manifest-structure

name	manifest-structure
description	Canonical system manifest format with all enumerated types for project, frontend, service, database, integration, LLM, agent, and communication components. Use when structuring architecture output.

System Manifest Structure

The System Manifest is the canonical structured representation of a product's architecture. Every deliverable (diagrams, cost estimates, complexity scores, specs) derives from this manifest. When building a manifest, use the types and structure defined below.

---

Manifest Top-Level Structure

project:
  name: string
  type: app | agent | hybrid
  description: string (one sentence)

users:
  - role: string
    description: string
    count_estimate: string (range, e.g. "100-1,000 MAU")

frontends:
  - name: string
    type: <frontend_type>
    framework: string
    pages: [string]
    build_tool: string (optional, e.g. "Vite", "Webpack", "Expo")
    rendering: ssr | ssg | spa (optional, web only)
    state_management: string (optional, e.g. "Zustand", "Redux")
    data_fetching: string (optional, e.g. "React Query", "SWR")
    component_library: string (optional, e.g. "Radix UI", "React Native Paper")
    form_handling: string (optional, e.g. "React Hook Form")
    validation: string (optional, e.g. "Zod", "Yup")
    api_client: string (optional, e.g. "Axios", "fetch")
    styling: string (optional, e.g. "Tailwind CSS")
    routing: string (optional, e.g. "React Router", "Expo Router")
    animation: string (optional, e.g. "Framer Motion")
    deploy_target: string (optional, e.g. "Vercel", "Cloudflare Pages")
    dev_port: integer (optional, e.g. 3000)
    backend_connections: (optional)
      - service: string (references a defined service)
        purpose: string
    client_auth: (optional)
      token_storage: string (e.g. "cookie", "async-storage", "keychain")
      csrf_protection: boolean
      token_refresh: boolean
      device_binding: boolean (mobile only)
    realtime: (optional)
      protocol: websocket | socket-io | sse | polling | webrtc
      provider: string (optional, e.g. "Cloudflare RTK", "Dyte")
    monitoring: (optional)
      error_tracking: string (e.g. "Sentry", "Crashlytics")
      analytics: string (e.g. "PostHog", "Mixpanel")
    mobile_config: (optional, for ios/android types)
      bundle_id: string (e.g. "com.example.myapp")
      build_platform: string (e.g. "Expo Managed")
      navigation: string (e.g. "Expo Router", "React Navigation")
      push_providers: [string] (e.g. ["FCM", "APNS"])
      deep_link_scheme: string (e.g. "myapp")
      associated_domains: [string]
      permissions: [string] (e.g. ["camera", "microphone"])
      ota_updates: string (e.g. "Expo Updates")

services:
  - name: string
    type: <service_type>
    framework: string
    responsibilities: [string]
    endpoints: [string] (key endpoints only)

databases:
  - name: string
    type: <database_type>
    purpose: string (primary | cache | search | analytics | vector-store)
    key_collections: [string]

integrations:
  - name: string
    category: <integration_category>
    service: string (specific provider)
    purpose: string
    credentials: [string]

agents: (only for agent or hybrid projects)
  - name: string
    purpose: string
    llm_provider: <llm_provider>
    model: string
    orchestration: <agent_orchestration>
    interface: <agent_interface>
    tools:
      - name: string
        type: <agent_tool_type>
        description: string
    memory: session | persistent | vector-store
    guardrails: [string]

shared:
  types:
    - name: string
      description: string
      used_by: [string] (component names that share this type)
      fields: [string] (key fields or shape)
  libraries:
    - name: string
      purpose: string
      used_by: [string]
  contracts:
    - name: string
      type: api-schema | event-schema | proto-definition
      description: string
      between: [string] (component names)

application_patterns:
  architecture: <architecture_pattern>
  principles: [string] (e.g. "dependency inversion", "single responsibility")
  folder_convention: <folder_convention>
  error_handling: string (strategy description)
  testing_strategy: string (e.g. "unit + integration", "contract tests between services")

