) - Note tool/MCP requirements 2. **Semantic Search (Memory MCP)** - Query Memory MCP with task description - Get top 5-10 candidate agents ranked by similarity - Filter by category/phase if known 3. **Capability Matching** - Score each candidate agent based on: - Exact capability matches (highest priority) - Domain specialization (category/subcategory) - Tool/MCP alignment - Phase alignment - Apply fallback rules if no perfect match 4. **Return Selection + Reasoning** - Selected agent name - Agent source (file path in registry) - Capabilities that matched - Alternatives considered - Selection reasoning ## Usage ```javascript // Skill invocation Skill("agent-selector") // Agent will prompt you for: // 1. Task description (what needs to be done) // 2. Domain hint (optional: backend, frontend, testing, etc.) // 3. Phase hint (optional: development, testing, deployment) // Output: { "selected_agent": "dev-backend-api", "agent_source": "delivery/development/backend/dev-backend-api.md", "agent_category": "delivery/development/backend", "capabilities": ["Express.js", "REST APIs", "JWT", "OpenAPI"], "selection_reasoning": "Specialized backend API agent with exact match for Express.js + REST requirements", "alternatives_considered": [ { "name": "backend-specialist", "score": 0.82, "reason": "Less API-specific, more general backend work" } ], "confidence": 0.95 } ``` ## Integration with Phase 4 Routing **Automatic Integration:** When Phase 4 routing runs, it MUST use this skill (or inline equivalent) to select agents: ```javascript // Phase 4 Routing for (const task of plan.tasks) { // Invoke agent-selector const agentSelection = Skill("agent-selector", { task: task.description, domain: task.domain, phase: task.phase }); // Use selected agent in Phase 5 task.agent = agentSelection.selected_agent; task.agent_source = agentSelection.agent_source; task.agent_capabilities = agentSelection.capabilities; task.agent_reasoning = agentSelection.selection_reasoning; } ``` ## Agent Selection Criteria (Priority Order) 1. **Exact Capability Match** (score: 1.0) - Agent metadata lists exact task requirement - Example: "Express.js API development" → dev-backend-api 2. **Domain Specialization** (score: 0.9) - Agent is in correct category/subcategory - Example: Backend task → delivery/development/backend agents 3. **Tool Requirements** (score: 0.8) - Agent has required tools/MCP servers - Example: Needs Post /*----------------------------------------------------------------------------*/ /* 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/orchestration/agent-selector/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "agent-selector-{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] AGENT_SELECTOR_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]