ai-agent-development

Name: ai-agent-development
Author: sickn33

44kstars6.5kforks

How to install ai-agent-development?

sickn33/agentic-awesome-skills/ai-agent-development

$npx -y skills add sickn33/agentic-awesome-skills --skill ai-agent-development

Installs into the current project.

Summary

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

Files · 1

View on GitHub

SKILL.md

1	# AI Agent Development Workflow
2
3	## Overview
4
5	Specialized workflow for building AI agents including single autonomous agents, multi-agent systems, agent orchestration, tool integration, and human-in-the-loop patterns.
6
7	## When to Use This Workflow
8
9	Use this workflow when:
10	- Building autonomous AI agents
11	- Creating multi-agent systems
12	- Implementing agent orchestration
13	- Adding tool integration to agents
14	- Setting up agent memory
15
16	## Workflow Phases
17
18	### Phase 1: Agent Design
19
20	#### Skills to Invoke
21	- `ai-agents-architect` - Agent architecture
22	- `autonomous-agents` - Autonomous patterns
23
24	#### Actions
25	1. Define agent purpose
26	2. Design agent capabilities
27	3. Plan tool integration
28	4. Design memory system
29	5. Define success metrics
30
31	#### Copy-Paste Prompts
32	```
33	Use @ai-agents-architect to design AI agent architecture
34	```
35
36	### Phase 2: Single Agent Implementation
37
38	#### Skills to Invoke
39	- `autonomous-agent-patterns` - Agent patterns
40	- `autonomous-agents` - Autonomous agents
41
42	#### Actions
43	1. Choose agent framework
44	2. Implement agent logic
45	3. Add tool integration
46	4. Configure memory
47	5. Test agent behavior
48
49	#### Copy-Paste Prompts
50	```
51	Use @autonomous-agent-patterns to implement single agent
52	```
53
54	### Phase 3: Multi-Agent System
55
56	#### Skills to Invoke
57	- `crewai` - CrewAI framework
58	- `multi-agent-patterns` - Multi-agent patterns
59
60	#### Actions
61	1. Define agent roles
62	2. Set up agent communication
63	3. Configure orchestration
64	4. Implement task delegation
65	5. Test coordination
66
67	#### Copy-Paste Prompts
68	```
69	Use @crewai to build multi-agent system with roles
70	```
71
72	### Phase 4: Agent Orchestration
73
74	#### Skills to Invoke
75	- `langgraph` - LangGraph orchestration
76	- `workflow-orchestration-patterns` - Orchestration
77
78	#### Actions
79	1. Design workflow graph
80	2. Implement state management
81	3. Add conditional branches
82	4. Configure persistence
83	5. Test workflows
84
85	#### Copy-Paste Prompts
86	```
87	Use @langgraph to create stateful agent workflows
88	```
89
90	### Phase 5: Tool Integration
91
92	#### Skills to Invoke
93	- `agent-tool-builder` - Tool building
94	- `tool-design` - Tool design
95
96	#### Actions
97	1. Identify tool needs
98	2. Design tool interfaces
99	3. Implement tools
100	4. Add error handling
101	5. Test tool usage
102
103	#### Copy-Paste Prompts
104	```
105	Use @agent-tool-builder to create agent tools
106	```
107
108	### Phase 6: Memory Systems
109
110	#### Skills to Invoke
111	- `agent-memory-systems` - Memory architecture
112	- `conversation-memory` - Conversation memory
113
114	#### Actions
115	1. Design memory structure
116	2. Implement short-term memory
117	3. Set up long-term memory
118	4. Add entity memory
119	5. Test memory retrieval
120
121	#### Copy-Paste Prompts
122	```
123	Use @agent-memory-systems to implement agent memory
124	```
125
126	### Phase 7: Evaluation
127
128	#### Skills to Invoke
129	- `agent-evaluation` - Agent evaluation
130	- `evaluation` - AI evaluation
131
132	#### Actions
133	1. Define evaluation criteria
134	2. Create test scenarios
135	3. Measure agent performance
136	4. Test edge cases
137	5. Iterate improvements
138
139	#### Copy-Paste Prompts
140	```
141	Use @agent-evaluation to evaluate agent performance
142	```
143
144	## Agent Architecture
145
146	```
147	User Input -> Planner -> Agent -> Tools -> Memory -> Response
148	\| \| \| \|
149	Decompose LLM Core Actions Short/Long-term
150	```
151
152	## Quality Gates
153
154	- [ ] Agent logic working
155	- [ ] Tools integrated
156	- [ ] Memory functional
157	- [ ] Orchestration tested
158	- [ ] Evaluation passing
159
160	## Related Workflow Bundles
161
162	- `ai-ml` - AI/ML development
163	- `rag-implementation` - RAG systems
164	- `workflow-automation` - Workflow patterns
165
166	## Limitations
167	- Use this skill only when the task clearly matches the scope described above.
168	- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
169	- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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ai-agent-development

44kstars6.5kforks

View on GitHub

How to install ai-agent-development?

sickn33/agentic-awesome-skills/ai-agent-development

$npx -y skills add sickn33/agentic-awesome-skills --skill ai-agent-development

Installs into the current project.

Summary

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

Files · 1

View on GitHub

SKILL.md

1	# AI Agent Development Workflow
2
3	## Overview
4
5	Specialized workflow for building AI agents including single autonomous agents, multi-agent systems, agent orchestration, tool integration, and human-in-the-loop patterns.
6
7	## When to Use This Workflow
8
9	Use this workflow when:
10	- Building autonomous AI agents
11	- Creating multi-agent systems
12	- Implementing agent orchestration
13	- Adding tool integration to agents
14	- Setting up agent memory
15
16	## