Bootstrap a new framework integration for apcore. Scaffolds the project with endpoint scanners, configuration system, context mapping, CLI commands, demo project, and Docker setup. Learns patterns from existing integrations (django-apcore, flask-apcore, nestjs-apcore).

Apcore Skills — Integration

⚡ Execution Entry Point (READ THIS FIRST)

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Bootstrap a new framework integration that connects a web framework to the apcore ecosystem.

Iron Law

EVERY INTEGRATION MUST IMPLEMENT THE SAME 5 CORE CAPABILITIES: scan endpoints, register modules, map request context, serve via MCP, and export to OpenAI tools format.

Anti-Rationalization Table

Thought	Reality
"This framework is different, it needs a different approach"	The 5 core capabilities are the same. Only the framework-specific adapters differ.
"I'll skip the demo project"	Demo projects are how users evaluate integrations. Always include one.
"CLI commands can come later"	CLI is the primary UX. `scan` and `serve` commands are required from day one.
"I'll just wrap the core SDK directly"	Integrations must use apcore-discovery for scanner logic to ensure consistency.

When to Use

Creating a new framework integration (e.g., fastapi-apcore, express-apcore, gin-apcore)
Re-scaffolding an existing integration that needs restructuring
Evaluating what's needed for a new framework integration

Command Format

/apcore-skills:integration <framework> [--lang python|typescript|go] [--ref django-apcore]

Parameter	Required	Default	Description
`<framework>`	Yes	—	Target framework: `fastapi`, `express`, `gin`, `spring`, `actix`, etc.
`--lang`	No	auto-detect	Language of the framework
`--ref`	No	auto-detect	Reference integration to learn patterns from

5 Core Capabilities

Every apcore framework integration must provide:

#	Capability	Description	CLI Command
1	Endpoint Scanner	Discover framework routes and convert to apcore module definitions	`{framework} apcore scan`
2	Module Registry	Register scanned endpoints as apcore modules with metadata	(automatic)
3	Context Mapping	Map framework request objects to apcore `Context`	(automatic)
4	MCP Server	Start an MCP server exposing registered modules as tools	`{framework} apcore serve`
5	OpenAI Export	Export registered modules as OpenAI-compatible tool definitions	`{framework} apcore export`

Context Management

Steps 2 and 4 use sub-agents. Step 2 analyzes the reference integration. Step 4 generates the project skeleton. Main context retains only structured summaries.

Workflow

Step 0 (ecosystem) → 1 (parse args) → 2 (analyze reference) → 3 (framework research) → 4 (scaffold) → 5 (demo project) → 6 (plan) → 7 (summary)

Detailed Steps

Step 0: Ecosystem Discovery

@../shared/ecosystem.md

Step 1: Parse Arguments

Parse $ARGUMENTS:

Extract <framework> — required, use AskUserQuestion if missing
Extract --lang — auto-detect from framework:
- Python frameworks: fastapi, flask, django, starlette, falcon, tornado
- TypeScript frameworks: express, fastify, nestjs, hono, koa
- Go frameworks: gin, echo, fiber, chi
- Rust frameworks: actix, axum, rocket
- Java frameworks: spring, quarkus, micronaut
- PHP frameworks: laravel, symfony, slim, lumen
Extract --ref — resolve reference integration (priority order):
- If --ref explicitly specified: use that
- If CWD is an existing integration repo (e.g., in django-apcore/): use CWD repo as reference
- Otherwise auto-detect: same-language integration preferred, fall back to any existing integration

Derive target repo name: {framework}-apcore Derive target path: {ecosystem_root}/{framework}-apcore/

Display:

Integration Bootstrap:
  Framework:  {framework}
  Language:   {lang}
  Reference:  {ref-repo}
  Target:     {target-path}

Step 2: Analyze Reference Integration (Sub-agent)

Spawn Agent(subagent_type="general-purpose"):

Sub-agent prompt:

Analyze the reference integration at {ref_path} to understand the pattern for apcore framework integrations.

Read the following key files:
1. Main extension/app file (extension.py, apps.py, or module entry)
2. Config file (config.py, settings.py) — extract all APCORE_* settings
3. Scanner directory (scanners/) — how framework endpoints are discovered
4. Context mapping (context.py) — how request → apcore Context works
5. Registry (registry.py) — how modules are registered
6. CLI commands (cli.py, management/) — what commands are available
7. Output writers (output/) — how bindings are written
8. README.md — for user-facing documentation patterns
9. examples/ or demo/ — demo project structure

Return a structured analysis:

INTEGRATION_PATTERN:
  framework: {framework}
  language: {lang}
  version: {version}

EXTENSION_MECHANISM:
  How the integration hooks into the framework: {description}
  Entry point: {file and class/function}

CONFIGURATION:
  Settings prefix: APCORE_
  Settings count: {N}
  Key settings:
    - {SETTING_NAME}: {type} = {default} — {description}

