agent-architecture

A Claude Code skill that turns Claude into an agent-design expert.

Ask Claude to design an AI agent and, by default, it improvises from memory — plausible, but generic, and blind to the failure modes that bite in production. This skill gives Claude a structured, battle-tested body of knowledge — the 21 agentic design patterns from Antonio Gulli's Agentic Design Patterns — so that instead of guessing, it reasons from a real catalog: which patterns your problem needs, how they trade off, and how they compose into a reliable system.

It changes how Claude thinks about agent design, not just what it knows.

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Why this is useful

A powerful LLM is not an agent. Making one reliable takes architecture — how it breaks down a task, calls tools, remembers, recovers from errors, and knows when to escalate to a human. That architecture is a solved problem: there are ~21 recurring patterns (the Gang-of-Four equivalents for the agent era). This skill puts all of them at Claude's fingertips, as concepts you can apply in any framework (LangChain, CrewAI, the raw Anthropic/OpenAI/Gemini SDK, or Google ADK). Code is deliberately excluded — the patterns are durable; framework choices aren't.

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What changes — with vs. without the skill

You: "Design a text-to-SQL agent that runs queries against our production database."

Without the skill — Claude improvises:

"I'd use an LLM to generate SQL from the question, run it, and return the results. You could add error handling and maybe let it retry."

Reasonable, but vague. It misses the schema-grounding problem, has no quality loop, and — dangerously — no safety gate before a generated query hits production.

With the skill — Claude reasons from the catalog:

"This needs five patterns working together:

• RAG to ground generation in your real schema (don't trust the model's guess at table names)
• Tool Use as the executor — but your code runs the SQL, never the model; and the tool should raise on DB errors, not return them as strings, so failures aren't silently swallowed
• Reflection with a separate critic (a 'meticulous SQL reviewer' persona) — self-review is biased; review the SQL against the schema before executing, capped at 3 iterations for cost
• Human-in-the-Loop as a write-gate — read-only SELECTs run autonomously; anything mutating escalates for approval (escalation is just another tool)
• Exception Handling to retry transient failures and feed permanent ones back into the reflection loop

Here's the runtime flow…"

Same question. The second answer is specific, ordered, and safe — it names the non-obvious pitfalls (raise-don't-return, biased self-review, the model-proposes / code-executes boundary) that come straight from the patterns, not from improvisation.

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What becomes possible

Loaded, the skill lets you:

• Pick the right patterns fast — describe a problem, get the minimal set of patterns that solves it (most agents need 3–6), with the trade-offs spelled out.
• Go deep on any one — get a pattern's full mechanics, real-world use cases, and the production pitfalls, without code noise.
• Design compositions — see how patterns stack into one system (a research assistant = Planning + Tool Use + Multi-Agent + Reflection + Memory).
• Pressure-test a design — ask "what am I missing?" and Claude checks your architecture against the full catalog (no guardrails? no eval? no recovery?).
• Stay framework-agnostic — decide what to build here; implement the how in whatever stack you use.

It's a design-phase tool: it makes the architecture decisions sharp before you write code.

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How to use it

Just talk to Claude about agent design. The skill activates on questions like:

• "Which patterns should this agent use?"
• "Design an agent that does X."
• "What's the difference between Routing and Planning?"
• "Review this agent design for what's missing."
• …or naming any pattern (RAG, Reflection, MCP, A2A, guardrails…).

Claude loads a one-screen index of all 21 patterns, then pulls the full detail for whichever ones your problem needs — so the right knowledge is in context exactly when it matters.

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The 21 patterns at a glance

	Group	Patterns
🧩	Foundations	Prompt Chaining · Routing · Parallelization · Reflection · Tool Use · Planning · Multi-Agent
🧠	State & Knowledge	Memory Management · Learning & Adaptation · Model Context Protocol (MCP) · Goal Setting & Monitoring
🛡️	Robustness	Exception Handling & Recovery · Human-in-the-Loop · Knowledge Retrieval (RAG)
🚀	Advanced & Scaling	Inter-Agent Comms (A2A) · Resource-Aware Optimization · Reasoning Techniques · Guardrails / Safety · Evaluation & Monitoring · Prioritization · Exploration & Discovery

_{Plus appendices (prompting techniques · frameworks overview · GUI/CLI/coding agents · AgentSpace), a worked composition example, and a glossary.}

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Install

As a plugin (recommended) — one-command install from within Claude Code:

/plugin marketplace add eshwarvijay/agent-architecture
/plugin install agent-architecture

Or manually — clone and symlink the skill:

git clone https://github.com/eshwarvijay/agent-architecture ~/agent-architecture
ln -s ~/agent-architecture/skills/agent-architecture ~/.claude/skills/agent-architecture

Either way — next time you ask Claude an agent-design question, the skill kicks in.

No Claude Code? Every file is plain markdown. Point any assistant at skills/agent-architecture/: "Read SKILL.md and the relevant patterns/ files, then design X." — or just browse the patterns here on GitHub.

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Distilled from Antonio Gulli, “Agentic Design Patterns” (2025) — concepts only, a derived reference; see the book for full text and code. Snapshot: mid-2025, so the patterns hold but specific model/API details may have moved on.

🍳 psst… you found the kitchen

_{Patterns are the recipe. Use the fewest that work — 3–6, not all 21. Over-season and your clean paneer butter masala turns into a 30-spice mess no one can debug.}