communication:
  - from: string (component name)
    to: string (component name)
    pattern: <communication_pattern>
    protocol: string (e.g. "HTTPS", "AMQP", "gRPC/Protobuf")
    auth: string (e.g. "JWT bearer", "API key", "mTLS", "none (internal)")
    data_format: string (e.g. "JSON", "Protobuf", "Avro")
    retry_strategy: string (optional, e.g. "exponential backoff, 3 retries")
    notes: string (optional, context for this connection)

artifacts:
  - name: string
    type: openapi | postman-collection | asyncapi | graphql-schema
    service: string (which service this artifact documents)
    format: yaml | json | graphql

security:
  auth_strategy: string (e.g. "JWT with refresh tokens via Clerk")
  api_security:
    - name: string (e.g. "rate limiting", "input validation", "CORS")
      implementation: string
      applies_to: [string] (component names)
  data_protection:
    encryption_at_rest: string (e.g. "AES-256 via database provider")
    encryption_in_transit: string (e.g. "TLS 1.3 on all endpoints")
    pii_fields: [string] (fields that contain personally identifiable information)
    data_retention: string (policy)
  secrets_management: string (e.g. "environment variables via Doppler / Vercel env")
  compliance: [string] (e.g. ["GDPR", "SOC2", "HIPAA"] — only if applicable)
  owasp_considerations:
    - threat: string (e.g. "SQL injection", "XSS", "CSRF")
      mitigation: string

observability:
  logging:
    strategy: string (e.g. "structured JSON logs")
    provider: string (e.g. "Axiom", "Datadog", "CloudWatch")
    log_levels: [string] (e.g. ["error", "warn", "info", "debug"])
  tracing:
    enabled: boolean
    provider: string (e.g. "OpenTelemetry → Jaeger" or "Datadog APM")
    instrumented_services: [string]
  metrics:
    provider: string (e.g. "Prometheus + Grafana", "Datadog")
    key_metrics: [string] (e.g. ["request latency p99", "error rate", "queue depth"])
  alerting:
    provider: string (e.g. "PagerDuty", "Opsgenie", "Slack webhooks")
    critical_alerts: [string] (e.g. ["error rate > 5%", "latency p99 > 2s", "queue backlog > 1000"])
  health_checks:
    - component: string
      endpoint: string (e.g. "/health")
      checks: [string] (e.g. ["database connectivity", "redis connectivity", "external API reachability"])

devops:
  cicd:
    provider: string (e.g. "GitHub Actions", "GitLab CI", "CircleCI")
    branch_strategy: <branch_strategy>
    pipeline_stages: [string] (e.g. ["lint", "test", "build", "deploy"])
    environments:
      - name: string (e.g. "development", "staging", "production")
        branch: string (e.g. "develop", "staging", "main")
        auto_deploy: boolean
        url_pattern: string (e.g. "{{service}}-dev.{{domain}}")
  database_migrations:
    tool: string (e.g. "Prisma Migrate", "Alembic", "Knex", "TypeORM")
    strategy: string (e.g. "versioned migrations with rollback scripts")
    seed_data: string (e.g. "dev seeds with faker data, staging seeds from anonymized prod")
    rollback_plan: string
  environment_config:
    strategy: <config_strategy>
    feature_flags: string (optional, e.g. "LaunchDarkly", "Unleash", "environment variables")
    config_validation: string (e.g. "Zod schema validation on startup")

deployment:
  - component: string
    target: string (e.g. "Vercel", "AWS ECS", "Railway")

---

Enumerated Types

Project Type

Value	When to Use
app	Traditional application — web, mobile, desktop, CLI. No AI agents.
agent	AI agent system — no traditional application UI beyond the agent interface.
hybrid	Application with embedded AI agents. Most common for modern products.

Frontend Type

Value	Description
web	Browser-based (React, Next.js, Vue, Svelte, etc.)
ios	Native iOS (Swift/SwiftUI) or cross-platform targeting iOS
android	Native Android (Kotlin) or cross-platform targeting Android
desktop	Desktop app (Electron, Tauri, native)
cli	Command-line interface
crm	CRM / back-office management interface
booking	Booking / scheduling application
ai-chat	AI chat / conversational interface

Frontend Rendering (Web Only)

Value	When to Use
ssr	Server-side rendering. Best for SEO, dynamic content.
ssg	Static site generation. Best for content-heavy, infrequently changing pages.
spa	Single-page application. Best for app-like UX, no SEO needs.