SCANNER_PATTERN:
  Scanner types: {list of scanner variants, e.g., DRF, django-ninja}
  How endpoints are discovered: {description}
  How params are extracted: {description}

CONTEXT_MAPPING:
  How framework request → apcore Context: {description}
  Authentication extraction: {description}

CLI_COMMANDS:
  - {command}: {description}

DEMO_STRUCTURE:
  - {file}: {purpose}

Error handling:
- If the reference repo path does not exist, return: STATUS: NOT_FOUND, REASON: "Reference integration not found at {path}"
- If expected directories (scanners/, output/) are missing, note them and analyze what IS available
- If config file not found, note it and continue with partial analysis
- If README.md is missing, skip documentation pattern analysis

Keep summary to ~3-4KB.

Store as ref_analysis. If sub-agent returns STATUS: NOT_FOUND, use AskUserQuestion to provide a different reference or proceed without reference (scaffold from conventions only).

Step 3: Framework-Specific Research

Use AskUserQuestion to gather framework-specific information:

Question 1: "Which {framework} routing mechanism should the scanner target?"
- Options based on framework (e.g., for FastAPI: "Path operations (Recommended)" / "APIRouter" / "Both")
Question 2: "Which authentication patterns should context mapping support?"
- Options: "Bearer token (Recommended)" / "Session-based" / "Both" / "Custom"
Question 3 (if framework has multiple API styles): "Which API definition style?"
- Options depend on framework

Store framework_config.

Step 4: Scaffold Project (Sub-agent)

@../shared/conventions.md (refer to "Framework Integration structure" section)

Spawn Agent(subagent_type="general-purpose"):

Sub-agent prompt:

Create the project skeleton for {framework}-apcore at {target-path}.

Language: {lang}
Framework: {framework}
Reference pattern: {ref_analysis summary}
Framework config: {framework_config}

## Required Structure

{target-path}/
├── {build-config}                           # pyproject.toml / package.json
├── .gitignore
├── README.md                                # Installation, Quick Start, Configuration, CLI
├── CHANGELOG.md
├── LICENSE                                  # Detect from ecosystem or ask user (MIT / Apache-2.0)
├── src/{package_name}/
│   ├── {main-module}                        # __init__.py / index.ts with public exports
│   ├── extension.{ext}                      # Framework integration entry point
│   │                                        # (or apps.py for Django-style)
│   ├── config.{ext}                         # APCORE_* configuration with all settings
│   │                                        # (include: ENABLED, DEBUG, SCANNERS, AUTH, TRANSPORT, etc.)
│   ├── registry.{ext}                       # Module registration from scanned endpoints
│   ├── context.{ext}                        # Request → apcore Context mapping
│   ├── scanners/
│   │   ├── {main-module}                    # Scanner exports
│   │   └── {framework-scanner}.{ext}        # Framework-specific endpoint scanner
│   ├── output/
│   │   ├── {main-module}
│   │   └── yaml_writer.{ext}               # YAML binding file writer
│   ├── cli.{ext}                            # CLI commands: scan, serve, export
│   └── observability.{ext}                  # Optional: framework-specific tracing
├── tests/
│   ├── {test-config}
│   ├── conftest.{ext}                       # Shared fixtures
│   ├── test_extension.{ext}
│   ├── test_config.{ext}
│   ├── test_scanner.{ext}
│   ├── test_context.{ext}
│   └── test_cli.{ext}
└── examples/
    └── demo/
        ├── {build-config}                   # Demo app build file
        ├── app.{ext}                        # Minimal framework app with sample endpoints
        ├── Dockerfile
        └── docker-compose.yml               # App + apcore-mcp server

## Implementation Requirements

1. **extension.{ext}**: Framework plugin/extension class that:
   - Initializes apcore Registry on startup
   - Runs scanner to discover endpoints
   - Registers discovered modules

2. **config.{ext}**: Configuration class with ALL standard APCORE_* settings:
   APCORE_ENABLED (bool, True)
   APCORE_DEBUG (bool, False)
   APCORE_SCANNERS (list, ["auto"])
   APCORE_INCLUDE_PATHS (list, [])
   APCORE_EXCLUDE_PATHS (list, [])
   APCORE_MODULE_PREFIX (str, "")
   APCORE_AUTH_ENABLED (bool, False)
   APCORE_AUTH_STRATEGY (str, "bearer")
   APCORE_TRANSPORT (str, "stdio")
   APCORE_HOST (str, "0.0.0.0")
   APCORE_PORT (int, 8808)
   {Add framework-specific settings}

3. **scanners/{scanner}.{ext}**: Scanner that:
   - Walks framework route table
   - Extracts: path, method, params (name, type, required, default), description
   - Converts to apcore module definitions
   - Respects include/exclude path patterns

4. **context.{ext}**: Context factory that:
   - Maps framework request → apcore Context
   - Extracts auth info (Bearer token, session, etc.)
   - Handles async/sync appropriately

5. **cli.{ext}**: Commands:
   - `scan` — Discover endpoints and display/write bindings
   - `serve` — Start MCP server with discovered modules
   - `export` — Export to OpenAI tools JSON format

All files should have proper stubs with TODO markers for implementation.

