AI Agents Development — Production Skill Hub

When to Use This Skill

• Designing an agent (LLM-based, tool-based, OS-based, or multi-agent).
• Scoping capability maturity and rollout risk for new agent behaviors.
• Creating action loops, plans, workflows, or delegation logic.
• Writing tool definitions, MCP tools, schemas, or validation logic.
• Generating RAG pipelines, retrieval modules, or context injection.
• Building memory systems (session, long-term, episodic, task).
• Creating evaluation harnesses, observability plans, or safety gates.
• Preparing CI/CD, rollout, deployment, or production operational specs.
• Producing any template in

  /references/

  or

  /assets/

  .
• Implementing MCP servers or integrating Model Context Protocol.
• Setting up agent handoffs and orchestration patterns.
• Configuring multi-layer guardrails and safety controls.
• Evaluating whether to build an agent (build vs not decision).
• Calculating agent ROI, token costs, or cost/benefit analysis.
• Assessing hallucination risk and mitigation strategies.
• Deciding when to kill an agent project (kill triggers).
• For prompt scaffolds, retrieval tuning, or security depth, see Scope Boundaries below.

Scope Boundaries (Use These Skills for Depth)

• Prompt scaffolds & structured outputs → ai-prompt-engineering
• RAG retrieval & chunking → ai-rag
• Search tuning (BM25/HNSW/hybrid) → ai-rag
• Security/guardrails → ai-mlops
• Inference optimization → ai-llm-inference

Default Workflow (Production)

• Pick an architecture with the Decision Tree (below); default to workflow/FSM/DAG for production.
• Draft an agent spec with

  assets/core/agent-template-standard.md

  (or

  assets/core/agent-template-quick.md

  ).
• Specify tools and handoffs with JSON Schema using

  assets/tools/tool-definition.md

  and

  references/api-contracts-for-agents.md

  .
• Add retrieval only when needed; start with

  assets/rag/rag-basic.md

  and scale via

  assets/rag/rag-advanced.md

  +

  references/rag-patterns.md

  .
• Add eval + telemetry early via

  references/evaluation-and-observability.md

  .
• Run the go/no-go gate with

  assets/checklists/agent-safety-checklist.md

  .
• Plan deploy/rollback and safety controls via

  references/deployment-ci-cd-and-safety.md

  .

Quick Reference

Framework Selection (2026)

references/modern-best-practices.md

Decision Tree: Choosing Agent Architecture

What does the agent need to do?
    ├─ Answer questions from knowledge base?
    │   ├─ Simple lookup? → RAG Agent (LangChain/LlamaIndex + vector DB)
    │   └─ Complex multi-step? → Agentic RAG (iterative retrieval + reasoning)
    │
    ├─ Perform external actions (APIs, tools, functions)?
    │   ├─ 1-3 tools, linear flow? → Tool-Using Agent (LangGraph + MCP)
    │   └─ Complex workflows, branching? → Planning Agent (ReAct/Plan-Execute)
    │
    ├─ Write/modify code autonomously?
    │   ├─ Single file edits? → Tool-Using Agent with code tools
    │   └─ Multi-file, issue resolution? → Code/SWE Agent (HyperAgent pattern)
    │
    ├─ Delegate tasks to specialists?
    │   ├─ Fixed workflow? → Multi-Agent Sequential (A → B → C)
    │   ├─ Manager-Worker? → Multi-Agent Hierarchical (Manager + Workers)
    │   └─ Dynamic routing? → Multi-Agent Group Chat (collaborative)
    │
    ├─ Control desktop/browser?
    │   └─ OS Agent (Anthropic Computer Use + MCP for system access)
    │
    └─ Hybrid (combination of above)?
        └─ Planning Agent that coordinates:
            - Tool-using for actions (MCP)
            - RAG for knowledge (MCP)
            - Multi-agent for delegation (A2A)
            - Code agents for implementation

• Use MCP for: Tool access, data retrieval, single-agent integration
• Use A2A for: Agent-to-agent handoffs, multi-agent coordination, task delegation

Core Concepts (Vendor-Agnostic)

Control Flow Options

• Reactive: direct tool routing per user request (fast, brittle if unbounded).
• Workflow (FSM/DAG): explicit states and transitions (default for deterministic production).
• Planner/Executor: plan with strict budgets, then execute step-by-step (use when branching is unavoidable).
• Orchestrated multi-agent: separate roles with validated handoffs (use when specialization is required).

