📘 Backend API Library Blueprint¶

Implementation alignment (read first)¶

This document mixes three things: (1) what dotnet new connectsoft-api-library produces today, (2) factory DSL / agent conventions, and (3) longer-term or optional follow-up work. Do not treat every section as guaranteed output from a single template run.

Canonical CLI and symbols for the baseline template: API Library Template parameters.

Topic	Baseline template (`ConnectSoft.ApiLibraryTemplate` / `connectsoft-api-library`)
Projects	One library under `src/{name}/` and one `{name}.UnitTests` project, plus solution (`.slnx` / `.sln`), `Directory.Packages.props`, `azure-pipelines.yml`, etc. No separate MockServer host project, no `.factory/` or `blueprints/` folders unless agents add them after scaffold.
Service shape	`I{ApiServiceName}Service` / `{ApiServiceName}Service` (sample default `ExchangeRate`), not a generic `*Client` name unless you choose that as `ApiServiceName`.
TFMs	`net10.0;net9.0;net10.0` on library and tests. `Framework` on `dotnet new` is a primary moniker only (default net10.0).
Auth	Exactly one `AuthenticationType`: `None`, `Basic`, `OAuth`, `OpenIDConnect`, `ApiKey`.
Metrics	Optional via `UseMetrics` (default true).
Tracing	Not generated in-template (no `ActivitySource` scaffold). Use host OpenTelemetry, or ConnectSoft.LibraryTemplate for tracing-oriented library samples.
Tests	MSTest + WireMock.Net in the unit test project (mocked HTTP), not necessarily a separate “integration test project” or ASP.NET mock server repo.
DSL in this doc	Fields like `baseUrl`, `retryPolicy`, `telemetry.tracing` are planning shapes—agents must map them to real template parameters and post-scaffold edits.

Later sections that describe mock server projects, .factory/ metadata trees, per-method ActivitySource spans, or always-on distributed tracing describe target factory behavior or extensions, unless labeled as matching (1) above.

🧭 Introduction and Purpose¶

The Backend API Library Blueprint defines how the AI Software Factory generates reusable, production-ready libraries for interacting with external or internal APIs. These libraries are created from a blueprint definition and implemented via the .NET Core CLI template named:

dotnet new connectsoft-api-library

This blueprint enables agents to rapidly scaffold API client libraries that follow ConnectSoft principles — strong typing, resiliency, logging, optional metrics, and security-first access to remote endpoints. Distributed tracing is a consumer/host concern unless agents add it after scaffold (see alignment table above).

🎯 Purpose¶

The blueprint serves to:

Encapsulate access to REST, GraphQL, gRPC, or proprietary APIs
Provide a typed HTTP interface for application services and other agents
Enable standard configuration, auth, logging, retry policies, etc.
Package libraries into NuGet-distributable modules
Include test harnesses (baseline: WireMock in *.UnitTests); separate mock server or contract projects are optional agent extensions, not the default template output
Document all capabilities via auto-generated usage guides and integration samples

🏭 Use in the Software Factory¶

The blueprint is used when:

Scenario	Trigger
✅ A service needs to consume an external API	Business Analyst Agent or Solution Architect defines integration need
✅ A domain module needs to publish an internal service client	Domain Architect Agent defines module boundary
✅ A third-party service is required in multiple modules	API Engineer Agent declares shared reusable SDK
✅ An AI agent needs to wrap its own function via HTTP	Tooling Agent emits client to call its own generated service

📦 Typical Output Artifacts¶

Artifact	Description
`ConnectSoft.MyCompany.GoogleAnalyticsClient.dll`	Compiled NuGet package
`Http.GoogleAnalyticsClient.cs`	Strongly typed wrapper around `HttpClient`
`GoogleAnalyticsOptions.cs`	Binds to configuration (e.g., API key, base URL)
`I{Service}Service.cs` / `{Service}Service.cs`	Interface-first typed HTTP access (name from `ApiServiceName`)
`tests/{name}.UnitTests/`	MSTest + WireMock scenarios (baseline)
`mock-server/` (optional)	Not from template; add via agents if required
`README.md`	Usage guide with samples
`azure-pipelines.yml`	CI build/test/publish workflow

💡 Blueprint Pattern Class¶

This blueprint belongs to:

🧩 Type: library.blueprint.backend.api
🧪 Domain: sdk, external-integration, internal-client
📐 Pattern: agentic.library.contract+http+resilience+telemetry

Related Blueprint	Purpose
`frontend-library-blueprint.md`	Consumed from frontend codebases (optional proxy wrapper)
`platform-blueprint.md`	May use this library as a package in the host
`agent-microservice-blueprint.md`	Can generate the server-side implementation for this client

✅ Summary¶

The Backend API Library Blueprint standardizes how API clients are created, tested, documented, and published as reusable modules in the platform. It combines strong architectural patterns with agent automation, enabling scalable integration at speed.

🧭 Key Principles and Design Alignment¶

This blueprint is deeply aligned with the foundational principles of the ConnectSoft AI Software Factory, ensuring that every generated API library is cleanly structured, modular, observable, and secure by design.

🧱 Clean Architecture Alignment¶

The backend API library generated by this blueprint follows Clean Architecture by:

Isolating the HTTP logic in Infrastructure layer (no leakage into Domain)
Providing clear interfaces (I{Service}Service.cs from template, or I*Client if agents rename) for injection
Ensuring no business logic resides in the library — it acts as a data access boundary

📂 Example structure:

src/
  {PackageName}/
      I{ApiServiceName}Service.cs
      {ApiServiceName}Service.cs
      {ApiServiceName}ServiceExtensions.cs
      Options/
      Metrics/          (if UseMetrics)
      Handlers/
      Resilience/

🧩 Domain-Driven Design (DDD) Principles¶

Clients are named after bounded contexts or external APIs (Analytics, Payments, CRM)
Optionally include value objects or response DTOs (from OpenAPI or manually modeled)
Designed to fit cleanly inside domain service layers, not UI or infrastructure mixing

🔁 Event-Driven and Observable¶

Baseline template: ILogger usage and (when UseMetrics is true) System.Diagnostics.Metrics patterns suitable for export in host apps.
Domain events like HttpRequestStarted / platform Event Mesh integration are factory extensions, not files emitted by dotnet new alone.
Trace context propagation is typically configured in the consuming application (OpenTelemetry, HttpClient instrumentation), not as a dedicated template tracing project.

📡 Observability-First Design¶

Capability	Baseline template?	Notes
Structured Logging	✅ (`ILogger` patterns)	Host chooses sinks (e.g. Serilog).
Distributed Tracing	❌ (not scaffolded)	Add in host or post-process; see Library Template for in-library tracing samples.
Metrics (custom instruments)	✅ when `UseMetrics`	`Microsoft.Extensions.Diagnostics`; export via host / OTel.
Resilience telemetry	✅ (via `Microsoft.Extensions.Http.Resilience`)	Retry/circuit behavior; not separate “audit events” type unless agents add them.

🧰 Modular, Composable, Extensible¶

Each client library is a self-contained package
Optional plugins: ICacheHandler, IRetryPolicy, IRequestSigner
Support for dependency injection via Add{ApiServiceName}Service()-style extensions from the template

🧩 Supports integration with:

OpenId Connect libraries
Configuration providers (Azure App Config, Vaults)
WireMock.Net for HTTP/API simulation in scaffolded tests (not Moq for remote HTTP)

🛡 Security-First Architecture¶

No secrets are hardcoded — all credentials injected via IOptions
Supports bearer token injection, API key headers, and OIDC delegation
Optional rate limiting, circuit breaking, IP restrictions

🧠 AI-Aware Blueprint Design¶

Blueprint includes prompts for:
- API docs ingestion
- Response/DTO modeling from samples
- Retry policy generation
Memory stores track failures, usage feedback, agent improvements

✅ Summary¶

The backend API library blueprint targets secure, testable, production-ready clients: the baseline connectsoft-api-library template encodes HTTP client, resilience, auth layout, and optional metrics; full observability stacks, mock servers, and .factory metadata require agent orchestration or host configuration as described in the alignment table at the top.

🧭 Generation Source: Template CLI and Blueprint Definition¶

This section explains the technical origin of the backend API library blueprint: it is instantiated via a specialized .NET CLI template and configured through an AI-readable blueprint definition. The combination enables fully agentic, repeatable scaffolding with predictable structure and metadata.

⚙️ .NET CLI Template¶

The blueprint is implemented via the ConnectSoft CLI template (parameters reference):

dotnet new connectsoft-api-library \
  --name "ConnectSoft.Example.Api" \
  --api-service-name "Example" \
  --api-service-description "Example HTTP API" \
  --authentication-type "ApiKey" \
  --use-metrics true

Default dotnet new output (multi-target net8;net9;net10):

Project / path	Description
`src/{name}/`	Library: `I{ApiServiceName}Service`, `{ApiServiceName}Service`, `Options/`, optional `Metrics/`, extensions
`tests/{name}.UnitTests/`	MSTest + WireMock-based tests
Solution + build	`.slnx`, `.sln`, `Directory.Packages.props`, `azure-pipelines.yml`, `README.md`, docs layout as authored

Not produced by the template alone: *.MockServer host project, separate Configuration project, .factory/ — add via agents or manual steps if your factory standard requires them.

🧠 Input: Blueprint DSL / YAML¶

The generation process may be driven by a YAML blueprint definition like this. Agents must map these fields to real dotnet new symbols (ApiServiceName, ApiServiceDescription, AuthenticationType, UseMetrics, Framework, buildDefinitionNumber, name) per API Library Template parameters. Fields such as baseUrl or traceIntegration are not template switches—they imply post-scaffold or host work unless added to the template later.

id: ConnectSoft.Backend.GoogleAnalyticsClient
type: backend.api.library
template: connectsoft-api-library
parameters:
  baseUrl: "https://analytics.googleapis.com/v1"   # → options / code, not a dotnet new symbol today
  authentication: oauth2                            # → map to AuthenticationType: OAuth
  retryPolicy: true                                 # → baseline resilience is already in template; extra policy is agent work
  traceIntegration: true                            # → host OTel / agent-added tracing, not template default
  optionsBinding: true                              # → pattern exists via Options in scaffold
metadata:
  createdBy: ApiScaffolderAgent
  originatingRunId: RUN-2025-06-07-001

This DSL is parsed by the agent, and prompts are shaped accordingly to guide the CLI invocation and post-processing.

⚙️ Template Features Supported¶

Feature	Supported?	Source
Typed `HttpClient`	✅	Scaffolded via base template
DI Extensions	✅	`Add{ApiServiceName}Service(IServiceCollection)` (template naming)
Test Templates	✅	MSTest, WireMock.Net, coverlet.collector
Retry + Resilience	✅	Optional flag in DSL
Config Binding	✅	`.UseGoogleAnalyticsOptions()`
Telemetry Hooks	Partial	Logging + optional metrics in scaffold; tracing = host or agent follow-up
NuGet Packaging	✅	`pack` task and `nuspec` auto-filled

🧠 Output: Traceability Context¶

Baseline template output does not create a .factory/ tree. When the Software Factory or agents emit metadata, the solution may include .factory/blueprint.meta.json (example shape):

{
  "id": "ConnectSoft.Backend.GoogleAnalyticsClient",
  "template": "connectsoft-api-library",
  "agent": "ApiScaffolderAgent",
  "createdAt": "2025-06-07T13:52:00Z",
  "parameters": {
    "authentication": "oauth2",
    "retryPolicy": true
  }
}

This enables regeneration, memory linking, reuse, and documentation automation.

📘 README.md Snippet from Template¶

# 📦 GoogleAnalyticsClient

This package is an API wrapper for Google Analytics v4, generated from the ConnectSoft backend API blueprint.

- Built with: `connectsoft-api-library` template
- Auth: OAuth2
- Retry Policy: Enabled
- Observability: Tracing, Logging, Metrics

✅ Summary¶

This blueprint is powered by a robust .NET CLI template, enriched by a blueprint YAML definition and consumed by agents. It allows precise, repeatable, traceable scaffolding of fully featured backend libraries — minimizing manual effort while enforcing ConnectSoft standards.

🧭 High-Level Folder and Project Layout¶

This section defines a reference layout for factory-evolved outputs. The minimal structure produced by dotnet new connectsoft-api-library alone is smaller (see Implementation alignment): one library project, one *.UnitTests project, no .factory/ or MockServer unless agents add them. Treat the tree below as target or extended unless you are explicitly layering agents on top of the baseline template.

📂 Solution Folder Structure¶

When the blueprint is executed via CLI and extended per factory conventions, a structure like the following may be generated:

GoogleAnalyticsClient/
├── src/
│   ├── GoogleAnalyticsClient/
│   │   ├── Clients/
│   │   ├── Configuration/
│   │   ├── Extensions/
│   │   ├── Models/
│   │   ├── Requests/
│   │   ├── Responses/
│   │   ├── Services/
│   │   ├── Authentication/
│   │   └── GoogleAnalyticsClient.csproj
│   └── GoogleAnalyticsClient.MockServer/
│       ├── Controllers/
│       ├── Fixtures/
│       └── GoogleAnalyticsClient.MockServer.csproj
├── tests/
│   └── GoogleAnalyticsClient.UnitTests/
│       ├── Builders/
│       ├── Integration/
│       ├── Unit/
│       ├── Fixtures/
│       └── GoogleAnalyticsClient.UnitTests.csproj
├── blueprints/
│   └── blueprint.yaml
├── .factory/
│   └── blueprint.meta.json
├── README.md
└── azure-pipelines.yml

📦 Key Subfolders Explained¶

Folder	Purpose
`Clients/`	Implements the actual HTTP interface logic
`Requests/Responses/Models/`	Strongly typed DTOs for API input/output
`Configuration/`	Contains `Options` classes and DI extension methods
`Authentication/`	Encapsulates OAuth2/API Key injectors
`Extensions/`	Fluent service registration and pipeline wiring
`Services/`	Higher-level business wrapper if needed (optional)
`MockServer/`	Fake/stubbed API service for local testing and CI
`Tests/`	Test projects organized by type (unit/integration/etc.)
`.factory/`	Metadata and trace logs for blueprint lineage

🧩 Layer Alignment¶

Layer	Location
Infrastructure	`Clients/`, `Authentication/`, `Http/`
Application	`Services/`, `Options/`, `Configuration/`
Test/Mocking	`Tests/`, `MockServer/`
Blueprint/CI	`.factory/`, `azure-pipelines.yml`

📘 README Structure (Auto-Generated)¶

# GoogleAnalyticsClient

> ConnectSoft standard backend API library

## 🔌 Installation
```bash
dotnet add package ConnectSoft.GoogleAnalyticsClient
```

## 🚀 Usage

```csharp
services.AddGoogleAnalyticsClient(Configuration);
```

## 📦 Structure

* Requests/Responses: Typed DTOs
* Clients: Typed `HttpClient` wrappers
* Config: OAuth2 and endpoint settings

✅ Summary¶

The high-level layout of the backend API library is modular, extensible, and clean — giving agents, developers, and testers a predictable and powerful starting point. This structure ensures that authentication, requests, configuration, and testing are separated but integrated, enabling rapid development and safe reuse.

🧭 Artifact Types Produced by the Blueprint¶

This section outlines the full set of runtime and development artifacts generated by the backend API library blueprint. These outputs are standardized across the factory to ensure portability, traceability, observability, and reuse within ConnectSoft’s modular ecosystem.

📦 Artifact Overview¶

Artifact Type	Output File or Format	Purpose
🧱 NuGet Package	`ConnectSoft.GoogleAnalyticsClient.nupkg`	Reusable, publishable .NET client package
🧪 Test Binaries	`GoogleAnalyticsClient.Tests.dll`	Unit/integration test output
📊 Telemetry Hooks	`ILogger`, `Activity`, metrics emitters	Observability-first instrumentation
🔐 Config Template	`GoogleAnalyticsOptions.cs`, `appsettings.json` snippet	Config-driven setup (base URL, keys, scopes)
📘 Documentation	`README.md`, `features.md`, `Usage.md`, `Authentication.md`	Agent-generated guides
⚙️ CI/CD Pipeline	`azure-pipelines.yml` or `ci.yaml`	Ready-to-use DevOps YAML pipeline
🔍 Mock Server	`GoogleAnalyticsClient.MockServer.dll`, Dockerfile (optional)	Simulated API for contract & integration testing
🧠 Trace Metadata	`.factory/blueprint.meta.json`	Traceable execution context
🧬 DSL Blueprint	`blueprints/blueprint.yaml`	The blueprint that defines and reproduces the library
📤 OpenAPI Snapshots	`openapi.schema.json` (optional)	Used when syncing API clients with server definitions

🧠 Deep Integration into Factory Memory¶

Every artifact is:

Tagged by its blueprint.id, version, and agent origin
Stored in:
- Azure Artifacts (NuGet feed)
- Azure DevOps pipeline storage
- Vector DB for embedding and reuse search
Linked to its original AgentRunId and DSL input

This enables:

Auditability of generated components
Full regeneration from metadata
Memory-based similarity search (e.g., “Find clients similar to this one”)

📘 Sample Artifact Directory Tree¶

dist/
├── ConnectSoft.GoogleAnalyticsClient.1.0.0.nupkg
├── test-results.xml
├── doc/
│   ├── README.md
│   ├── Authentication.md
│   ├── Configuration.md
│   └── Usage.md
├── .factory/
│   └── blueprint.meta.json
├── mock-server/
│   ├── docker-compose.yml
│   └── GoogleAnalyticsClient.MockServer.dll

🧠 Agents Producing Artifacts¶

Agent	Artifact
LibraryScaffolderAgent	.NET projects, main code layout
DocsAgent	Markdown and usage docs
MockServerAgent	Fake implementation & API test targets
PipelineAgent	`azure-pipelines.yml`, NuGet pack and push
MemoryIndexerAgent	Pushes `.meta.json` and DSL into trace memory
TestGeneratorAgent	MSTest suites, stubs, mocks

🧩 Example Use: App Consumes Published NuGet¶

dotnet add package ConnectSoft.GoogleAnalyticsClient

services.AddGoogleAnalyticsClient(configuration);
var client = serviceProvider.GetRequiredService<IGoogleAnalyticsClient>();
await client.TrackEventAsync("campaign");

✅ Summary¶

The backend API library blueprint produces more than just code — it yields a full constellation of publishable, observable, testable artifacts that can be consumed across microservices, apps, and agents. These outputs are machine-traceable and composable — making every API client a secure, reusable module in the ConnectSoft software ecosystem.

🧭 When to Use This Blueprint¶

This section defines when and why an agent or engineer should instantiate the backend API library blueprint. It helps differentiate its use from other blueprint types (e.g. microservices, frontend libraries) and clarifies best-fit scenarios across system architecture and product needs.

🧩 Primary Use Cases¶

Scenario	Use This Blueprint
✅ A backend service needs to call an external 3^rd-party API	YES – Generate a secure, typed HTTP client wrapper
✅ An internal domain module wants to expose a reusable service interface	YES – Produce a NuGet SDK-style library
✅ An AI agent wraps a service it generates via REST	YES – Creates a usable interface for self-call or downstream agents
❌ A service hosts endpoints and needs to scale independently	❌ Use the `agent-microservice-blueprint.md`
❌ A UI consumes APIs directly via TypeScript or Blazor	❌ Use the `frontend-library-blueprint.md`
✅ Common tenant-aware services (e.g. billing, audit) consumed by many apps	YES – Abstract client logic into a library with shared responsibility

🎯 Ideal Blueprint Characteristics¶

✅ Pull-based communication (client → service)
✅ Reusable logic across services or apps
✅ No need for database or hosting runtime
✅ Strong need for authentication, observability, retries
✅ Output is a NuGet-distributed .NET library

🧠 Triggering Agents¶

Agent	Triggering Condition
Business Analyst Agent	Identifies integration need with external API
Solution Architect Agent	Models boundary between services and suggests reuse
Platform Agent	Extracts shared logic from multiple microservices
DevOps Agent	Creates standard pipelines and artifacts for API integration
AI Runtime Agent	Needs to expose or consume a backend function securely

📘 Examples¶

Case	Result
🧾 CRM system wants to push customer events to Segment	Generates `SegmentClient` with OAuth2
🧾 Payment Service needs to call Stripe API	Generates `StripeClient` with API key support
🧾 Tenant Management needs to centralize billing across apps	Generates reusable `TenantBillingClient` NuGet
🧾 AI Agent wraps an internal retry-and-queue system	Outputs `RetryClient` used in runtime orchestration

🧩 Library vs. Microservice Decision¶

Feature	Library Blueprint	Microservice Blueprint
Hosting runtime	❌ No	✅ Yes
External HTTP endpoints	❌ No	✅ Yes
Pulls external data	✅ Yes	❌ No
Reused across other modules	✅ Yes	⛔ Rarely
Deployed independently	❌ No	✅ Yes
Published as NuGet	✅ Yes	❌ No

✅ Summary¶

The backend API library blueprint is ideal for producing typed, authenticated, observable client wrappers for remote APIs — internal or external. It enables reuse, testing, and CI/CD at the library level, without the burden of full microservice deployment. It is the default choice whenever your service needs to consume other services reliably and securely.

