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ai-agent-development

ai-agent-development is a skill for Claude Code, Codex from manu14357/zskills. It costs 32 tokens per session (936 once invoked), scanned A, a copy of ai-agent-development, MIT.

A development workflow for building AI agents, systems with multiple cooperating agents, and the connections between agents and external tools. It covers frameworks such as CrewAI and LangGraph as well as custom implementations.

In plain words
What is it for?
Use it to plan autonomous agents, multi-agent systems, orchestration, tool integrations, memory, and human review steps.
Why use it?
Agent projects can become difficult to design when responsibilities, tools, memory, and success measures are not planned together. This workflow provides stages for designing, implementing, integrating, and testing them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 16repo 1mo ago A scan 32 tokens copy · 97% MIT

Good fit Use it to plan autonomous agents, multi-agent systems, orchestration, tool integrations, memory, and human review steps.

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Install with agentmods
npx agentmods add skills/manu14357/zskills/ai-agent-development
View source ↗ manu14357/zskills zskills.vercel.app
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add manu14357/zskills --skill ai-agent-development
Clone the repo
git clone --depth 1 https://github.com/manu14357/zskills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ai-agent-development

README.md
[![agentmods](https://agentmods.dev/badge/skills/manu14357/zskills/ai-agent-development/github.svg)](https://agentmods.dev/skills/manu14357/zskills/ai-agent-development)
Your own site
<a href="https://agentmods.dev/skills/manu14357/zskills/ai-agent-development"><img src="https://agentmods.dev/badge/skills/manu14357/zskills/ai-agent-development/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-agent-development

Your own site · 80×15
<a href="https://agentmods.dev/skills/manu14357/zskills/ai-agent-development"><img src="https://agentmods.dev/badge/skills/manu14357/zskills/ai-agent-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 936 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 97% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.00936
Opus 5 $0.00016 $0.00468
Sonnet 5 $0.00006 $0.00187
Haiku 4.5 $0.00003 $0.00094

Measured 10d ago against content hash c8dc69e14d3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ai-agent-development scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

97% identical to ai-agent-development — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/ai-agent-development/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Agent Development Workflow

Overview

Specialized workflow for building AI agents including single autonomous agents, multi-agent systems, agent orchestration, tool integration, and human-in-the-loop patterns.

When to Use This Workflow

Use this workflow when:

  • Building autonomous AI agents
  • Creating multi-agent systems
  • Implementing agent orchestration
  • Adding tool integration to agents
  • Setting up agent memory

Workflow Phases

Phase 1: Agent Design

Skills to Invoke
  • ai-agents-architect - Agent architecture
  • autonomous-agents - Autonomous patterns
Actions
  1. Define agent purpose
  2. Design agent capabilities
  3. Plan tool integration
  4. Design memory system
  5. Define success metrics
Copy-Paste Prompts
Use @ai-agents-architect to design AI agent architecture

Phase 2: Single Agent Implementation

Skills to Invoke
  • autonomous-agent-patterns - Agent patterns
  • autonomous-agents - Autonomous agents
Actions
  1. Choose agent framework
  2. Implement agent logic
  3. Add tool integration
  4. Configure memory
  5. Test agent behavior
Copy-Paste Prompts
Use @autonomous-agent-patterns to implement single agent

Phase 3: Multi-Agent System

Skills to Invoke
  • crewai - CrewAI framework
  • multi-agent-patterns - Multi-agent patterns
Actions
  1. Define agent roles
  2. Set up agent communication
  3. Configure orchestration
  4. Implement task delegation
  5. Test coordination
Copy-Paste Prompts
Use @crewai to build multi-agent system with roles

Phase 4: Agent Orchestration

Skills to Invoke
  • langgraph - LangGraph orchestration
  • workflow-orchestration-patterns - Orchestration
Actions
  1. Design workflow graph
  2. Implement state management
  3. Add conditional branches
  4. Configure persistence
  5. Test workflows
Copy-Paste Prompts
Use @langgraph to create stateful agent workflows

Phase 5: Tool Integration

Skills to Invoke
  • agent-tool-builder - Tool building
  • tool-design - Tool design

Read the full file on GitHub · 175 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 175 lines · 32 tokens per session scan A c8dc69e14d3b

Subscribe to this mod's changes

ai-agent-development is a skill published in the GitHub repository manu14357/zskills (16 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 936 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to ai-agent-development, differing in 4 lines, and is treated as a copy.

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