Client-Side Token Storage

Value	Platform	Description
cookie	Web	HTTP-only cookies. Most secure for web.
localStorage	Web	Browser localStorage. Persistent but XSS-vulnerable.
sessionStorage	Web	Browser sessionStorage. Cleared on tab close.
memory	Web	In-memory only. Most secure but lost on refresh.
async-storage	Mobile (RN)	React Native AsyncStorage. Unencrypted.
secure-store	Mobile (RN)	Expo SecureStore. Uses Keychain/Keystore.
keychain	Mobile (iOS)	iOS Keychain. Survives reinstalls.
encrypted-shared-prefs	Mobile (Android)	Android EncryptedSharedPreferences.

Real-Time Protocol

Value	When to Use
websocket	Raw WebSocket for bidirectional communication
socket-io	Socket.IO with auto-reconnect, rooms, namespaces
sse	Server-Sent Events for one-way streaming (AI responses, live feeds)
polling	HTTP polling when WebSocket not available
webrtc	Peer-to-peer audio/video communication

Mobile Permissions

Value	Description
camera	Camera access for photos/video
microphone	Microphone access for audio/calls
contacts	Address book access
location	GPS / location services
notifications	Push notification permission
photos	Photo library access
calendar	Calendar access
bluetooth	Bluetooth device communication
background-audio	Background audio playback/recording

Service Type

Value	Description
rest-api	RESTful HTTP API
graphql	GraphQL API
websocket	Real-time bidirectional communication
worker	Background job processor
cron	Scheduled task runner
gateway	API gateway or reverse proxy

Database Type

Value	Typical Use Case
postgresql	Relational data, complex queries, transactions
mongodb	Document storage, flexible schemas
redis	Caching, sessions, rate limiting, pub/sub
dynamodb	Key-value at scale, serverless workloads
elasticsearch	Full-text search, log analytics
mysql	Relational data, legacy systems
sqlite	Local/embedded, development, mobile
firestore	Real-time sync, mobile-first, serverless

Integration Category

Value	Examples
payments	Stripe, PayPal, Paddle, LemonSqueezy
email	SendGrid, Resend, AWS SES, Postmark
sms	Twilio, MessageBird, Vonage
maps	Google Maps, Mapbox, HERE
auth	Auth0, Clerk, Firebase Auth, Supabase Auth
storage	AWS S3, Cloudflare R2, Google Cloud Storage
analytics	PostHog, Mixpanel, Amplitude, Google Analytics
monitoring	Sentry, Datadog, Grafana, New Relic
cdn	Cloudflare, CloudFront, Fastly
search	Algolia, Typesense, Meilisearch
messaging	Slack API, Discord API, Telegram Bot API
notifications	OneSignal, Firebase Cloud Messaging, Novu
ci-cd	GitHub Actions, GitLab CI, CircleCI

LLM Provider

Value	Models
anthropic	Claude Haiku, Sonnet, Opus
openai	GPT-4o, GPT-4o-mini, o1, o3
google	Gemini Flash, Gemini Pro
mistral	Mistral Large, Mistral Small, Codestral
groq	LLaMA, Mixtral (fast inference)
local	Ollama, llama.cpp, vLLM
multi	Multiple providers with fallback/routing

Agent Orchestration

Value	When to Use
single-turn	Simple request-response, no reasoning chain needed
react	Tool-using agent that reasons then acts in a loop
chain-of-thought	Multi-step reasoning without tool use
multi-agent-router	Router dispatches to specialist agents sequentially
multi-agent-parallel	Multiple agents work simultaneously, results merged
plan-and-execute	Planner creates steps, executor runs them
custom	Novel orchestration pattern — describe in detail

Agent Tool Type

Value	Description
api-call	Calls an external HTTP API
database-query	Reads from or writes to a database
web-search	Searches the web for information
code-execution	Runs code in a sandbox
file-io	Reads or writes files
browser	Navigates web pages, scrapes content
human-handoff	Escalates to a human operator
agent-delegate	Delegates to another agent
custom	Custom tool — describe in detail