🧭 Blueprint DSL and Configurable Parameters¶

This section describes the blueprint definition schema (DSL) used by agents to instantiate and configure backend API libraries. The DSL allows agents to declaratively define the behavior, dependencies, security, and observability expectations of the generated library — before code is written.

📘 Sample DSL Snippet¶

id: ConnectSoft.Backend.StripeClient
type: backend.api.library
template: connectsoft-api-library
parameters:
  baseUrl: "https://api.stripe.com/v1"
  authentication:
    type: apiKey
    headerName: "Authorization"
    prefix: "Bearer "
  retryPolicy:
    strategy: exponentialBackoff
    maxAttempts: 5
  telemetry:
    enabled: true
    tracing: true
    metrics: true
  options:
    enabled: true
    bindFrom: "Stripe:Client"
  environments:
    - Development
    - Production

🔧 Supported Parameters¶

Parameter	Description	Example
`baseUrl`	Base endpoint of the API	`https://api.stripe.com/v1`
`authentication`	Auth strategy (API key, OAuth2, custom)	`apiKey`, `oauth2`
`retryPolicy`	Retry/backoff config	`exponentialBackoff`, `linear`, `none`
`telemetry`	Enable logs, traces, metrics	`enabled: true`
`options`	Bind config to `IOptions<T>`	Bind from `appsettings`
`environments`	List of supported environments	`Development`, `Staging`, `Production`
`headers`	Custom headers to inject	`{ x-api-version: "v1" }`
`rateLimiting`	Enable local rate limiter	`enabled: true, window: 1s, max: 10`

🧠 DSL Usage in Agent Prompts¶

Agents use the DSL fields to:

Shape prompt for client method extraction:
- e.g., "Here is the OpenAPI spec and base URL. GenerateIAnalyticsClientinterface using baseUrl from DSL."
Inject conditional logic:
- If authentication.type = oauth2, scaffold token providers and AuthorizationHandler
Compose observability config:
- Telemetry decorators inserted only if telemetry.enabled = true
Choose environment-specific overrides:
- E.g., use mock baseUrl in Development

🧩 Modular Extensions¶

The DSL is composable — additional blueprint fragments can extend the base spec:

extends:
  - observability-standard
  - retry-default

Agents can use shared fragments (stored in vector memory or blob) to apply reusable patterns.

🧬 Versioned DSL¶

Each blueprint can be versioned and replayed. DSLs are saved into:

.factory/blueprint.meta.json
blueprints/blueprint.yaml
Memory vector index for lookup and regeneration

📘 Validated DSL Schema (JSON)¶

Blueprints follow a schema-compatible structure and are validated prior to generation:

{
  "type": "object",
  "required": ["id", "template", "parameters"],
  "properties": {
    "authentication": {
      "type": "object",
      "properties": {
        "type": { "enum": ["apiKey", "oauth2", "custom"] },
        "headerName": { "type": "string" }
      }
    }
  }
}

✅ Summary¶

The DSL gives agents declarative control over how an API library is structured, secured, and wired. It ensures reproducibility, allows conditional prompt logic, and supports memory-driven reuse of patterns across blueprints. It’s the foundation of blueprint-driven scaffolding in the ConnectSoft AI Software Factory.

🧭 Example Instantiation Flow: From DSL to Working Library¶

This section illustrates a complete agentic instantiation flow of the backend API library blueprint — starting from an integration need, through DSL definition and prompt orchestration, to a fully generated, testable, publishable client library.

📘 Scenario: Stripe API Integration¶

"The Product Owner requests secure, reusable access to the Stripe Billing API for recurring subscriptions."

🧠 Step-by-Step Agent Flow¶

Step	Agent	Action
1️⃣	Business Analyst Agent	Captures requirement: "Integrate with Stripe to manage customer subscriptions."
2️⃣	Solution Architect Agent	Decides to isolate Stripe access into a standalone client
3️⃣	LibraryScaffolderAgent	Prepares DSL and emits it into prompt
4️⃣	Code Generator Agent	Generates structure using `connectsoft-api-library`
5️⃣	Authentication Agent	Adds API key support based on DSL config
6️⃣	RetryPolicy Agent	Adds exponential backoff decorators
7️⃣	Observability Agent	Wraps methods with logs, traces, and metrics
8️⃣	Docs Agent	Generates `README.md`, `Authentication.md`, `Usage.md`
9️⃣	Pipeline Agent	Adds `azure-pipelines.yml` for build + publish
🔁	MemoryIndexerAgent	Stores blueprint metadata, DSL, and artifacts for future reuse

📂 Input DSL¶

id: ConnectSoft.Backend.StripeClient
template: connectsoft-api-library
parameters:
  baseUrl: "https://api.stripe.com/v1"
  authentication:
    type: apiKey
    headerName: "Authorization"
    prefix: "Bearer "
  telemetry:
    enabled: true
    tracing: true
    metrics: true
  retryPolicy:
    strategy: exponentialBackoff
    maxAttempts: 4

🏗️ CLI Generation¶

dotnet new connectsoft-api-library --name StripeClient

Produces:

StripeClient/
StripeClient.Tests/
StripeClient.MockServer/
.factory/blueprint.meta.json

🧪 Example Generated Interface¶

public interface IStripeClient
{
    Task<CustomerResponse> GetCustomerAsync(string customerId, CancellationToken cancellationToken = default);
    Task<InvoiceResponse> CreateInvoiceAsync(CreateInvoiceRequest request, CancellationToken cancellationToken = default);
}

🚀 Sample Usage (Consumer App)¶

services.AddStripeClient(Configuration);
var stripe = sp.GetRequiredService<IStripeClient>();
var invoice = await stripe.CreateInvoiceAsync(new CreateInvoiceRequest { ... });

📘 Generated README (Excerpt)¶

# StripeClient

> ConnectSoft API client for Stripe Billing v1

## 🔐 Authentication

This client uses Bearer token-based API key auth.

Set in `appsettings.json`:

```json
"Stripe": {
  "ApiKey": "sk_test_123456..."
}
```

## 📦 Installation

```bash
dotnet add package ConnectSoft.StripeClient
```

🔁 Trace Metadata¶

Saved in .factory/blueprint.meta.json:

{
  "id": "ConnectSoft.Backend.StripeClient",
  "agent": "LibraryScaffolderAgent",
  "originatingRunId": "RUN-2025-06-07-024",
  "parameters": {
    "authentication": "apiKey",
    "retryPolicy": "exponentialBackoff"
  }
}

✅ Summary¶

This example shows how a simple DSL blueprint can drive an automated, production-grade API integration — complete with authentication, retries, observability, CI/CD, tests, and documentation. The entire flow is reproducible, traceable, and memory-indexed for future reuse or mutation.

🧭 Cross-Blueprint Dependencies and Shared Integrations¶

This section explains how backend API libraries generated by this blueprint can depend on, extend, or compose with other blueprints — forming modular, reusable service SDKs that integrate deeply across the ConnectSoft platform.

🔁 Cross-Blueprint Relationship Map¶

graph TD
  B[Backend API Library]
  F[Frontend Library Blueprint]
  M[Microservice Blueprint]
  P[Platform Blueprint]
  O[Observability Blueprint]
  C[Configuration Blueprint]
  T[Testing Blueprint]

  B --> O
  B --> C
  B --> T
  F --> B
  M --> B
  P --> B

Hold "Alt" / "Option" to enable pan & zoom

🧩 Typical Dependencies¶

Blueprint	Integration Mode	Description
`observability-blueprint.md`	Decorators / DI hooks	Logging, tracing, metrics injected into client
`configuration-blueprint.md`	Options pattern	Auto-binds `appsettings.json` or Vault
`testing-blueprint.md`	Test base, mocks	Used to generate mock servers and test doubles
`frontend-library-blueprint.md`	API shape mirroring	Shared DTOs or signature alignment
`agent-microservice-blueprint.md`	Server implementation	Generated library may call generated microservice
`platform-blueprint.md`	Compositional reuse	Library injected as NuGet into platform host apps

🔁 Blueprint Reuse Example¶

📘 StripeClient is consumed in:

TenantBillingService (microservice blueprint)

ConnectSoft Platform (platform blueprint)

TenantPortalWebApp (frontend blueprint via proxy bridge)

🧠 Agent-Level Collaboration¶

Producer Agent	Consuming Agent
`LibraryScaffolderAgent`	`DocsAgent`, `PipelineAgent`
`AuthInjectorAgent`	`ObservabilityAgent`
`MockServerAgent`	`TestGeneratorAgent`
`PlatformOrchestratorAgent`	Reuses NuGet from API library blueprint

This interaction is orchestrated by blueprint dependency graphs, where each artifact carries a dependsOn metadata block.

📘 Blueprint Metadata Extension¶

{
  "id": "ConnectSoft.Backend.StripeClient",
  "dependsOn": [
    "blueprint.configuration.standard",
    "blueprint.observability.default",
    "blueprint.testing.mstest"
  ]
}

This allows agents to automatically resolve and inject additional blueprints or capabilities during generation.

📦 Shared Packages/Artifacts¶

Generated backend API libraries may depend on shared ConnectSoft nugets such as:

NuGet Package	Purpose
`ConnectSoft.Extensions.Http.OpenIdConnect`	Token handler for OIDC flows
`ConnectSoft.Resilience`	Retry, circuit breaker decorators
`ConnectSoft.Observability.Core`	Logging, tracing, metrics hooks
`ConnectSoft.Testing.MockServer`	Prebuilt HTTP mocks and assert helpers

📂 Output Folder Enrichment¶

Blueprints may co-locate shared components or emit them into the same workspace for local linking:

/src/
  StripeClient/
  ConnectSoft.Observability.Core/     <-- Injected from observability blueprint
  ConnectSoft.Configuration.Shared/

✅ Summary¶

The backend API library blueprint is not isolated — it is composable and interconnected with the larger platform via blueprint dependencies, shared agents, and layered artifact reuse. This makes it scalable, traceable, and evolvable — while minimizing code duplication and siloed integrations.