Memory Types (Tradeoffs)

• Short-term (session): cheap, ephemeral; best for conversational continuity.
• Episodic (task): scoped to a case/ticket; supports audit and replay.
• Long-term (profile/knowledge): high risk; requires consent, retention limits, and provenance.

Failure Handling (Production Defaults)

• Classify errors: retriable vs fatal vs needs-human.
• Bound retries: max attempts, backoff, jitter; avoid retry storms.
• Fallbacks: degraded mode, smaller model, cached answers, or safe refusal.

Do / Avoid

• Do keep state explicit and serializable (replayable runs).
• Do enforce tool allowlists, scopes, and idempotency for side effects.
• Do log traces/metrics for model calls and tool calls (OpenTelemetry GenAI semantic conventions: https://opentelemetry.io/docs/specs/semconv/gen-ai/).

• Avoid runaway autonomy (unbounded loops or step counts).
• Avoid hidden state (implicit memory that cannot be audited).
• Avoid untrusted tool outputs without validation/sanitization.

Navigation: Economics & Decision Framework

Should You Build an Agent?

• Build vs Not Decision Framework -

  references/build-vs-not-decision.md

  • 10-second test (volume, cost, error tolerance)
  • Red flags and immediate disqualifiers
  • Alternatives to agents (usually better)
  • Full decision tree with stage gates
  • Kill triggers during development and post-launch
  • Pre-build validation checklist

Agent ROI & Token Economics

• Agent Economics -

  references/agent-economics.md

  • Token pricing by model (January 2026)
  • Cost per task by agent type
  • ROI calculation formula and tiers
  • Hallucination cost framework and mitigation ROI
  • Investment decision matrix
  • Monthly tracking dashboard

Navigation: Core Concepts & Patterns

Governance & Maturity

• Agent Maturity & Governance -

  references/agent-maturity-governance.md

  • Capability maturity levels (L0-L4)
  • Identity & policy enforcement
  • Fleet control and registry management
  • Deprecation rules and kill switches

Modern Best Practices

• Modern Best Practices -

  references/modern-best-practices.md

  • Model Context Protocol (MCP)
  • Agent-to-Agent Protocol (A2A)
  • Agentic RAG (Dynamic Retrieval)
  • Multi-layer guardrails
  • LangGraph over LangChain
  • OpenTelemetry for agents

Context Management

• Context Engineering -

  references/context-engineering.md

  • Progressive disclosure
  • Session management
  • Memory provenance
  • Retrieval timing
  • Multimodal context

Core Operational Patterns

• Operational Patterns -

  references/operational-patterns.md

  • Agent loop pattern (PLAN → ACT → OBSERVE → UPDATE)
  • OS agent action loop
  • RAG pipeline pattern
  • Tool specification
  • Memory system pattern
  • Multi-agent workflow
  • Safety & guardrails
  • Observability
  • Evaluation patterns
  • Deployment & CI/CD

Navigation: Protocol Implementation

• MCP Practical Guide -

  references/mcp-practical-guide.md

  Building MCP servers, tool integration, and standardized data access
• MCP Server Builder -

  references/mcp-server-builder.md

  End-to-end checklist for workflow-focused MCP servers (design → build → test)
• A2A Handoff Patterns -

  references/a2a-handoff-patterns.md

  Agent-to-agent communication, task delegation, and coordination protocols
• Protocol Decision Tree -

  references/protocol-decision-tree.md

  When to use MCP vs A2A, decision framework, and selection criteria

Navigation: Agent Capabilities

• Agent Operations -

  references/agent-operations-best-practices.md

  Action loops, planning, observation, and execution patterns
• RAG Patterns -

  references/rag-patterns.md

  Contextual retrieval, agentic RAG, and hybrid search strategies
• Memory Systems -

  references/memory-systems.md

  Session, long-term, episodic, and task memory architectures
• Tool Design & Validation -

  references/tool-design-specs.md

  Tool schemas, validation, error handling, and MCP integration

Skill Packaging & Sharing

• Skill Lifecycle -

  references/skill-lifecycle.md

  Scaffold, validate, package, and share skills with teams (Slack-ready)
• API Contracts for Agents -

  references/api-contracts-for-agents.md

  Request/response envelopes, safety gates, streaming/async patterns, error taxonomy
• Multi-Agent Patterns -

  references/multi-agent-patterns.md

  Manager-worker, sequential, handoff, and group chat orchestration
• OS Agent Capabilities -

  references/os-agent-capabilities.md

  Desktop automation, UI grounding, and computer use patterns
• Code/SWE Agents -

  references/code-swe-agents.md

  SE 3.0 paradigm, autonomous coding patterns, SWE-Bench, HyperAgent architecture

Navigation: Production Operations

• Evaluation & Observability -

  references/evaluation-and-observability.md

  OpenTelemetry GenAI, metrics, LLM-as-judge, and monitoring
• Deployment, CI/CD & Safety -

  references/deployment-ci-cd-and-safety.md

  Multi-layer guardrails, HITL controls, NIST AI RMF, production checklists

Navigation: Templates (Copy-Paste Ready)

Checklists

• Agent Design & Safety Checklist -

  assets/checklists/agent-safety-checklist.md

  Go/No-Go safety gate: permissions, HITL triggers, eval gates, observability, rollback

Core Agent Templates

• Standard Agent Template -

  assets/core/agent-template-standard.md

  Full production spec: memory, tools, RAG, evaluation, observability, safety
• Specialized Agent Template -

  assets/core/agent-template-specialized.md

  Domain-specific agents with custom capabilities and constraints
• Quick Agent Template -

  assets/core/agent-template-quick.md

  Minimal viable agent for rapid prototyping

RAG Templates

• Basic RAG -

  assets/rag/rag-basic.md

  Simple retrieval-augmented generation pipeline
• Advanced RAG -

  assets/rag/rag-advanced.md

  Contextual retrieval, reranking, and agentic RAG patterns
• Hybrid Retrieval -

  assets/rag/hybrid-retrieval.md

  Semantic + keyword search with BM25 fusion

Tool Templates

• Tool Definition -

  assets/tools/tool-definition.md

  MCP-compatible tool schemas with validation and error handling
• Tool Validation Checklist -

  assets/tools/tool-validation-checklist.md

  Testing, security, and production readiness checks

Multi-Agent Templates

• Manager-Worker Template -

  assets/multi-agent/manager-worker-template.md

  Orchestration pattern with task delegation and result aggregation
• Evaluator-Router Template -

  assets/multi-agent/evaluator-router-template.md

  Dynamic routing with quality assessment and domain classification

Service Layer Templates

• FastAPI Agent Service -

  ../dev-api-design/assets/fastapi/fastapi-complete-api.md

  Auth, pagination, validation, error handling; extend with model lifespan loads, SSE, background tasks

External Sources Metadata

• Curated References -

  data/sources.json

  Authoritative sources spanning standards, protocols, and production agent frameworks

Shared Utilities (Centralized patterns — extract, don't duplicate)

