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Production Agent Example

This example demonstrates a full production-style agent with identity, model configuration, tools, resources, prompts, permissions, security, runtime settings, and metadata.

Complete Reference

This example uses all major ADL features. Use it as a reference when building production agents.

Document​

research-assistant.adl.yaml
$schema: https://adl-spec.org/0.2/schema.json
adl_spec: "0.2.0"
name: Research Assistant
description: An AI assistant that helps researchers find, summarize, and analyze academic papers.
version: "2.1.0"
id: urn:adl:acme:research-assistant:2.1.0

data_classification:
  sensitivity: internal
  categories:
    - intellectual_property

lifecycle:
  status: active
  effective_date: "2026-01-15T00:00:00Z"

provider:
  name: Acme AI
  url: https://acme.ai
  contact: support@acme.ai

cryptographic_identity:
  did: did:web:acme.ai:agents:research-assistant
  public_key:
    algorithm: Ed25519
    value: base64-encoded-public-key

model:
  provider: anthropic
  name: claude-sonnet-4-20250514
  context_window: 200000
  temperature: 0.5
  capabilities:
    - function_calling

system_prompt: >-
  You are a research assistant that helps users find and analyze academic papers.
  Be thorough, accurate, and cite your sources.

tools:
  - name: search_papers
    description: Search for academic papers
    parameters:
      type: object
      properties:
        query:
          type: string
        limit:
          type: integer
          default: 10
      required:
        - query
    read_only: true

  - name: get_paper
    description: Get full paper details
    parameters:
      type: object
      properties:
        paper_id:
          type: string
      required:
        - paper_id
    read_only: true

  - name: save_note
    description: Save a research note
    parameters:
      type: object
      properties:
        title:
          type: string
        content:
          type: string
      required:
        - title
        - content

resources:
  - name: paper_index
    type: vector_store
    description: Vector index of paper embeddings
    uri: s3://research-data/papers/

prompts:
  - name: summarize
    description: Summarize a paper
    template: |
      Summarize the following paper:

      {{content}}

permissions:
  network:
    allowed_hosts:
      - api.semanticscholar.org
      - arxiv.org
    allowed_protocols:
      - https
    deny_private: true
  filesystem:
    allowed_paths:
      - path: /data/papers/**
        access: read
      - path: /data/notes/**
        access: read_write
  resource_limits:
    max_memory_mb: 2048
    max_duration_sec: 300

security:
  authentication:
    type: oauth2
    required: true
    scopes:
      - read:papers
      - write:notes
  encryption:
    in_transit:
      required: true
      min_version: "1.2"
  attestation:
    type: self
    issued_at: "2026-02-01T00:00:00Z"
    expires_at: "2027-02-01T00:00:00Z"

runtime:
  tool_invocation:
    parallel: true
    max_concurrent: 3
    timeout_ms: 30000
  error_handling:
    on_tool_error: retry
    max_retries: 2

metadata:
  authors:
    - name: Research Team
      email: research@acme.ai
  license: Apache-2.0
  documentation: https://docs.acme.ai/research-assistant
  repository: https://github.com/acme/research-assistant
  tags:
    - research
    - academic
    - papers
    - summarization

Sections Breakdown​

Identity​

The agent has a unique identifier and provider information:

id: urn:adl:acme:research-assistant:2.1.0
provider:
  name: Acme AI
  url: https://acme.ai
  contact: support@acme.ai

Cryptographic Identity​

For secure agent identification:

cryptographic_identity:
  did: did:web:acme.ai:agents:research-assistant
  public_key:
    algorithm: Ed25519
    value: base64-encoded-public-key

Permissions (Deny-by-Default)​

Security Model

Network and filesystem access is explicitly defined. Any access not explicitly granted is denied.

permissions:
  network:
    allowed_hosts:
      - api.semanticscholar.org
      - arxiv.org
    allowed_protocols:
      - https
    deny_private: true

Security​

Authentication and encryption requirements:

security:
  authentication:
    type: oauth2
    required: true
    scopes:
      - read:papers
      - write:notes

Runtime Configuration​

How the agent should execute:

runtime:
  tool_invocation:
    parallel: true
    max_concurrent: 3
    timeout_ms: 30000

Notes​

Production Checklist
  • Use $schema to enable IDE validation and autocomplete
  • Define explicit permissions (deny-by-default)
  • Configure security requirements (authentication, encryption)
  • Set attestation with appropriate expiration dates
  • Include comprehensive metadata for discovery