🧭 Typed HTTP Client Design and Interface Generation¶

This section focuses on how the blueprint generates typed, testable, and DI-ready HTTP clients. These clients are scaffolded with explicit interfaces, clean request/response models, and extensible behavior hooks — enabling composable and resilient backend API access.

🔧 Interface-First Design Pattern¶

The generated client adheres to the interface-first principle:

public interface IStripeClient
{
    Task<CustomerResponse> GetCustomerAsync(string customerId, CancellationToken ct = default);
    Task<InvoiceResponse> CreateInvoiceAsync(CreateInvoiceRequest request, CancellationToken ct = default);
}

The implementation:

public class StripeClient : IStripeClient
{
    private readonly HttpClient client;

    public StripeClient(HttpClient client)
    {
        this.client = client;
    }

    public async Task<CustomerResponse> GetCustomerAsync(string customerId, CancellationToken ct)
    {
        var response = await client.GetAsync($"/customers/{customerId}", ct);
        response.EnsureSuccessStatusCode();
        return await response.Content.ReadFromJsonAsync<CustomerResponse>(cancellationToken: ct);
    }
}

🏗️ Generated via Agentic Template¶

Interface and class are generated from:
- OpenAPI spec
- Sample JSON
- User-defined prompt
Optional fallback: agents prompt GPT to infer methods from API doc text

🧩 Benefits of Interface-First Approach¶

Benefit	Description
🧪 Testability	Interface enables fakes; HTTP tests use WireMock.Net (not Moq for API simulation)
🔄 Swappability	Can replace implementation at runtime (e.g., mock, proxy)
🧠 LLM Reasoning	Simplifies reflection, traceability, and behavioral prompts
🛠 DI Compatibility	Plugs into factory-wide `AddXyzClient()` extensions
📘 Auto-docs	Enables agents to generate usage snippets from method signature

🔌 Typed `HttpClient` Injection¶

The client is registered via DI:

services.AddHttpClient<IStripeClient, StripeClient>()
    .ConfigureHttpClient((sp, client) =>
    {
        var opts = sp.GetRequiredService<IOptions<StripeOptions>>().Value;
        client.BaseAddress = new Uri(opts.BaseUrl);
        client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", opts.ApiKey);
    })
    .AddPolicyHandler(RetryPolicies.ExponentialBackoff());

This supports:

✅ Resiliency decorators
✅ Telemetry middleware (e.g., TracingHandler)
✅ Config-driven headers and base URLs

📂 Project Layout¶

Folder	Contents
`Clients/`	`IStripeClient.cs`, `StripeClient.cs`
`Models/`	DTOs such as `InvoiceRequest`, `CustomerResponse`
`Authentication/`	Token and header injectors
`Configuration/`	`StripeOptions.cs`, `IOptions<StripeOptions>`

🧠 AI Prompt Sample¶

You are the API Client Agent.

You are given:
- baseUrl: https://api.stripe.com/v1
- Auth type: API Key in Bearer header
- Required methods: create invoice, get customer

Produce:
- `IStripeClient` interface
- `StripeClient` implementation
- Typed models in `Requests/` and `Responses/`
- DI registration extension

✅ Summary¶

Typed HTTP clients are the core output artifact of the backend API blueprint. They expose clean, versioned, observable interfaces with testability, DI support, and resiliency built-in — enabling the factory to scale integrations without sacrificing maintainability.

🧭 Authentication and Authorization Strategies¶

This section defines the authentication mechanisms supported by the backend API library blueprint and how they are injected, abstracted, and configured during agentic generation. These strategies ensure secure access to both internal and external services in a reusable and pluggable way.

🔐 Supported Auth Strategies¶

Strategy	Description	Example Use
`apiKey`	Static key passed in a header or query param	Stripe, SendGrid, Mailchimp
`oauth2-client-credentials`	Machine-to-machine OAuth 2.0 flow	Microsoft Graph, Salesforce, HubSpot
`openIdConnect`	Identity tokens, user delegation	Azure AD, Auth0
`custom`	Agent-defined injectors, dynamic headers	Partner APIs, legacy systems

🔧 DSL Example¶

authentication:
  type: oauth2-client-credentials
  tokenUrl: https://login.microsoftonline.com/tenant/oauth2/v2.0/token
  clientId: __from_config__
  clientSecret: __from_keyvault__
  scope: https://graph.microsoft.com/.default

🧩 Injection via Decorator Handlers¶

The generated client uses delegating handlers to insert tokens automatically:

public class OAuth2AuthorizationHandler : DelegatingHandler
{
    private readonly ITokenProvider tokenProvider;

    public OAuth2AuthorizationHandler(ITokenProvider tokenProvider) =>
        this.tokenProvider = tokenProvider;

    protected override async Task<HttpResponseMessage> SendAsync(HttpRequestMessage request, CancellationToken cancellationToken)
    {
        var token = await tokenProvider.GetAccessTokenAsync();
        request.Headers.Authorization = new AuthenticationHeaderValue("Bearer", token);
        return await base.SendAsync(request, cancellationToken);
    }
}

Registered via DI:

services.AddTransient<OAuth2AuthorizationHandler>();
services.AddHttpClient<IMyClient, MyClient>()
        .AddHttpMessageHandler<OAuth2AuthorizationHandler>();

🔐 API Key Configuration¶

For simpler APIs using static keys:

client.DefaultRequestHeaders.Add("Authorization", $"Bearer {opts.ApiKey}");

API keys are securely bound via IOptions<T>:

"Stripe": {
  "ApiKey": "sk_test_..."
}

services.Configure<StripeOptions>(Configuration.GetSection("Stripe"));

🧠 Token Providers and Reuse¶

Agents may inject:

IClientCredentialTokenProvider for OAuth2 client flow
IOpenIdConnectTokenProvider for ID tokens
ICustomHeaderInjector for proprietary logic

These are shared across libraries and available as reusable nugets.

🔁 Token Caching¶

The blueprint integrates with a platform-wide caching layer:

Feature	Behavior
Memory Cache	Default per-process access token reuse
Distributed Cache	Optional for clustered environments
Token TTL Awareness	Respects `expires_in` from token response

🔒 Secrets and Key Vault Support¶

The blueprint never hardcodes secrets. It supports:

Azure Key Vault via:
- ISecretProvider
- Configuration binding from Managed Identity
Local secrets via .usersecrets
CI-injected secrets via pipeline variables

✅ Summary¶

Authentication in the backend API library blueprint is flexible, pluggable, and composable. Agents configure it via DSL, and the scaffolded client ensures proper injection, caching, and reuse of credentials — across APIs and runtime environments — without security compromises.

🧭 Resiliency Layer: Retries, Circuit Breakers, Bulkheads¶

This section outlines how the backend API library blueprint integrates resiliency patterns to ensure robustness and fault tolerance when communicating with remote APIs — including automatic retries, fallback strategies, timeout handling, and optional circuit breakers.

🧰 Resiliency Features Built-In¶

Capability	Included	Description
✅ Retry Policies	✔️	Retry transient failures (e.g., HTTP 429, 503)
✅ Timeout Policies	✔️	Abort long-running requests gracefully
✅ Circuit Breakers	⏳ Opt-in	Stop requests temporarily after repeated failures
✅ Bulkhead Isolation	⏳ Opt-in	Limit concurrency for expensive endpoints

These behaviors are injected via HttpClient policies and are configurable through DSL or DI.

🔧 DSL Configuration Example¶

retryPolicy:
  strategy: exponentialBackoff
  maxAttempts: 5
  delay: 1s
  jitter: true

circuitBreaker:
  enabled: true
  failureThreshold: 10
  breakDuration: 30s

⚙️ Resiliency Implementation (Polly)¶

Generated code uses Polly or platform-specific wrappers:

services.AddHttpClient<IStripeClient, StripeClient>()
    .AddPolicyHandler(Policy<HttpResponseMessage>
      .Handle<HttpRequestException>()
      .OrResult(r => r.StatusCode == HttpStatusCode.TooManyRequests)
      .WaitAndRetryAsync(5, retryAttempt => 
          TimeSpan.FromSeconds(Math.Pow(2, retryAttempt))
      ));

🔁 Other strategies:

Retry-After header aware
Circuit breaker:

.AddPolicyHandler(Policy<HttpResponseMessage>
    .Handle<Exception>()
    .CircuitBreakerAsync(10, TimeSpan.FromSeconds(30)));

🧪 Testing & Simulation¶

The generated library includes:

ResiliencyTests.cs to simulate failure conditions
Optional mock server support to inject:
- 500, 503, 429 responses
- Timeout conditions
- Header-based retry instructions

📈 Telemetry Hooks¶

All retry/circuit logic is observable:

Metric	Description
`retry_attempt_count`	Total retries
`circuit_state`	Closed / Open / Half-Open
`timeout_count`	Requests aborted due to timeout
`fallback_used`	Was a fallback strategy applied?

Emitted via OpenTelemetry or ILogger.

🔌 Optional Custom Decorators¶

Blueprint supports:

Custom retry selector
Retry per-method granularity
Fallback method decorators (optional in future blueprint evolution)

[RetryPolicy(RetryType.Exponential, MaxRetries = 4)]
Task<MyResponse> GetData();

⚙️ Agents may inject such attributes via code-generation if DSL enables advanced resiliency profiles.

✅ Summary¶

The backend API library blueprint ensures production-grade resilience out of the box. With retry policies, circuit breakers, and observability hooks integrated via configuration and agents, every generated client can safely call external systems — even under partial failure or load spikes.

🧭 Observability Integration: Logs, Traces, Metrics¶

Baseline connectsoft-api-library: Structured logging and optional metrics scaffolding align with template parameters (e.g. UseMetrics). Distributed tracing (per-method spans, ActivitySource in generated code) is not part of the template output — use the host OpenTelemetry pipeline or factory/agents to add it. See Implementation alignment (read first) at the top of this document.

This section describes observability hooks the blueprint targets: logging and metrics are in scope for the scaffold; tracing and rich span behavior apply when you extend the library via agents or hosting.