Agent Interface

Value	Description
chat-ui	Web-based chat interface
api	Programmatic API (no UI)
slack-bot	Slack workspace bot
discord-bot	Discord server bot
cli	Command-line interface
email	Email-based interaction
voice	Voice interface (phone, smart speaker)

Architecture Pattern

Value	When to Use
clean-architecture	Layered with strict dependency inversion (domain → use cases → adapters → frameworks). Best for complex business logic.
hexagonal	Ports and adapters. Similar to clean architecture but emphasizes interchangeable external integrations.
mvc	Model-View-Controller. Simple apps, server-rendered pages, CRUD-heavy products.
mvvm	Model-View-ViewModel. Mobile apps, reactive UIs with data binding.
modular-monolith	Monolith organized into self-contained modules with clear boundaries. Good starting point before microservices.
microservices	Independent deployable services with own databases. Only when team/scale justifies the overhead.
serverless	Functions as compute units (Lambda, Cloud Functions). Event-driven, low-traffic, or bursty workloads.
event-driven	Components communicate through events/messages. Decoupled, async-first.
cqrs	Command Query Responsibility Segregation. Separate read/write models. Complex domains with different read/write patterns.
layered	Simple horizontal layers (presentation → business → data). Straightforward CRUD apps.

Folder Convention

Value	Structure	Best For
feature-based	src/features/auth/, src/features/orders/, src/features/payments/	Most apps. Groups related code (routes, services, models) by feature.
layer-based	src/controllers/, src/services/, src/models/, src/repositories/	Simple CRUD apps. Groups by technical layer.
domain-driven	src/domain/, src/application/, src/infrastructure/, src/presentation/	Clean/hexagonal architecture. Enforces dependency direction.
module-based	src/modules/auth/, src/modules/billing/ with internal layers per module	Modular monoliths. Each module is self-contained.
flat	src/ with files grouped loosely	Small services, workers, single-purpose microservices.

Shared Contract Type

Value	Description
api-schema	OpenAPI / JSON Schema defining REST API contracts between services
event-schema	Event payload schema (e.g. CloudEvents, AsyncAPI) for message queues / event bus
proto-definition	Protocol Buffer definition for gRPC services
graphql-schema	Shared GraphQL type definitions
typescript-types	Shared TypeScript type/interface package
json-schema	Generic JSON Schema used for validation across services

Branch Strategy

Value	When to Use
github-flow	Single main branch + feature branches. Simple. Best for most startups and small teams.
gitflow	develop + main + feature/release/hotfix branches. Best for products with scheduled releases.
trunk-based	Everyone commits to main with short-lived feature branches (<1 day). Best for CI/CD-mature teams.
release-branching	Main + release branches (release/1.0, release/1.1). Best for products with multiple supported versions.

Config Strategy

Value	Description
env-vars	Environment variables (.env files locally, platform env vars in production). Simplest approach.
config-service	Centralized config management (Doppler, AWS Parameter Store, HashiCorp Vault). Best for multi-service architectures.
file-based	Config files per environment (config.dev.json, config.prod.json). Best for simple apps.
hybrid	Secrets in a config service, non-sensitive config in env vars or files. Best balance of security and simplicity.

Communication Pattern

Value	When to Use
rest	Standard request-response between services
graphql	Flexible queries from frontend to backend
websocket	Real-time bidirectional (chat, live updates)
grpc	High-performance service-to-service
message-queue	Async processing (SQS, RabbitMQ, BullMQ)
event-bus	Event-driven decoupled services (EventBridge, Kafka)
sse	Server-to-client streaming (AI responses, live feeds)

