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Architecture Pattern

Architecture Patterns provide reusable solutions to commonly occurring software and system design problems. They offer proven templates for organizing code, components, and interactions across distributed systems, microservices, cloud-native applications, and enterprise software.

agent aware

Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.

Kin Score

API Evangelist profiles Architecture Pattern the way a machine reads it — 38 machine-readable artifacts across 3 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Architecture Pattern scores 49.7/100 (developing), with a separate agent-readiness read of 39/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 49.7/100 · developing
Contract Quality 14.0 / 25
Developer Ergonomics 3.9 / 20
Commercial Clarity 7.9 / 20
Operational Transparency 4.8 / 13
Governance 10.4 / 12
Discoverability 8.8 / 10
Agent readiness — 39/100 · agent aware
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Architecture Pattern

Each block below is one kind of artifact we hold for Architecture Pattern. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

APIs 3

Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.

Individual APIs this provider publishes, each with its own machine-readable definition.

Architecture Pattern Domains API

The Domains API from Architecture Pattern — 1 operation(s) for domains.

Architecture Pattern Patterns API

The Patterns API from Architecture Pattern — 3 operation(s) for patterns.

Architecture Pattern Trade-offs API

The Trade-offs API from Architecture Pattern — 1 operation(s) for trade-offs.

Pricing Plans 1

Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.

Published pricing tiers and plan structures.

Rate Limits 1

Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.

Documented rate limits and quota policies.

FinOps 1

Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.

Cost, billing, and metering signals for API financial operations.

Features 5

The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.

Notable capabilities this provider offers.

Pattern Catalog

Comprehensive catalog of architecture patterns for microservices, distributed systems, and cloud-native applications.

Problem-Solution Framework

Each pattern includes problem statement, solution approach, and known trade-offs.

Pattern Language

Related patterns organized into a coherent pattern language for navigating complex architecture decisions.

Real-World Examples

Patterns illustrated with real-world implementations from production systems.

Decision Support

Guidance for selecting appropriate patterns based on context and constraints.

Semantic Vocabularies 1

JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.

JSON-LD contexts and semantic vocabularies used across these APIs.

Architecture Pattern Api Context

6 classes · 0 properties

JSON-LD

Spectral Rules 2

Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.

Architecture Pattern API Rules

5 rules · 3 warnings

SPECTRAL

Architecture Pattern API Rules

19 rules · 8 errors · 10 warnings

SPECTRAL

JSON Schema 6

Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.

Standalone JSON Schema definitions for this provider's data models.

DomainList

2 properties

JSON SCHEMA

Domain

5 properties

JSON SCHEMA

PatternList

4 properties

JSON SCHEMA

Pattern

12 properties

JSON SCHEMA

TradeoffList

2 properties

JSON SCHEMA

Tradeoff

7 properties

JSON SCHEMA

JSON Structure 6

JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.

JSON Structure definitions describing this provider's data shapes.

Examples 6

Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.

Example request and response payloads for these APIs.

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Agentic Access 1

An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.

Recommended x-agentic-access execution contracts for AI agents.

Architecture Pattern Agentic Access

5 operations

5 operations · 0 acting

AGENTIC

Use Cases 4

What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.

What developers build with this provider.

Microservices Design

Apply patterns for decomposing monolithic applications into microservices.

Distributed Systems

Reference patterns for handling distributed computing challenges like consistency and availability.

Cloud Migration

Select cloud-native patterns when migrating on-premises applications to cloud platforms.

Architecture Review

Evaluate architecture decisions against proven patterns and identify improvement areas.

Resources

Every other property we hold for Architecture Pattern — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Get Started 1

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 3

Pagination, idempotency, versioning, errors, and events

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 1

Authentication, authorization, and security posture

Company 1

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/architecture-pattern · machine-readable index on apis.io