🔍 Observability Pillars¶

Pillar	Implementation
📜 Logs	Structured logging via `ILogger`
📈 Metrics	Counters, histograms, timers when metrics are enabled in template / agents
📡 Tracing	Distributed trace context — host and/or agent extension, not baseline template
🧠 Events	Span events for retries, exceptions, fallbacks — when tracing is added

Logging is standard in generated clients. Metrics follow template flags and optional factory enrichment. Tracing is opt-in via host OTel or blueprint agents, not assumed for raw dotnet new output.

🧠 Blueprint DSL Example¶

telemetry:
  enabled: true
  logging: true
  tracing: true
  metrics: true

🧱 Instrumentation Points¶

Layer	Instrumentation
HTTP Pipeline	Request start/end logs, error logs, retry logs
Retry Middleware	Emits retry count, result state
Circuit Breaker	Logs state transitions (open/close), failure reasons
Client Interface	Trace spans per method when agents inject tracing
Authentication	Token fetch timing, cache hits/misses

📜 Logging Format (Serilog / ILogger)¶

{
  "timestamp": "2025-06-07T14:35:21Z",
  "message": "StripeClient.GetInvoiceAsync executed",
  "httpMethod": "GET",
  "url": "https://api.stripe.com/v1/invoices/inv_123",
  "durationMs": 482,
  "statusCode": 200,
  "retryAttempts": 1,
  "traceId": "b3943c2...c71"
}

Logs include:

Correlation IDs
Span IDs
Retry/circuit state
User/tenant context if available

📡 OpenTelemetry Tracing¶

When tracing is added (host or agents), client methods may be wrapped in spans, for example:

using var span = tracer.StartActiveSpan("StripeClient.GetInvoice");

With trace context passed via:

HttpRequestMessage.Headers
B3, W3C Trace Context, or custom format

Spans are exported to:

Jaeger
Zipkin
Azure Monitor
Prometheus (via otel-collector)

📈 Metrics Emitted¶

Metric Name	Type	Purpose
`http_request_duration_seconds`	Histogram	API latency
`retry_attempt_count`	Counter	Retry operations
`client_failure_count`	Counter	Failures grouped by status
`circuit_state`	Gauge	Current CB state (0=closed, 1=open)

🧪 Test Verification¶

Extended blueprints or agent pipelines may include tests to validate:

Logs are emitted
Spans are created (when tracing is part of the build)
Metrics counters increment correctly (when metrics are enabled)

These can be run with mock tracing and log collectors in CI where that stack is present.

🧠 Agent Skills Used¶

Agent	Skills
`ObservabilityAgent`	`TelemetryHookInjectorSkill`, `SpanTemplateGeneratorSkill`
`TestAgent`	`ObservabilityAssertionsSkill`, `MetricsValidationSkill`

✅ Summary¶

Logging and metrics (when enabled) are first-class in the generated client shape. Distributed tracing in generated code is a platform or agent extension, not a guarantee of the minimal API library template — combine baseline output with host OpenTelemetry or factory observability agents for full trace coverage.

🧭 Configuration Binding and Multi-Environment Support¶

This section details how the backend API library blueprint enables configuration flexibility across environments by generating standardized IOptions<T> bindings, support for secret injection, and runtime switching logic — essential for tenant-aware, secure, and portable deployments.

🔧 Blueprint DSL Configuration Section¶

options:
  enabled: true
  bindFrom: "Stripe"
  environments:
    - Development
    - Staging
    - Production

🧩 Generated Options Class¶

public class StripeOptions
{
    public string BaseUrl { get; set; }
    public string ApiKey { get; set; }
    public bool UseSandbox { get; set; }
}

⚙️ Configuration Binding Setup¶

Generated extension method:

services.Configure<StripeOptions>(
    Configuration.GetSection("Stripe"));

The client is bound as:

services.AddHttpClient<IStripeClient, StripeClient>()
    .ConfigureHttpClient((sp, client) =>
    {
        var options = sp.GetRequiredService<IOptions<StripeOptions>>().Value;
        client.BaseAddress = new Uri(options.BaseUrl);
        client.DefaultRequestHeaders.Authorization =
            new AuthenticationHeaderValue("Bearer", options.ApiKey);
    });

📁 Environment-Specific Configuration Files¶

File	Use
`appsettings.Development.json`	Local or mock servers
`appsettings.Production.json`	Real service endpoints
`appsettings.Test.json`	CI test stubs

// appsettings.Production.json
{
  "Stripe": {
    "BaseUrl": "https://api.stripe.com/v1",
    "ApiKey": "__from_keyvault__"
  }
}

🔐 KeyVault bindings are auto-injected via configuration providers.

🔄 Environment-Sensitive Behaviors¶

Feature	Use Case
Mock server in `Development`	Simulated API test double
Rate limiting disabled in `Staging`	Easier QA throughput
Strict timeout in `Production`	Prevents runaway retries
Logging verbosity adjusted	More verbose in `Debug`, errors only in `Prod`

🔧 Optional Bindings¶

The blueprint allows mapping other sections via:

bindFrom: "Services:Stripe:Client"

Supports deep navigation, prefix aliasing, and custom IConfigurationSection logic.

🔐 Secrets Management Integration¶

Supports secrets loaded from:

Azure Key Vault (via DefaultAzureCredential)
.usersecrets
Environment Variables
CI/CD Variable Groups

🔒 Keys like ApiKey, ClientSecret, and TenantId are never hardcoded.

🧠 Generated Metadata¶

The blueprint emits:

{
  "config": {
    "boundOptions": "StripeOptions",
    "section": "Stripe",
    "environmentSupport": ["Development", "Staging", "Production"]
  }
}

✅ Summary¶

Every backend API library generated from this blueprint includes robust configuration scaffolding — environment-aware, options-bound, and secret-ready. This makes the client safe, portable, and CI/CD-friendly, whether running locally, in tests, or across cloud environments.

🧭 Unit, Integration, and Contract Testing Strategy¶

This section outlines the testing strategy built into the blueprint — ensuring that generated backend API libraries are verifiable through unit tests, integration tests (real and simulated), and contract tests aligned with observability and authentication expectations.

🔬 Testing Layers Generated¶

Layer	Type	Purpose
🧪 Unit Tests	Pure C# logic (e.g., auth header, DTO validation)	Fast feedback
🌐 Integration Tests	Live or mock endpoint invocations	End-to-end behavior
📜 Contract Tests	Validates client matches OpenAPI or expected response structure	Ensures schema sync
🔒 Security Tests	Verifies token injection, permission failures	Boundary enforcement

📂 Test Project Layout¶

/tests/
  GoogleAnalyticsClient.Tests/
    - StripeClientTests.cs
    - StripeAuthTests.cs
    - StripeResiliencyTests.cs
    - StripeMockServerFixture.cs

⚙️ Test Frameworks¶

🧪 MSTest (default) or xUnit, depending on template variant
🤖 MockHttpMessageHandler for simulating HTTP flows
🧱 TestServer or WireMock.Net for full protocol simulation
🔁 IOptionsSnapshot<T> + test-specific DI configuration

🧠 Agent-Initiated Test Generation¶

Agents generate tests from:

DSL (retryPolicy, auth, metrics → should retry on 503)
Sample payloads
MockServer DSL
Usage examples (e.g., from API docs)

Example auto-generated test case:

[TestMethod]
public async Task GetInvoice_ShouldRetryOn503()
{
    var mock = new MockHttpMessageHandler();
    mock.Expect("/invoices/inv_123")
        .Respond(HttpStatusCode.ServiceUnavailable);
    mock.Expect("/invoices/inv_123")
        .Respond(HttpStatusCode.OK, "application/json", "{...}");

    var client = new StripeClient(mock.ToHttpClient());
    var result = await client.GetInvoiceAsync("inv_123");

    Assert.IsNotNull(result);
    mock.VerifyNoOutstandingExpectation();
}

🤝 Contract Testing Option¶

When OpenAPI spec is known or imported:

Contract tests validate:
DTOs match response schema
Required fields present
HTTP methods and paths align

Tooling includes:

NSwag or OpenAPI.NET
WireMock with schema stubbing

📈 Telemetry Assertions¶

The blueprint injects test helpers to validate:

Logs emitted
Spans created
Retry metrics increased

AssertMetric("retry_attempt_count", expected: 2);
AssertSpan("StripeClient.CreateInvoice", status: SpanStatus.Ok);

🧪 Test Modes per Environment¶

Mode	Description
`Test`	Fast, mock-based
`Staging`	Live endpoint tests (optional pipeline trigger)
`CI`	Replays integration with local test server
`Chaos`	(future) Inject failure conditions via chaos agent

✅ Summary¶

The blueprint ensures every generated backend API library includes a complete testing stack — not only validating logic correctness, but also verifying telemetry, configuration, retries, and contracts. This improves confidence, security, and compliance in every service that consumes these libraries.

🧭 Mock Server and Sandbox Generation Support¶

Baseline template: connectsoft-api-library does not emit a dedicated mock-server web project; WireMock.Net is used in the scaffolded unit tests for HTTP client behavior. The material below describes a factory or agent extension (e.g. *.MockServer) when you add that project to the solution.

This section covers how an extended blueprint or pipeline may add a mock server alongside the client library. When present, the mock server acts as a sandboxed test double for local development, CI testing, AI agent self-call simulations, and contract validation — without needing real API access.