---

Example Manifest Snippet

project:
  name: "SupportBot Pro"
  type: hybrid
  description: "AI-powered customer support platform with human escalation"

users:
  - role: customer
    description: "End users seeking support"
    count_estimate: "1,000-10,000 MAU"
  - role: support-agent
    description: "Human support staff handling escalations"
    count_estimate: "5-20"
  - role: admin
    description: "Manages knowledge base, views analytics"
    count_estimate: "1-3"

frontends:
  - name: customer-widget
    type: web
    framework: React
    pages: [chat-widget, ticket-history]
    build_tool: Vite
    rendering: spa
    state_management: Zustand
    data_fetching: React Query
    api_client: fetch
    styling: Tailwind CSS
    deploy_target: Vercel
    dev_port: 3001
    backend_connections:
      - { service: api-server, purpose: "Ticket CRUD and history" }
      - { service: agent-service, purpose: "Real-time AI chat" }
    client_auth:
      token_storage: cookie
      csrf_protection: true
      token_refresh: true
    realtime:
      protocol: websocket
    monitoring:
      error_tracking: Sentry
  - name: agent-dashboard
    type: web
    framework: Next.js
    pages: [inbox, conversation-view, knowledge-base, analytics]
    build_tool: Webpack
    rendering: ssr
    state_management: Zustand
    data_fetching: React Query
    component_library: Radix UI
    form_handling: React Hook Form
    validation: Zod
    styling: Tailwind CSS
    routing: Next.js App Router
    deploy_target: Vercel
    dev_port: 3000
    backend_connections:
      - { service: api-server, purpose: "All admin and agent operations" }
    client_auth:
      token_storage: cookie
      token_refresh: true
    monitoring:
      error_tracking: Sentry
      analytics: PostHog

services:
  - name: api-server
    type: rest-api
    framework: Node.js/Express
    responsibilities: [auth, ticket-management, knowledge-base-crud]
  - name: agent-service
    type: websocket
    framework: Node.js
    responsibilities: [ai-agent-orchestration, streaming-responses]

databases:
  - name: primary-db
    type: postgresql
    purpose: primary
    key_collections: [users, tickets, conversations, knowledge_articles]
  - name: vector-db
    type: postgresql
    purpose: vector-store
    key_collections: [knowledge_embeddings]
  - name: cache
    type: redis
    purpose: cache
    key_collections: [sessions, rate_limits]

agents:
  - name: support-agent
    purpose: "Answer customer questions using knowledge base, escalate complex issues"
    llm_provider: anthropic
    model: claude-sonnet
    orchestration: react
    interface: chat-ui
    tools:
      - name: search-knowledge-base
        type: database-query
        description: "Vector search over knowledge articles"
      - name: create-ticket
        type: api-call
        description: "Create support ticket for human follow-up"
      - name: human-handoff
        type: human-handoff
        description: "Transfer conversation to human agent"
    memory: persistent
    guardrails:
      - "Never make promises about refunds or policy changes"
      - "Always disclose that you are an AI when asked"
      - "Escalate to human if confidence is low or customer is upset"

shared:
  types:
    - name: User
      description: "Core user type shared across API and dashboard"
      used_by: [api-server, agent-dashboard]
      fields: [id, email, role, displayName, createdAt]
    - name: Ticket
      description: "Support ticket shared between API, agent, and dashboard"
      used_by: [api-server, agent-service, agent-dashboard]
      fields: [id, customerId, subject, status, priority, messages[], assignedTo]
    - name: KnowledgeArticle
      description: "Knowledge base article used by API and AI agent"
      used_by: [api-server, support-agent]
      fields: [id, title, content, embedding, category, updatedAt]
  libraries:
    - name: shared-types
      purpose: "TypeScript type definitions shared across all Node.js services"
      used_by: [api-server, agent-service, agent-dashboard, customer-widget]
    - name: shared-validators
      purpose: "Zod schemas for request/response validation"
      used_by: [api-server, agent-service]
  contracts:
    - name: ticket-events
      type: event-schema
      description: "Event payloads for ticket lifecycle (created, assigned, resolved, escalated)"
      between: [api-server, agent-service]
    - name: api-contract
      type: api-schema
      description: "OpenAPI spec for the REST API consumed by frontends"
      between: [api-server, customer-widget, agent-dashboard]

application_patterns:
  architecture: clean-architecture
  principles:
    - "Dependency inversion — domain layer has zero external dependencies"
    - "Single responsibility — each service owns one bounded context"
    - "Interface segregation — clients depend only on the methods they use"
    - "Fail fast — validate at boundaries, trust internal data"
  folder_convention: feature-based
  error_handling: "Structured error codes with user-friendly messages. Services return {code, message, details}. Frontend maps codes to UI text."
  testing_strategy: "Unit tests for business logic, integration tests for API endpoints, contract tests between api-server and agent-service"

