ai-agent-development

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Author repo skills-registry

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGrap…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Overview”, “When to Use This Workflow”, “Workflow Phases”, “Phase 1: Agent Design”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name ai-agent-development directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Overview / When to Use This Workflow / Workflow Phases” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

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

Define agent purpose
Design agent capabilities
Plan tool integration
Design memory system
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

Choose agent framework
Implement agent logic
Add tool integration
Configure memory
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

Define agent roles
Set up agent communication
Configure orchestration
Implement task delegation
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

Design workflow graph
Implement state management
Add conditional branches
Configure persistence
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

Actions

Identify tool needs
Design tool interfaces
Implement tools
Add error handling
Test tool usage

Copy-Paste Prompts

Use @agent-tool-builder to create agent tools

Phase 6: Memory Systems

Skills to Invoke

agent-memory-systems - Memory architecture
conversation-memory - Conversation memory

Actions

Design memory structure
Implement short-term memory
Set up long-term memory
Add entity memory
Test memory retrieval

Copy-Paste Prompts

Use @agent-memory-systems to implement agent memory

Phase 7: Evaluation

Skills to Invoke

agent-evaluation - Agent evaluation
evaluation - AI evaluation

Actions

Define evaluation criteria
Create test scenarios
Measure agent performance
Test edge cases
Iterate improvements

Copy-Paste Prompts

Use @agent-evaluation to evaluate agent performance

Agent Architecture

User Input -> Planner -> Agent -> Tools -> Memory -> Response
              |          |        |        |
         Decompose   LLM Core  Actions  Short/Long-term

Quality Gates

Agent logic working
Tools integrated
Memory functional
Orchestration tested
Evaluation passing

ai-ml - AI/ML development
rag-implementation - RAG systems
workflow-automation - Workflow patterns

Source: Andruia/antigravity-awesome-skills — distributed by TomeVault.

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: AI
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @tomevault-io · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Plug-and-play
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Unspecified
Detected file/system behavior: Read-only
Write / modify
Detected network behavior: Local-only
Install commands: None (reference only)

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview ai-agent-development.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

# 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

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> Overview → When to Use This Workflow → Workflow Phases → Phase 1: Agent Design → Phase 2: Single Agent Implementation → Phase 3: Multi-Agent System
terms    -> no emphasized key terms
files/cmd -> ai-agents-architect · autonomous-agents · autonomous-agent-patterns · crewai · multi-agent-patterns · langgraph · workflow-orchestration-patterns · agent-tool-builder
body sha256 -> 31972fc4f69e

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

AI Agent Development Workflow

Overview

When to Use This Workflow

Workflow Phases

Phase 1: Agent Design

Skills to Invoke

Actions

Copy-Paste Prompts

Phase 2: Single Agent Implementation

Skills to Invoke

Actions

Copy-Paste Prompts

Phase 3: Multi-Agent System

Skills to Invoke

Actions

Copy-Paste Prompts

Phase 4: Agent Orchestration

Skills to Invoke

Actions

Copy-Paste Prompts

Phase 5: Tool Integration

Skills to Invoke

Actions

Copy-Paste Prompts

Phase 6: Memory Systems

Skills to Invoke

Actions

Copy-Paste Prompts

Phase 7: Evaluation

Skills to Invoke

Actions

Copy-Paste Prompts

Agent Architecture

Quality Gates

Related Workflow Bundles

Discussion