Naming conventions:
- Python: snake_case for functions/methods, PascalCase for classes
- TypeScript: camelCase for functions/methods, PascalCase for classes
- Go: PascalCase for public, camelCase for private
- Rust: snake_case for functions/methods, PascalCase for types
- Java: camelCase for methods, PascalCase for classes

Error handling:
- If {target-path} is not writable, return: STATUS: WRITE_ERROR, REASON: "{description}"
- If a file cannot be created, skip it and include in the return as "{file} (SKIPPED: {reason})"
- If the framework is not recognized, proceed with generic scaffold and note: "Unknown framework — used generic pattern"

Create ALL files listed. Return file list.

Verify after sub-agent:

Build config exists
At least scanner, config, extension, context, cli files exist
Tests directory has test files
Examples/demo directory exists

Step 5: Generate Demo Project

If demo directory wasn't fully created by Step 4, create it:

Write a minimal demo app that:

Creates a {framework} app with 3-5 sample CRUD endpoints
Integrates apcore via the extension
Includes docker-compose.yml with:
- App service
- Optional: MCP server service (using apcore-mcp)
Includes README.md with setup instructions

Step 6: Generate Code-Forge Config and Feature Specs

Write .code-forge.json and generate feature specs for code-forge planning.

Feature specs to generate (one per core capability):

scanner.md — Endpoint scanning for this framework
config.md — Configuration system
context.md — Request-to-context mapping
registry.md — Module registration
cli.md — CLI commands (scan, serve, export)
observability.md — Framework-specific tracing (optional)

Each feature spec MUST include:

Purpose — what the feature does
Public API surface — classes / functions / CLI commands introduced by this integration
Acceptance criteria
One ## Contract: ClassName.method block per public method — per shared/contract-spec.md. The integration's public methods are scanner discovery entry points, config loader, context factory, CLI command entry points. Fill Contract fields from the reference integration ({ref_path}) where possible; mark the rest as TODO. Never emit an empty Contract block — if inference impossible, skip that method and surface as "Contract skeleton deferred for {method} — fill by hand" in the summary.
Core-SDK consumer contract — for every call the integration makes into the core SDK (e.g., Registry.register, Executor.execute, Context(...)), cite the upstream ## Contract: in apcore/docs/features/*.md and record which inputs / errors / properties the integration relies on. audit D10 uses this to verify the integration keeps using the core SDK correctly as the SDK evolves.

6.1 Configuration Settings — Canonical Source

config.md feature spec and src/{package}/config.{ext} MUST source APCORE_* setting names / types / defaults from shared/conventions.md → "Required settings" list. Do NOT invent new settings inside an integration. If the framework genuinely requires a new setting:

Name it with the prefix APCORE_{FRAMEWORK}_* (e.g., APCORE_FASTAPI_ROUTE_PREFIX), not bare APCORE_*
Document the rationale in docs/features/config.md under a ### Framework-specific settings section
File a PR against shared/conventions.md only if the setting is universally applicable

audit D7 flags any bare APCORE_* setting in an integration that is not in the canonical list.

Initialize git and create the skeleton commit automatically:

cd {target-path}
git init
git add .
git commit -m "chore: initialize {framework}-apcore project skeleton"

Display:

Git initialized with skeleton commit.

Step 7: Display Summary and Next Steps

apcore-skills:integration — Integration Bootstrap Complete

Target: {target-path}
Framework: {framework} ({lang})
Source files: {N} scaffolded
Test files: {N} scaffolded
Feature specs: {N} generated
Demo project: examples/demo/

Core Capabilities:
  [stub] Endpoint Scanner     — scanners/{scanner}.{ext}
  [stub] Module Registry      — registry.{ext}
  [stub] Context Mapping      — context.{ext}
  [stub] MCP Server           — cli.{ext} (serve command)
  [stub] OpenAI Export        — cli.{ext} (export command)

Configuration: {N} APCORE_* settings defined

Next steps:
  cd {target-path}
  /code-forge:plan @docs/features/scanner.md       Plan scanner implementation
  /code-forge:impl scanner                          Implement scanner
  /apcore-skills:sync                                Verify consistency with other integrations

Coordination with Other Skills

After integration: Use code-forge:plan per feature spec to plan implementation
During implementation: Use code-forge:impl to execute TDD tasks
After each feature: Use code-forge:review to review quality
Cross-integration consistency: Use apcore-skills:audit --scope integrations
For release: Use apcore-skills:release (integration versions are independent)