oreilly-design-reference

name	oreilly-design-reference
description	O'Reilly book reference lookup for software design decisions. Coding agents MUST use this skill whenever making or reviewing any design decision — choosing an architecture pattern, selecting a data structure, structuring a module, evaluating a library, deciding on an API contract, applying a design pattern, weighing trade-offs between approaches, or any moment where a choice between two or more implementation strategies comes up. The O'Reilly MCP handles the actual book search; this skill tells you how and when to invoke it. Trigger even for seemingly small decisions (naming, layering, concurrency model, error handling strategy) — the best engineers reach for authoritative references before committing to an approach.
metadata	{"author":"marco","version":"1.0.0","category":"software-engineering","tags":"oreilly, design-decisions, architecture, patterns, references, coding-agent"}

O'Reilly Design Reference

A skill for coding agents that ensures every significant design decision is grounded in authoritative, book-level knowledge via the O'Reilly MCP.

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Prime Directive

Before committing to any design decision, search O'Reilly for references.

This is not optional. Even if you are confident in an approach, a 5-second O'Reilly lookup either confirms your direction with authoritative backing or surfaces a better alternative you hadn't considered. The O'Reilly MCP does the heavy lifting — your job is to know when and how to invoke it.

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When to Trigger a Reference Lookup

Invoke the O'Reilly MCP search on any of the following signals:

Architecture & Structure

• Choosing between monolith, microservices, modular monolith, event-driven, or layered architectures
• Deciding on module boundaries, package layout, or dependency direction
• Evaluating hexagonal/ports-and-adapters, clean architecture, or DDD patterns
• Designing an API (REST, GraphQL, gRPC, message-based)

Design Patterns & Principles

• Applying or questioning a GoF design pattern (Factory, Strategy, Observer, …)
• Applying SOLID, GRASP, or other OO principles
• Deciding between composition and inheritance
• Identifying code smells and choosing refactoring techniques

Data & State

• Choosing a data structure (tree vs. graph, list vs. set, …)
• Designing a schema or domain model
• Evaluating caching strategies, consistency models, or storage engines
• Deciding on state management approach (immutability, event sourcing, CQRS, …)

Concurrency & Performance

• Choosing between threading, async/await, actor model, or CSP
• Designing for scalability or latency
• Evaluating locking strategies, lock-free structures, or backpressure

Error Handling & Resilience

• Choosing an error propagation strategy (exceptions vs result types vs panic)
• Designing retry, circuit-breaker, or fallback logic
• Evaluating fault-isolation boundaries

Testing & Quality

• Deciding on a testing strategy (unit vs integration vs contract vs E2E)
• Choosing test doubles (mock vs stub vs fake vs spy)
• Evaluating TDD or BDD workflows

Language & Library Choices

• Evaluating a library or framework against alternatives
• Deciding on a serialization format (JSON, Protobuf, Avro, …)
• Choosing between language idioms (e.g., dataclasses vs TypedDict in Python)

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How to Use the O'Reilly MCP

The O'Reilly MCP is the tool that performs the actual book and content search. When it is connected, coding agents should call it directly with a well-formed query. Do not attempt to answer design questions from memory alone when this MCP is available.

Query Construction

Good queries are specific. Include:

1. The decision type (pattern, architecture, data structure, …)
2. The domain or context (distributed systems, frontend, ML pipelines, …)
3. Optional: language or ecosystem (Python, Go, TypeScript, …)

Examples of good queries:

"event sourcing vs CQRS trade-offs distributed systems"
"repository pattern domain-driven design"
"async error handling Python"
"observer pattern vs event bus"
"database sharding strategies horizontal scaling"
"dependency injection vs service locator"
"API versioning strategies REST"
"circuit breaker pattern resilience"

Examples of poor queries (too vague):

"design patterns"         # too broad
"how to code"             # not a design decision
"Python tutorial"         # not a design question

Lookup Workflow

1. IDENTIFY the design decision at hand
        ↓
2. FORMULATE a specific O'Reilly search query
        ↓
3. CALL the O'Reilly MCP search tool
        ↓
4. REVIEW the returned book excerpts, titles, and chapter references
        ↓
5. CITE the relevant source(s) in your explanation or PR comment
        ↓
6. APPLY the guidance — or explicitly note why you're diverging from it

Multiple Perspectives

For consequential decisions (architectural choices, public API design, major refactors), run 2–3 searches with different angles:

Search 1: the pattern you're considering ("event sourcing implementation")
Search 2: the alternative ("CQRS without event sourcing")
Search 3: trade-off framing ("event sourcing drawbacks complexity")

This surfaces the full picture before committing.

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How to Present Findings

When reporting back to the developer, structure your reference-backed answer:

### Design Decision: [brief label]

**Recommended approach:** [your recommendation]

**O'Reilly references:**
- *[Book Title]* — [Author]: [one-sentence summary of relevant guidance]
- *[Book Title]* — [Author]: [one-sentence summary of relevant guidance]

**Trade-offs considered:**
- ✅ [Advantage of chosen approach]
- ⚠️  [Trade-off or caveat]

**Why not [alternative]:** [brief reasoning, ideally backed by a reference]

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Citing References in Code

For design decisions baked into the codebase, add a reference comment:

# Architecture: Hexagonal (Ports & Adapters)
# Ref: "Architecture Patterns with Python" — Percival & Gregory, Ch. 2
class OrderRepository(AbstractRepository):
    ...

// Pattern: Strategy — delegates algorithm selection to runtime
// Ref: "Design Patterns" — GoF, p. 315
interface PricingStrategy {
  calculate(order: Order): Money;
}

This makes architectural intent explicit and gives future maintainers a learning path.

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When the O'Reilly MCP Is Not Connected

If the O'Reilly MCP is unavailable:

1. Flag it clearly — note that authoritative references could not be retrieved.
2. Use the oop-knowledge skill as a fallback for OOP/pattern decisions (if installed).
3. Fall back to general knowledge but explicitly mark it as unverified: [no O'Reilly reference — recommend manual lookup].
4. Recommend the developer search learning.oreilly.com manually with the query you would have used.

Never silently skip the reference step — always surface the gap.

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Quick-Reference: Common Decision → Query Mapping

Design Decision	Suggested O'Reilly Query
Microservices vs monolith	"microservices trade-offs monolith migration"
Event-driven architecture	"event-driven architecture patterns messaging"
Domain model design	"domain-driven design aggregate bounded context"
Async task queue	"task queue worker pattern async processing"
REST API design	"REST API design best practices versioning"
Database choice	"polyglot persistence database selection patterns"
Dependency injection	"dependency injection inversion of control containers"
Testing strategy	"test pyramid integration testing strategy"
Error handling	"error handling resilience fault tolerance patterns"
Caching	"caching strategies invalidation distributed cache"
Auth/AuthZ	"authentication authorization OAuth JWT patterns"
CI/CD pipeline	"continuous delivery deployment pipeline patterns"