🧪 Purpose of the Mock Server¶

Use Case	Description
🧪 Local Testing	Simulates API responses for integration tests and debugging
🧠 Agent Sandbox	Allows AI agents to test calls without external dependencies
✅ CI Pipelines	Reliable test runs with no 3^rd-party failures
📜 Contract Testing	Validate generated client conforms to expected structure
🧱 Multi-tenant Simulation	Emulate different environments or tenants

🏗️ Folder Structure¶

/src/
  GoogleAnalyticsClient.MockServer/
    Controllers/
    Fixtures/
    Extensions/
    GoogleAnalyticsClient.MockServer.csproj

⚙️ Features of the Mock Server¶

Feature	Description
✅ Route matching	Handles all client interface methods
🧪 Predefined fixtures	Static or templated JSON files for repeatable outputs
🔄 Delay simulation	Artificial latency, timeouts for resiliency tests
🔁 Behavior switching	Return `200`, `404`, `503`, or malformed responses
🔐 Token check	Can optionally validate API keys, tokens
🧠 AI sandbox hooks	Allows agent-triggered overrides of behavior

🧩 Configuration Example¶

app.MapGet("/customers/{id}", (string id) => 
{
    return Results.Ok(new { id, name = "Test Customer", email = "test@connectsoft.ai" });
});

Or dynamically from fixture:

app.MapPost("/invoices", async (HttpContext ctx) =>
{
    var json = await File.ReadAllTextAsync("Fixtures/CreateInvoice.json");
    return Results.Json(JsonSerializer.Deserialize<object>(json)!);
});

📁 Fixture File Example¶

{
  "id": "inv_12345",
  "status": "draft",
  "customer": "cus_67890"
}

🧠 Agent Interaction¶

Agents like TestGeneratorAgent or RuntimeSimAgent can:

Launch the mock server in isolated mode
Inject temporary fixtures or behaviors via DSL
Validate outputs from the mock during replay
Record conversation for feedback loops

🔧 CLI Launch in Local Dev¶

dotnet run --project src/GoogleAnalyticsClient.MockServer

Also used by CI with environment variable USE_MOCK_SERVER=true

🔁 CI Integration¶

Runs in background process during test stage
Used for:
Contract validation
Resiliency testing
Retry simulation

🧠 DSL Control for Mock Mode¶

mockServer:
  enabled: true
  delayMs: 250
  failureRate: 10%
  returnMalformedJson: false

This allows the agent to simulate degraded or edge scenarios.

✅ Summary¶

Mock server generation is a first-class citizen in the backend API library blueprint. It enables agentic development, repeatable testing, and safer deployments — giving AI agents and human developers a controllable, realistic sandbox to test and iterate without risk.

🧭 Pipeline, Packaging, and NuGet Publication Blueprinting¶

This section defines how the backend API library blueprint includes automated DevOps pipeline scaffolding, packaging conventions, and NuGet publication setup. These make the library consumable across microservices, platforms, and other agents with minimal manual steps.

🧪 CI/CD Pipeline Objectives¶

Goal	Achieved by
✅ Build validation	.NET build, test, lint stages
✅ Test automation	Unit, integration, contract test runs
📦 NuGet packaging	`dotnet pack` with versioning rules
🚀 Secure publishing	Push to internal or public NuGet feeds
🔁 Blueprint traceability	Artifact tagging with run/session metadata

📁 File Structure¶

/azure-pipelines.yml
/.factory/publish.meta.json
/src/GoogleAnalyticsClient/
  - GoogleAnalyticsClient.csproj

⚙️ Generated Azure Pipelines File¶

trigger:
  branches:
    include: [ main ]

pool:
  vmImage: 'windows-latest'

variables:
  buildConfiguration: 'Release'

steps:
- task: UseDotNet@2
  inputs:
    packageType: 'sdk'
    version: '8.x'

- script: dotnet restore
- script: dotnet build --configuration $(buildConfiguration)
- script: dotnet test --configuration $(buildConfiguration) --logger trx
- script: dotnet pack --configuration $(buildConfiguration) -o $(Build.ArtifactStagingDirectory)
- task: PublishBuildArtifacts@1
- task: NuGetCommand@2
  inputs:
    command: 'push'
    packagesToPush: '$(Build.ArtifactStagingDirectory)/*.nupkg'
    nuGetFeedType: 'internal'
    publishVstsFeed: 'connectsoft-nuget-feed-id'

📦 NuGet Metadata Blueprint¶

<PropertyGroup>
  <PackageId>ConnectSoft.StripeClient</PackageId>
  <Version>1.2.4</Version>
  <Authors>ConnectSoft AI Factory</Authors>
  <Description>Typed API client for Stripe integration</Description>
  <RepositoryUrl>https://dev.azure.com/connectsoft/_git/StripeClient</RepositoryUrl>
</PropertyGroup>

🔐 Secure Feed Publishing¶

Mode	Strategy
Internal	Azure Artifacts feed with `vstsFeed`
Public	NuGet.org with API key secret
Scoped	Publish to tenant-specific feeds via agent parameter injection

🧠 Agent Collaboration¶

Agent	Role
`PipelineAgent`	Generates and validates `azure-pipelines.yml`
`PackageVersioningAgent`	Bumps version, edits `.csproj` and meta
`ArtifactRegistryAgent`	Pushes to configured NuGet feeds
`AuditTrailAgent`	Adds session ID to artifact metadata

🔁 Versioning Rules¶

Patch: Minor edits or bugfixes
Minor: New methods or endpoints added
Major: Breaking change in client interface
Blueprint version stored in .factory/version.json

Supports SemVer and metadata like:

{
  "version": "1.3.0-beta+build123",
  "originatingAgent": "LibraryScaffolderAgent",
  "timestamp": "2025-06-07T18:32Z"
}

🧪 Publish Validation¶

Blueprint includes test pipeline that:

Asserts nupkg structure
Validates README is present
Ensures dependency versions match factory policies

✅ Summary¶

The blueprint doesn’t just generate code — it generates a DevOps-ready, publishable library complete with pipeline, semantic versioning, and NuGet configuration. This makes integration, reuse, and CI/CD automation effortless for both agents and human developers.

🧭 Cross-Agent Consumption and Agent-to-Agent Contracts¶

This section explains how the generated backend API library can be safely and programmatically consumed by other agents within the ConnectSoft AI Software Factory — enabling agent-to-agent contracts, intelligent orchestration, and multi-agent workflows using shared, versioned SDKs.

🤖 Why Agent-to-Agent Contracts Matter¶

Benefit	Description
✅ Consistency	All agents use the same SDK interfaces and models
✅ Decoupling	Interface hides low-level HTTP complexity
🧠 Reasoning	Agents reason over clear method signatures
🔁 Reusability	Reuse library across design-time and runtime agents
🔒 Trust	Versioned contract prevents breaking changes

🧠 Agent Usage Examples¶

Consumer Agent	Purpose
`TestOrchestratorAgent`	Calls generated mock server using `IStripeClient`
`RuntimeSimAgent`	Executes sample flow to validate expected results
`MCP Integration Agent`	Binds external skill to generated library methods
`ValidationAgent`	Verifies library behavior against blueprint DSL
`CodeReviewerAgent`	Analyzes interface for DDD and traceability standards

🧩 Agent DSL Output Example¶

useLibrary: ConnectSoft.StripeClient
methods:
  - name: CreateInvoiceAsync
    input: CreateInvoiceRequest
    output: InvoiceResponse
    requiredHeaders: [ Authorization ]
    retryable: true
    observable: true

This DSL is generated alongside the blueprint and used as input to agentic chains.

⚙️ AI Usage (as Agent Tools)¶

When exposed to Microsoft Agent Framework agents:

[Description("Create a Stripe invoice for the customer")]
public async Task<InvoiceResponse> CreateStripeInvoiceAsync(
    [Description("Stripe customer id")] string customerId)
{
    return await _stripeClient.CreateInvoiceAsync(new CreateInvoiceRequest
    {
        CustomerId = customerId,
        AutoAdvance = true
    });
}

✅ The generated interface becomes a plug-and-play skill in the kernel function system, enabling hybrid agent + OpenAI workflows.

🧱 Contract Metadata (`.factory/agent.contract.json`)¶

{
  "interface": "IStripeClient",
  "methods": [
    {
      "name": "CreateInvoiceAsync",
      "inputs": ["customerId", "amount"],
      "output": "InvoiceResponse",
      "auth": "apiKey"
    }
  ],
  "origin": "agent-blueprint-run-02458"
}

Agents fetch this metadata to dynamically inspect capabilities and emit calls.

🧪 Contract-Driven Validation¶

Contract metadata is used for:

Auto-prompt generation
Request replay testing
Failure path simulation
Version mismatch detection (if consumer requires a method not found in current version)

🤝 Example Multi-Agent Chain¶

sequenceDiagram
    DevAgent ->> BlueprintAgent: Request Stripe API library
    BlueprintAgent ->> CodeAgent: Generate client
    CodeAgent ->> PackageAgent: Push NuGet
    RuntimeAgent ->> NuGet: Install ConnectSoft.StripeClient
    RuntimeAgent ->> StripeClient: CreateInvoiceAsync()

Hold "Alt" / "Option" to enable pan & zoom

📦 One library, many consumers: orchestrators, validators, Agent Framework agents, DevOps agents, and runtime clusters.

✅ Summary¶

The backend API library blueprint produces artifacts that are not just code — they are agent-readable, memory-indexed, skill-convertible contracts. This enables deep reuse across the entire agentic lifecycle and reinforces composability, observability, and automation at platform scale.

🧭 Memory, Metadata, and Traceability in Blueprint Artifacts¶

This section explores how every generated backend API library embeds traceable metadata and integrates into the platform's memory system — enabling full observability, lookup, and auditability for every artifact produced by the AI Software Factory.

🧠 Why Memory & Metadata Matter¶

Capability	Purpose
🧭 Traceability	Understand what agent produced what artifact, from which prompt
🔁 Replayability	Rebuild any artifact from blueprint and memory
🧠 Context Awareness	Other agents can search for and reason over prior blueprints
🧪 Provenance	Verify trust chain of generated code
📦 Reuse	Compose new solutions using prior libraries as base packages

📂 Metadata Files Injected into Output¶

File	Purpose
`.factory/blueprint.meta.json`	Blueprint ID, version, inputs, producers
`.factory/agent.contract.json`	Machine-readable method + parameter contract
`.factory/memory.tags.yaml`	Vector DB tags (domain, purpose, API group)
`README.md` (with prompt header)	Human-readable trace of what was generated and why

🧬 Sample `blueprint.meta.json`¶

{
  "blueprintId": "backend.api.library",
  "name": "ConnectSoft.StripeClient",
  "producedByAgent": "LibraryScaffolderAgent",
  "version": "1.0.0",
  "timestamp": "2025-06-07T22:00:15Z",
  "sourceInputs": [
    "https://api.stripe.com/v1",
    "OpenAPI spec",
    "custom DSL"
  ],
  "linkedBlueprints": [
    "observability.default",
    "configuration.standard"
  ],
  "memoryIndex": "agentic-blueprints/backend.api.library/stripeclient"
}

🔖 Memory Tagging (Vector Indexing)¶

The blueprint includes a memory.tags.yaml file:

tags:
  domain: "Billing"
  system: "Stripe"
  type: "backend.api.library"
  methodProfiles:
    - create_invoice
    - get_customer
  observability: true
  retryable: true

This is embedded into the memory ingestion pipeline, enabling:

Searchable lookup from any agent
Memory recall in downstream factories
Cross-blueprint reasoning (e.g., infer capabilities)

🧠 Embedding Strategy¶

Interface signatures, model class names, method names → embedded into vector DB
Token metadata (e.g., HTTP verbs, paths, common errors) → embedded for contract memory
Blueprint DSL fragments → embedded to power reuse and validation prompts

Stored in vector collections:

blueprints/backend.api.library
clients/http.methods
skills/generated-by-agent

🔍 Traceability Hooks¶

Agents can answer:

"Which agent generated this client?"
"When was this client last updated?"
"What API spec was this client based on?"
"Does a library for service X already exist?"

