# Agent Creation > Agent Creation - Skill: `majiayu000/agent-creation` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds add majiayu000/agent-creation` - Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/agent-creation/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: majiayu000 (https://skillmd.com/u/majiayu000) - Updated: 2026-09-09 - Page: https://skillmd.com/skills/majiayu000/agent-creation --- /*============================================================================*/ /* AGENT-CREATION SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: agent-creation version: 1.0.0 description: | [assert|neutral] Systematic agent creation using evidence-based prompting principles and 4-phase SOP methodology. Use when creating new specialist agents, refining existing agent prompts, or designing multi-agent syst [ground:given] [conf:0.95] [state:confirmed] category: foundry tags: - foundry - creation - meta-tools author: ruv cognitive_frame: primary: compositional goal_analysis: first_order: "Execute agent-creation workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic foundry processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "agent-creation", category: "foundry", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Compositional", source: "German", force: "Build from primitives?" } [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-creation", "foundry", "workflow"], context: "user needs agent-creation capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ ## Skill Execution Criteria ### When to Use This Skill - Creating new specialist agents with domain-specific expertise - Refining existing agent system prompts for better performance - Designing multi-agent coordination systems - Implementing role-based agent hierarchies - Building production-ready agents with embedded domain knowledge ### When NOT to Use This Skill - For simple one-off tasks that don't need agent specialization - When existing agents already cover the required domain - For casual conversational interactions without systematic requirements - When the task is better suited for a slash command or micro-skill ### Success Criteria - [assert|neutral] primary_outcome: "Production-ready agent with optimized system prompt, clear role definition, and validated performance" [ground:acceptance-criteria] [conf:0.90] [state:provisional] - [assert|neutral] quality_threshold: 0.9 [ground:acceptance-criteria] [conf:0.90] [state:provisional] - [assert|neutral] verification_method: "Agent successfully completes domain-specific tasks with consistent high-quality output, passes validation tests, and integrates with Claude Agent SDK" [ground:acceptance-criteria] [conf:0.90] [state:provisional] ### Edge Cases - case: "Vague agent requirements" handling: "Use Phase 1 (Initial Analysis) to research domain, identify patterns, and clarify scope before proceeding" - case: "Overlapping agent capabilities" handling: "Conduct agent registry search, identify gaps vs duplicates, propose consolidation or specialization" - case: "Agent needs multiple conflicting personas" handling: "Decompose into multiple focused agents with clear coordination pattern" ### Skill Guardrails NEVER: - "Create agents without deep domain research (skipping Phase 1 undermines quality)" - "Use generic prompts without evidence-based techniques (CoT, few-shot, role-based)" - "Skip validation testing (Phase 3) before considering agent production-ready" - "Create agents that duplicate existing registry agents without justification" ALWAYS: - "Complete all 4 phases: Analysis -> Prompt Engineering -> Testing -> Integration" - "Apply evidence-based prompting: Chain-of-Thought for reasoning, few-shot for patterns, clear role definition" - "Validate with diverse test cases and measure against quality criteria" - "Document agent capabilities, limitations, and integration points" ### Evidence-Based Execution self_consistency: "After agent creation, test with same task multiple times to verify consistent outputs and reasoning quality" program_of_thought: "Decompose agent creation into: 1) Domain analysis, 2) Capability mapping, 3) Prompt architecture, 4) Test design, 5) Validation, 6) Integration" plan_and_solve: "Plan: Research domain + identify capabilities -> Execute: Build prompts + test cases -> Verify: Multi-run consistency + edge case handling" # Agent Creation - Systematic Agent Design ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. Evidence-based agent creation following best practices for prompt engineering and agent specialization. --- ## When to Use This Skill Use when creating new specialist agents for specific domains, refining existing agent capabilities, designing multi-agent coordination systems, or implementing role-based agent hierarchies. --- ## 4-Phase Agent Creation SOP ### Phase 1: Specification - Define agent purpose and domain - Identify core capabilities needed - Determine input/output formats - Specify quality criteria **Tools**: Use `resources/scripts/generate_agent.sh` for automated generation ### Phase 2: Prompt Engineering - Apply evidence-based prompting principles - Use Chain-of-Thought for reasoning tasks - Implement few-shot learning with examples (2-5 examples) - Define role and persona clearly **Reference**: See `references/prompting-principles.md` for detailed techniques ### Phase 3: Testing & Vali /*----------------------------------------------------------------------------*/ /* 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/agent-creation/{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-creation-{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_CREATION_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]