agent-systems-handbook

Source#

• Repository: Prompthon-IO/agent-systems-handbook
• Last source update: 2026-05-10
• Last verified: 2026-05-10

Tags#

Integration notes#

Repository is focused on tool/server interoperability; wrap in bounded worker contracts for production use.

worker.md example#

Starter worker.md contract mapped from this registry entry. Copy this file and adapt schemas, constraints, and statuses for your task.

---
id: agent-systems-handbook-repo-derived-worker
name: agent-systems-handbook Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/agent-systems-handbook/
source_repository: https://github.com/Prompthon-IO/agent-systems-handbook
repository_default_branch: main
repository_language: MDX
repository_license: NOASSERTION
repository_updated_at: 2026-05-10
worker_mode: tool-gateway-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.9
derived_on: 2026-05-10
tags:
  - a2a
  - agent-framework
  - agent-memory
  - agentic-ai
  - agentic-workflow
  - ai-agent
---

# agent-systems-handbook Repo-Derived Worker

## Repo-derived summary
- Registry summary: A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current tre...
- Repository description: A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: multimodal file search, emerging agent runtimes, and production AI workflow patterns.
- Stars (snapshot): 179
- Primary language: MDX
- Worker mode classification: tool-gateway-worker

## Extracted from
- https://github.com/Prompthon-IO/agent-systems-handbook
- https://github.com/Prompthon-IO/agent-systems-handbook/blob/main/README.md

## Evidence notes (from repository text)
- README summary paragraph: AI-agent demos are easy to find. Production-ready agent systems are harder to understand. This handbook maps the workflows, tools, memory systems, context engineering, MCP/A2A interoperability, evaluation, observability, and multi-agent architecture behind real-world AI agents.
- Use it to understand, design, build, and operate production-minded AI agents — from first principles to framework choices and implementation patterns.
- Prompthon Agentic Labs publishes the Agent Systems Handbook by Prompthon: an AI-native field guide for students, practitioners, and builders exploring modern agent systems from different angles.
- The content is created through an AI-native workflow that combines AI-assisted drafting, synthesis, iteration, and refinement with expert guidance and review.
- - AI agent foundations and agent-system mental models
- - Agentic workflows, planning, reflection, tool use, and function calling

## Installation hints found in README
- No explicit package installation command detected in README text.

## worker.md contract (derived starter)
Purpose: Expose repository-supported tool/server capabilities behind a bounded worker interface.

### Input schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "request_id",
    "operation",
    "payload"
  ],
  "properties": {
    "request_id": {
      "type": "string"
    },
    "operation": {
      "type": "string"
    },
    "payload": {
      "type": "object"
    }
  }
}
```

### Output schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "request_id",
    "status",
    "result"
  ],
  "properties": {
    "request_id": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": [
        "ok",
        "retryable_error",
        "invalid_request",
        "invalid_output"
      ]
    },
    "result": {
      "type": "object"
    }
  }
}
```

### Constraints
- timeout_seconds: 30
- max_attempts: 2
- idempotency_key: request_id
- status_enum: [ok, retryable_error, invalid_request, invalid_output]
- notes: adapt to concrete APIs/classes documented in this repository before production use

## How this should be used
1. Treat this file as a repo-derived starter profile, not a claim of an official repository API contract.
2. Replace schemas with exact interfaces from code/docs you adopt.
3. Keep execution bounded and auditable using worker protocol constraints.

How to use#

• Save this as a worker spec file (for example: agent-systems-handbook-my-task.worker.md).
• Replace the input/output schemas and purpose with your real bounded task.
• Enforce schema validation + timeout + retry policy in your runtime before production use.

Citation#

Reference URL: https://worker.md/registry/agent-systems-handbook/

Source URL: https://github.com/Prompthon-IO/agent-systems-handbook