🧠 Used by Other Agents¶

Agent	Use
`KnowledgeAgent`	Lookup previously generated libraries
`ReuseOrchestratorAgent`	Reuses existing blueprints via vector similarity
`RegenerationAgent`	Rebuilds broken artifacts from prompt + metadata
`AuditAgent`	Validates contract compliance across versions

✅ Summary¶

This blueprint doesn’t just generate clients — it emits memory-aware, self-describing artifacts. With structured metadata, memory tagging, and embedding support, every library becomes a first-class citizen in the AI Software Factory’s collective intelligence.

🧭 Error Handling, Fallbacks, and Developer Feedback Features¶

This section describes how the backend API library blueprint integrates structured error handling, optional fallback strategies, and tooling for developers and agents to analyze, log, and respond to failures in predictable and traceable ways.

💥 Error Types Handled¶

Type	Examples	Handling Strategy
HTTP Errors	4xx, 5xx, 429	Standardized exception + retry logic
Transport Failures	DNS, Timeout, ConnectionRefused	Retry + circuit breaker
Deserialization Errors	Invalid/missing fields	Safe fallback or developer trace
Auth Failures	401, 403	Token refresh or prompt user
Rate Limits	429 + `Retry-After`	Observes backoff policy

🧱 Unified Error Model¶

Generated libraries use a common exception hierarchy:

public class ApiException : Exception
{
    public HttpStatusCode StatusCode { get; }
    public string? ResponseBody { get; }
    public string? Endpoint { get; }

    public ApiException(string message, HttpStatusCode statusCode, string? responseBody = null)
        : base(message) { ... }
}

public class AuthException : ApiException { ... }
public class DeserializationException : ApiException { ... }
public class RetryExhaustedException : ApiException { ... }

🧪 Developer-Visible Feedback¶

All failures are logged with:

Request URL, headers (sanitized)
Status code and error body
Retry attempts
TraceId / CorrelationId

Example log:

{
  "level": "Error",
  "message": "Failed to fetch invoice inv_123",
  "statusCode": 503,
  "retries": 3,
  "endpoint": "/invoices/inv_123",
  "traceId": "e293..."
}

🔄 Optional Fallback Strategies¶

Defined in DSL or injected later:

fallbacks:
  GetInvoiceAsync:
    mode: static
    response: "Fixtures/GetInvoiceFallback.json"

OR in generated code (future support):

[FallbackResponse(typeof(InvoiceResponse), Source = "json", Path = "fallbacks/invoice.json")]
Task<InvoiceResponse> GetInvoiceAsync(string invoiceId);

🧠 Agent-Driven Error Handling¶

Agent	Role
`TestAgent`	Validates retry, timeout, error boundaries
`ObservabilityAgent`	Emits spans with failure markers
`RuntimeSimAgent`	Verifies fallback pathways
`DocsAgent`	Generates "how to handle this error" sections

📘 Error Documentation Blueprint¶

Part of the README and .factory/errors.json:

{
  "operation": "CreateInvoiceAsync",
  "errors": [
    { "code": 401, "meaning": "Invalid API Key", "suggestion": "Check StripeOptions.ApiKey" },
    { "code": 429, "meaning": "Rate Limit", "suggestion": "Back off and retry after delay" }
  ]
}

🔁 Integration with Observability¶

Each error emits:

🪵 ILogger.LogError with detailed context
📈 Metrics like client_error_count{code=503}
📡 Tracing span with status code and failure tag

This makes failure rates and retry loops fully observable.

✅ Summary¶

Robust, structured error handling is a core pillar of the backend API blueprint. From retry-aware exceptions to agent-visible logs and fallback JSON, every failure becomes an opportunity for recovery, traceability, and continuous improvement across automated and manual consumers.

🧭 Versioning, Deprecation, and Backward Compatibility Strategies¶

This section outlines how the backend API library blueprint implements semantic versioning, deprecation signaling, and backward compatibility enforcement across generated artifacts — ensuring stability, safe upgrades, and contract integrity across consuming services and agents.

🧮 Versioning Model¶

Component	Rule
📦 NuGet Package	Uses SemVer 2.0.0
🧠 Blueprint Version	Embedded in metadata (`blueprint.meta.json`)
🧾 Contract Hash	Used for backward compatibility checks
📁 Source Tag	Git tag/version injected into project README and changelog

Example:

{
  "packageVersion": "1.3.2",
  "blueprintVersion": "v2",
  "apiContractHash": "cfb294e3...",
  "generatedBy": "agent-blueprint-run-05923"
}

🧪 Change Detection Heuristics¶

Agents or the pipeline detect:

Change	Impact
New method added	Minor bump
Existing method removed	Major bump
Input/output changed	Major bump
Retry policy tweaked	Patch
Logging format changed	Patch (internal)

Detected via:

Interface diffs (AST or Roslyn analysis)
OpenAPI diff (when spec-based)
Contract hash comparison

⚠️ Deprecation Mechanism¶

Deprecation is encoded in both metadata and source code:

[Obsolete("Use CreateInvoiceV2Async instead.")]
public Task<InvoiceResponse> CreateInvoiceAsync(...) { ... }

And reflected in:

{
  "operation": "CreateInvoiceAsync",
  "status": "deprecated",
  "replacement": "CreateInvoiceV2Async"
}

🧠 Agents see this and auto-adjust their flows.

📜 Changelog Generation¶

Agents generate a changelog:

## v1.4.0

- Added: `SendNotificationAsync` method
- Changed: `RetryPolicy` now exponential backoff by default
- Deprecated: `SendEmailAsync` (use `SendNotificationAsync`)

Stored in CHANGELOG.md and .factory/changelog.md.

🧠 Consumers React to Versions¶

Agent	Behavior
`CodeReviewerAgent`	Flags major change without test coverage
`UpdateAssistantAgent`	Suggests upgrade path for affected consumers
`RuntimeValidatorAgent`	Warns if deprecated method is still used
`BuildPinnerAgent`	Locks to safe version range (e.g., `<2.0.0`)

🔁 Support for Multiple Versions¶

The factory allows:

Side-by-side packaging (MyClient.V1, MyClient.V2)
Adapter classes or shims
Graceful opt-in to new interface with compatibility toggle

🧪 Version Tests (Optional)¶

Generated tests ensure older methods are still callable (if supported):

[TestMethod]
public void DeprecatedMethod_StillCompilesAndRuns()
{
    var client = new StripeClient(...);
    var invoice = client.CreateInvoiceAsync("cus_123").Result;
    Assert.IsNotNull(invoice);
}

✅ Summary¶

Versioning in the backend API library blueprint is not just syntactic — it’s semantic, agent-visible, and upgrade-aware. With embedded changelogs, deprecation notices, and behavioral diffing, this blueprint ensures stable evolution and safe reuse across generations of software and automation agents.

🧭 Runtime Extension Points and Composition Hooks¶

This section explains how the backend API library blueprint enables safe extensibility and runtime customization through generated extension points, partial methods, composition hooks, and plugin-ready structures — all while preserving stability, testability, and compatibility.

🧩 Why Extension Points Matter¶

Need	Solution
🔁 Add custom headers or transformations	Request/response interceptors
🧠 Inject observability hooks	Span decorators
🧪 Override retry/fallback logic	Pluggable policies
🔄 Replace endpoint behavior	Partial method stubs
📦 Plug in external libraries	DI composition modules

🧱 Composition Hook Locations¶

Hook	Purpose
`HttpRequestMessageBuilder`	Modify request before send
`IResponseParser`	Customize deserialization and validation
`AuthHandler`	Token injection, renewal
`ILoggerDecorator`	Extend observability span
`ErrorClassifier`	Wrap specific HTTP responses into typed exceptions

These hooks are injected via DI or method override stubs.

🧠 Example: Request Customizer Hook¶

public interface IRequestCustomizer
{
    void Customize(HttpRequestMessage request);
}

Injected into the client:

requestCustomizer?.Customize(request);

Allows agent or developer to:

Add tenant ID
Inject trace headers
Modify URL dynamically

🧩 Partial Method for Override¶

public partial class StripeClient
{
    partial void OnBeforeSend(HttpRequestMessage request);
    partial void OnAfterReceive(HttpResponseMessage response);
}

These methods are no-ops unless implemented. Safe for extension in shared libraries.

📦 Generated Extension Points in DI¶

services.AddTransient<IRequestCustomizer, CustomHeaderInjector>();
services.AddScoped<IResponseParser, CustomParser>();

Or configured via factory:

.AddHttpClient<IStripeClient, StripeClient>((sp, client) => {
    var auth = sp.GetRequiredService<IAccessTokenProvider>();
    client.DefaultRequestHeaders.Authorization = new(...);
});

🔁 Agent-Powered Composition¶

Agents can:

Extend generated classes using partial files
Register new behaviors via metadata DSL:

extensions:
  requestHeaderInjector:
    enabled: true
    header: "X-Tenant-ID"
    source: "ContextResolverService"

Inject handlers during orchestration or test setup
Publish customized libraries as variants

🤝 Inter-Agent Hooks¶

Some extensions are targeted at other agent types, e.g.:

Observability spans injected by ObservabilityAgent
Tracing headers managed by RequestTracerAgent
Error classifiers aligned with ContractValidatorAgent

This enables safe chaining across platform clusters.

⚙️ Extension Strategy: Open/Closed Principle¶

Open: via interfaces, delegates, DI hooks
Closed: core retry/auth policies guarded by factory
Overrides must be opt-in via DSL or agent contract extension

✅ Summary¶

Every backend API client generated from this blueprint includes safe and composable runtime hooks. Developers and agents can extend behavior without modifying core logic, ensuring platform integrity while enabling rich cross-agent composition and specialization.