communication:
  - from: customer-widget
    to: api-server
    pattern: rest
    protocol: HTTPS
    auth: JWT bearer
    data_format: JSON
  - from: customer-widget
    to: agent-service
    pattern: websocket
    protocol: WSS
    auth: JWT bearer
    data_format: JSON
  - from: agent-dashboard
    to: api-server
    pattern: rest
    protocol: HTTPS
    auth: JWT bearer
    data_format: JSON
  - from: agent-service
    to: api-server
    pattern: rest
    protocol: HTTP (internal)
    auth: API key
    data_format: JSON
    notes: "Internal service-to-service call for ticket operations"
  - from: api-server
    to: agent-service
    pattern: message-queue
    protocol: Redis/BullMQ
    auth: none (internal)
    data_format: JSON
    retry_strategy: "exponential backoff, 3 retries"
    notes: "Async ticket assignment and AI processing"

security:
  auth_strategy: "JWT with refresh tokens via Clerk"
  api_security:
    - name: rate-limiting
      implementation: "Upstash Ratelimit — 100 requests/min per user"
      applies_to: [api-server]
    - name: input-validation
      implementation: "Zod schemas on all request bodies"
      applies_to: [api-server, agent-service]
    - name: cors
      implementation: "Whitelist customer-widget and agent-dashboard origins only"
      applies_to: [api-server]
    - name: helmet-headers
      implementation: "helmet middleware for CSP, HSTS, X-Frame-Options"
      applies_to: [api-server]
  data_protection:
    encryption_at_rest: "AES-256 via Supabase (PostgreSQL) default encryption"
    encryption_in_transit: "TLS 1.3 on all external endpoints"
    pii_fields: [email, displayName, phone]
    data_retention: "User data retained while account active, deleted 30 days after account deletion"
  secrets_management: "Vercel environment variables for production, .env files for local development"
  owasp_considerations:
    - threat: "Broken access control"
      mitigation: "Role-based middleware on every route. Support agents can't access admin endpoints."
    - threat: "Injection"
      mitigation: "Prisma parameterized queries. Zod validation on all inputs."
    - threat: "SSRF"
      mitigation: "Agent tool URLs whitelisted. No user-provided URLs fetched server-side."

observability:
  logging:
    strategy: "Structured JSON logs via pino"
    provider: "Axiom (free tier)"
    log_levels: [error, warn, info, debug]
  tracing:
    enabled: false
    provider: "Not needed at MVP stage"
    instrumented_services: []
  metrics:
    provider: "Vercel Analytics + Sentry performance"
    key_metrics: ["request latency p99", "error rate", "queue depth", "AI response time"]
  alerting:
    provider: "Sentry + Slack webhook"
    critical_alerts: ["error rate > 5%", "api-server down", "agent-service queue backlog > 500"]
  health_checks:
    - component: api-server
      endpoint: "/health"
      checks: ["PostgreSQL connectivity", "Redis connectivity"]
    - component: agent-service
      endpoint: "/health"
      checks: ["Redis connectivity", "Anthropic API reachability"]

devops:
  cicd:
    provider: "GitHub Actions"
    branch_strategy: github-flow
    pipeline_stages: [lint, test, build, deploy]
    environments:
      - name: staging
        branch: develop
        auto_deploy: true
        url_pattern: "{{service}}-staging.vercel.app"
      - name: production
        branch: main
        auto_deploy: true
        url_pattern: "{{service}}.vercel.app"
  database_migrations:
    tool: "Prisma Migrate"
    strategy: "Versioned migrations committed to git. Run automatically in CI before deploy."
    seed_data: "Dev seeds with faker.js for local development"
    rollback_plan: "Prisma migrate rollback for failed migrations. Manual SQL for data fixes."
  environment_config:
    strategy: env-vars
    feature_flags: "Environment variables (ENABLE_AI_AGENT=true/false) for MVP"
    config_validation: "Zod schema validates all env vars on service startup"