Design

Design (Choose Code Pattern)

Overview

Pick the simplest design that fits, then map it to a code pattern only if it buys you clear leverage (change isolation, testability, reuse, or performance).

In TypeScript systems, also watch for “complications” that patterns can accidentally amplify (hidden lifetimes, implicit throw, unchecked boundary data, cyclic deps). Prefer patterns that keep boundaries and ownership explicit.

If the main pressure is system-level (multiple services/processes, partial failures, retries/idempotency, sagas, event-driven architecture, domain boundaries), use architecture first; then come back here to pick any code patterns needed for the in-process implementation.

If you’re standardizing cross-cutting boundary behavior across multiple services, consider extracting the primitive into a shared package (see platform) so the pattern becomes a consistent “golden path” instead of copy/paste.

Workflow

0. Load archobs data (required): Run archobs show risks --format json and archobs show clusters --format json to get risk scores and coupling signals for the files under consideration. Use xnbr to identify files bridging multiple concerns, hubness to find fan-in bottlenecks, and cluster leakage to see where boundaries are porous. This data helps narrow the pattern choice — e.g., high xnbr suggests Facade or Strategy; high hubness suggests Mediator. If the artifacts do not exist, run archobs report --repo <path> --out .archobs --suggestions-provider rules and wait for it to complete before continuing.

1. Decide whether the context is scriptic vs systemic (short-lived script vs long-lived system). Set policies for boundary validation, error semantics, and ownership/lifetimes.

2. Restate the problem as: what varies and what must stay stable (API, data model, timing, performance). 2b. Pattern Longevity Check (conditional — run when the selected pattern wraps or isolates an external dependency):

   intel forecast    # lifecycle phase for the wrapped dependency
   

   Decision mapping: See Lifecycle Decision Mapping — Design: Pattern Longevity for lifecycle phase → pattern adjustment tables and compound signal (archobs x forecast) implications.

3. Identify the main pressure:

   • Creation pressure: hard-to-test construction, many variants, environment-specific families.
   • Structure pressure: wrapping/combining objects, incompatible interfaces, indirection, memory sharing.
   • Behavior pressure: pluggable algorithms, eventing, pipelines, undo, state-dependent behavior.

4. Pick 1 primary pattern (avoid "pattern soup"). Add a 2nd only if it addresses a different pressure.

5. Stress-test the decision (if 2+ viable approaches exist; skip for single viable approach):

   • Assumptions: What are facts vs assumptions? Which assumption is least certain — how will we validate it? Cross-reference with pattern longevity check from step 2b (if applicable). (include in output trade-offs)
   • Second-Order Effects: What happens next week / next quarter / next year? What new coupling or failure mode does this create? If this pattern choice fails in 6-12 months, what likely caused failure? Cross-reference with pattern longevity check from step 2b (if applicable). (include in output trade-offs)
   • Opportunity Cost: What are we saying "no" to with this pattern choice? Are we favoring this due to sunk cost, familiarity, or novelty? (include in output trade-offs)
   • If probe output already exists from an earlier Define-stage skill in this flow (including workflow orchestration), refine it instead of re-running.

6. Validate with 2 examples: a "happy path" and a likely future change.

7. Confirm the choice reduces coupling and increases testability (or has a clear perf win).

Clarifying Questions

• Is this scriptic (one-off) or systemic (long-lived)? Who owns startup/shutdown?
• What is the stable API/contract we must preserve?
• What changes most often: implementations, algorithms, steps, object graphs, external systems?
• Are we at an IO boundary (HTTP/DB/fs/events/env)? What is unknown and how will it be decoded?
• What are the expected failures vs truly unknown failures? Should errors be signified (Result/tagged unions)?
• Do we need cancellation/backpressure/timeouts (AbortSignal) or long-running “agents”?
• Do we need undo/redo, queuing, retries, caching, auth, logging, or other cross-cutting concerns?
• Are there many similar objects (memory pressure) or many collaborators (dependency explosion)?

Pattern Chooser (Cheat Sheet)

Creational

• Factory Method: callers want an interface; subclasses/modules choose which concrete product to create.
• Abstract Factory: pick an “environment” (e.g., OS/vendor) and create a compatible family of products.
• Builder: object has many optional parts or multiple representations; construction must be stepwise/validated.
• Prototype: cloning is cheaper/cleaner than constructing; you must define copy semantics explicitly.
• Singleton (use sparingly): exactly one instance is required; prefer DI/container-managed lifetimes instead.

Structural

• Adapter: translate one interface to another to integrate a legacy/third-party API.
• Bridge: split abstraction from implementation so each can vary independently (two axes of change).
• Composite: treat individual objects and object trees uniformly.
• Decorator: add optional behavior by wrapping (stackable features).
• Facade: hide a complex subsystem behind a small, stable API.
• Flyweight: lots of similar objects; separate intrinsic vs extrinsic state to reduce memory.
• Proxy: stand-in that controls access (lazy load, cache, auth, remote boundary, rate limit).

Behavioral

• Chain of Responsibility: request flows through a configurable pipeline of handlers.
• Command: represent an action/request as an object (queue, schedule, undo).
• Iterator: traverse a structure without exposing representation; support multiple traversal strategies.
• Mediator: reduce many-to-many coupling; centralize coordination rules.
• Memento: snapshot/restore state (undo/redo) without exposing internals.
• Observer: publish/subscribe updates; multiple listeners react to events.
• State: behavior changes as state changes; states own transitions/behaviors.
• Strategy: swap algorithms behind a stable interface; choose at runtime/config.
• Template Method: stable algorithm skeleton with overridable steps (often via hooks; use inheritance only when it already fits).
• Visitor: add new operations over a stable object structure without changing the element classes.

Common Confusions

• Decorator vs Proxy vs Adapter vs Facade:
  • Decorator adds behavior; Proxy controls access; Adapter converts interface; Facade simplifies a subsystem.
• Strategy vs State vs Template Method:
  • Strategy chooses an algorithm; State changes behavior based on internal state; Template Method fixes skeleton + overrides steps.
• Factory Method vs Abstract Factory vs Builder:
  • Factory Method picks a product; Abstract Factory picks a compatible family; Builder controls stepwise construction.

Guardrails

• Prefer simpler refactors first: extract functions, introduce interfaces, compose objects, use DI.
• Avoid patterns that force inheritance when composition would do (especially Template Method/Singleton).
• Remember Template Method can be implemented without inheritance in TS (template function + step hooks); don’t default to base classes.
• Keep “pattern seams” small: a tiny interface plus focused implementations.
• In systemic code, avoid top-level side effects; wire dependencies in a composition root and keep lifetimes explicit.
• If the change axis is unclear, prototype with a simple interface + two implementations before formalizing.

References

• Empirical coupling data to inform pattern choice: archobs
• If the pressure is cross-service/system-level: architecture
• If you need a concrete implementation guide: patterns-creational, patterns-structural, patterns-behavioral
• If the seam should be shared across services: platform
• If you're in TypeScript and hitting systemic constraints (boundaries/lifetimes/errors): typescript
• Structured-thinking probes + templates: ../references/ (checklists for inline probes, templates for escalation)

Output Template

When recommending a pattern, return:

• 1–2 sentences: pattern + why it fits this problem (what changes, what stays stable).
• Trade-offs and 1 alternative ("no pattern" option included), with assumptions (facts vs assumptions) and opportunity costs if probes were run.
• A minimal implementation plan (roles/interfaces, wiring point, tests).
• If implementing: small skeleton + one example call site.