🧭 Blueprint-Driven Documentation and Developer Portal Integration¶

This section details how the blueprint generates structured documentation artifacts for developer consumption, agent reasoning, and integration into internal and external developer portals, ensuring the client library is understandable, traceable, and self-describing.

📘 Types of Documentation Generated¶

Format	Purpose
`README.md`	Entry-point doc with usage examples
`docs/` Markdown	Advanced usage, config, testing, security
`.factory/errors.json`	Structured error reference
`.factory/agent.contract.json`	Agent-readable method and type schema
`CHANGELOG.md`	Human + agent trace of evolution
`docs/openapi.json` (optional)	If derived from OpenAPI or Swagger spec

📁 Folder Structure¶

/docs/
  README.md
  usage.md
  configuration.md
  troubleshooting.md
  authentication.md
  testing.md
  changelog.md
.factory/
  agent.contract.json
  errors.json

📄 README.md Sample¶

# ConnectSoft.StripeClient

This library provides a typed API interface to Stripe for use within ConnectSoft services and AI agents.

## 🔌 Usage

```csharp
var result = await _stripeClient.CreateInvoiceAsync(new() {
  CustomerId = "cus_abc123",
  AutoAdvance = true
});
```

## 📦 Configuration

Bind options from `Stripe` section in `appsettings.json`.

## 🔁 Retry

The client retries 3 times on 429, 503, and timeout errors.

🔄 Regeneration and Update Hooks¶

Documentation is versioned and regenerated automatically when:

Methods change
Retry/auth/fallback policies are added or removed
Blueprint version or contract hash is updated

Ensures drift between code and docs is minimized.

🧠 Agent-Readable Contracts¶

{
  "methods": [
    {
      "name": "CreateInvoiceAsync",
      "parameters": ["CustomerId", "AutoAdvance"],
      "output": "InvoiceResponse",
      "auth": true,
      "retryable": true
    }
  ],
  "errorModel": "ApiException",
  "observable": true
}
````

Used by:

* `CodeReviewerAgent`
* `RuntimeTestAgent`
* `PromptOrchestratorAgent`

---

### 🌐 Developer Portal Integration

| Portal                 | Integration                                             |
| ---------------------- | ------------------------------------------------------- |
| ConnectSoft DevCenter  | Indexed into internal portal registry                   |
| AI Blueprint Browser   | Searchable via memory and blueprint viewer              |
| Public Docs (optional) | Exportable to Markdown, OpenAPI, or doc-as-code formats |
| ChatGPT Plugin Builder | SDK + method hints injected via prompt metadata         |

Blueprint emits:

* Tags for search
* Links to changelog, README, test coverage
* Downloadable package metadata

---

### 🧠 Developer Feedback Loops

Future versions may include:

* Embedded "copy this usage" button
* Error codes → help article mapping
* Interactive client playground using mock server
* Agent-published usage patterns and hints

---

### ✅ Summary

Documentation is a **first-class output** of the blueprint — not an afterthought. It’s human-friendly, agent-readable, portal-integrated, and change-aware. This ensures maximum clarity, adoption, and platform alignment across all developer and AI agent consumers.

---

## 🧭 Blueprint-Driven Compliance, Auditability, and Policy Alignment

This final section covers how the backend API library blueprint enforces **compliance with organizational policies**, emits **audit metadata**, and aligns with **security, observability, and quality requirements** across all generated libraries — ensuring trust, accountability, and governance at scale.

---

### 🔐 Compliance Domains Addressed

| Domain            | Compliance Strategy                                     |
| ----------------- | ------------------------------------------------------- |
| 🔐 Security       | Token usage, sensitive field masking, TLS-only clients  |
| 📊 Observability  | Span creation, error telemetry, retry logging           |
| 🔁 Retry Policies | Blueprint-based backoff settings, retry limits          |
| 📦 Packaging      | Naming conventions, license headers, artifact structure |
| ⚖️ Licensing      | Default MIT/ConnectSoft license headers with validation |
| 📜 Documentation  | Required sections and changelog generation              |
| 👤 Data Privacy   | Field-level PII masking and logging policies            |

---

### 📜 Policy Rules Enforced by Blueprint

| Rule                                                          | Enforced By     |
| ------------------------------------------------------------- | --------------- |
| All HTTP clients must use `ILogger` and structured logs       | Template        |
| Retryable methods must expose `RetryPolicyOptions`            | DSL constraint  |
| Public-facing packages must contain `README.md` and `LICENSE` | Linter          |
| `ApiKey` must be sourced from `IOptions` or `KeyVault` only   | Generator guard |
| DTO fields with PII tags are auto-masked in logs              | Serializer shim |
| All exceptions must extend `ApiException`                     | Validator agent |

---

### 📁 Audit Files and Metadata

| File                          | Purpose                                        |
| ----------------------------- | ---------------------------------------------- |
| `.factory/audit.json`         | Agent trail, session IDs, prompt hashes        |
| `README.md` header            | Includes creation origin and blueprint version |
| `changelog.md`                | Shows code changes across blueprint runs       |
| `.factory/policy.report.json` | Which policies were enforced or bypassed       |

Example `.factory/audit.json`:

```json
{
  "generatedBy": "LibraryScaffolderAgent",
  "sessionId": "run-2321312",
  "promptFingerprint": "8a9cb0f8...",
  "blueprintVersion": "v2.3",
  "policyCompliance": ["auth.tokens.secured", "observability.traces.emitted"],
  "timestamp": "2025-06-07T23:45:02Z"
}

🧠 Agent Alignment¶

Agent	Use
`PolicyValidatorAgent`	Validates blueprint output against factory rules
`SecurityScannerAgent`	Reviews token handling and URL injection safety
`AuditTrailAgent`	Records generator identity and session for each artifact
`DocumentationAgent`	Injects policy reference into public docs
`ContractValidatorAgent`	Asserts backward compatibility against contract hash

🔍 Blueprint Policy Profiles¶

The blueprint can inject policy levels:

compliance:
  profile: strict
  rules:
    - auth.tokens.required
    - observability.enabled
    - retry.policy.defined
    - changelog.required

These policies become binding for the agent execution context.

🔐 Security Hooks¶

HTTP clients require TLS or fail-fast
Authorization header redacted from all logs
Request tracing headers (e.g. X-Correlation-ID) injected by default
Access tokens must be non-null or throw

📘 Audit Chain Traceability¶

Mermaid view:

flowchart TD
    A[LibraryScaffolderAgent] --> B[BlueprintEmitter]
    B --> C[.factory/blueprint.meta.json]
    B --> D[.factory/audit.json]
    B --> E[NuGet Package]
    E --> F[AgentOrRuntimeConsumer]

Hold "Alt" / "Option" to enable pan & zoom

Every artifact is cryptographically and semantically linked back to its origin.

✅ Summary¶

This final layer of the backend API library blueprint enforces a trustworthy, compliant, auditable software generation process. With metadata trails, enforcement hooks, and policy-aligned generation, ConnectSoft ensures that every output — even from AI agents — meets enterprise standards and regulatory needs.

📘 Backend API Library Blueprint¶

Implementation alignment (read first)¶

🧭 Introduction and Purpose¶

🎯 Purpose¶

🏭 Use in the Software Factory¶

📦 Typical Output Artifacts¶

💡 Blueprint Pattern Class¶

🔗 Related Blueprints¶

✅ Summary¶

🧭 Key Principles and Design Alignment¶

🧱 Clean Architecture Alignment¶

🧩 Domain-Driven Design (DDD) Principles¶

🔁 Event-Driven and Observable¶

📡 Observability-First Design¶

🧰 Modular, Composable, Extensible¶

🛡 Security-First Architecture¶

🧠 AI-Aware Blueprint Design¶

✅ Summary¶

🧭 Generation Source: Template CLI and Blueprint Definition¶

⚙️ .NET CLI Template¶

🧠 Input: Blueprint DSL / YAML¶

⚙️ Template Features Supported¶

🧠 Output: Traceability Context¶

📘 README.md Snippet from Template¶

✅ Summary¶

🧭 High-Level Folder and Project Layout¶

📂 Solution Folder Structure¶

📦 Key Subfolders Explained¶

🧩 Layer Alignment¶

📘 README Structure (Auto-Generated)¶

✅ Summary¶

🧭 Artifact Types Produced by the Blueprint¶

📦 Artifact Overview¶

🧠 Deep Integration into Factory Memory¶

📘 Sample Artifact Directory Tree¶

🧠 Agents Producing Artifacts¶

🧩 Example Use: App Consumes Published NuGet¶

✅ Summary¶

🧭 When to Use This Blueprint¶

🧩 Primary Use Cases¶

🎯 Ideal Blueprint Characteristics¶

🧠 Triggering Agents¶

📘 Examples¶

🧩 Library vs. Microservice Decision¶

✅ Summary¶

🧭 Blueprint DSL and Configurable Parameters¶

📘 Sample DSL Snippet¶

🔧 Supported Parameters¶

🧠 DSL Usage in Agent Prompts¶

🧩 Modular Extensions¶

🧬 Versioned DSL¶

📘 Validated DSL Schema (JSON)¶

✅ Summary¶

🧭 Example Instantiation Flow: From DSL to Working Library¶

📘 Scenario: Stripe API Integration¶

🧠 Step-by-Step Agent Flow¶

📂 Input DSL¶

🏗️ CLI Generation¶

🧪 Example Generated Interface¶

🚀 Sample Usage (Consumer App)¶

📘 Generated README (Excerpt)¶

🔁 Trace Metadata¶

✅ Summary¶

🧭 Cross-Blueprint Dependencies and Shared Integrations¶

🔁 Cross-Blueprint Relationship Map¶

🧩 Typical Dependencies¶

🔁 Blueprint Reuse Example¶

🧠 Agent-Level Collaboration¶

📘 Blueprint Metadata Extension¶

📦 Shared Packages/Artifacts¶

📂 Output Folder Enrichment¶

✅ Summary¶

🧭 Typed HTTP Client Design and Interface Generation¶

🔧 Interface-First Design Pattern¶

🏗️ Generated via Agentic Template¶

🧩 Benefits of Interface-First Approach¶

🔌 Typed HttpClient Injection¶

📂 Project Layout¶

🧠 AI Prompt Sample¶

✅ Summary¶

🔌 Typed `HttpClient` Injection¶