• ../software-clean-code-standard/utilities/llm-utilities.md — Token counting, streaming, cost estimation
• ../software-clean-code-standard/utilities/error-handling.md — Effect Result types, correlation IDs
• ../software-clean-code-standard/utilities/resilience-utilities.md — p-retry v6, circuit breaker for API calls
• ../software-clean-code-standard/utilities/logging-utilities.md — pino v9 + OpenTelemetry integration
• ../software-clean-code-standard/utilities/observability-utilities.md — OpenTelemetry SDK, tracing, metrics
• ../software-clean-code-standard/utilities/testing-utilities.md — Test factories, fixtures, mocks
• ../software-clean-code-standard/references/clean-code-standard.md — Canonical clean code rules (

  CC-*

  ) for citation

Trend Awareness Protocol

data/sources.json

Trigger Conditions

• "What's the best agent framework for [use case]?"
• "What should I use for [multi-agent/tool use/orchestration]?"
• "What's the latest in AI agents?"
• "Current best practices for [agent architecture/MCP/A2A]?"
• "Is [LangGraph/CrewAI/AutoGen] still relevant in 2026?"
• "[Agent framework A] vs [Agent framework B]?"
• "Best way to build [coding agent/RAG agent/OS agent]?"
• "What MCP servers are available?"

Required Searches

1. Search:

   "AI agent frameworks best practices 2026"

2. Search:

   "[LangGraph/CrewAI/AutoGen/Semantic Kernel] comparison 2026"

3. Search:

   "AI agent trends January 2026"

4. Search:

   "MCP servers available 2026"

What to Report

• Current landscape: What agent frameworks are popular NOW
• Emerging trends: New patterns gaining traction (MCP, A2A, agentic coding)
• Deprecated/declining: Frameworks or patterns losing relevance
• Recommendation: Based on fresh data, not just static knowledge

Example Topics (verify with fresh search)

• Agent frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, Pydantic AI)
• MCP ecosystem (available servers, new integrations)
• Agentic coding (Codex CLI, Claude Code, Cursor, Windsurf, Cline)
• Multi-agent patterns (hierarchical, collaborative, competitive)
• Tool use protocols (MCP, function calling)
• Agent evaluation (SWE-Bench, AgentBench, GAIA)
• OS/computer use agents (computer-use APIs, browser automation)

Related Skills

Core Dependencies

• ../ai-llm/

  - LLM patterns, prompt engineering, and model selection for agents

• ../ai-rag/

  - Deep RAG implementation: chunking, embedding, reranking

• ../ai-prompt-engineering/

  - System prompt design, few-shot patterns, reasoning strategies

Production & Operations

• ../qa-observability/

  - OpenTelemetry, metrics, distributed tracing

• ../software-security-appsec/

  - OWASP Top 10, input validation, secure tool design

• ../ops-devops-platform/

  - CI/CD pipelines, deployment strategies, infrastructure

Supporting Patterns

• ../dev-api-design/

  - REST/GraphQL design for agent APIs and tool interfaces

• ../ai-mlops/

  - Model deployment, monitoring, drift detection

• ../qa-debugging/

  - Agent debugging, error analysis, root cause investigation

Usage Notes

• Modern Standards: Default to MCP for tools, agentic RAG for retrieval, handoff-first for multi-agent
• Lightweight SKILL.md: Use this file for quick reference and navigation
• Drill-down resources: Reference detailed resources for implementation guidance
• Copy-paste templates: Use templates when the user asks for structured artifacts
• External sources: Reference

  data/sources.json

  for authoritative documentation links
• No theory: Never include theoretical explanations; only operational steps

Key Modern Migrations

• Custom APIs → Model Context Protocol (MCP)
• Static RAG → Agentic RAG with contextual retrieval
• Ad-hoc handoffs → Versioned handoff APIs with JSON Schema
• Single guardrail → Multi-layer defense (5+ layers)
• LangChain agents → LangGraph stateful workflows
• Custom observability → OpenTelemetry GenAI standards
• Model-centric → Context engineering-centric

AI-Native SDLC Template

• Use

  assets/agent-template-ainative-sdlc.md

  for the Delegate → Review → Own runbook (guardrails + outputs checklist).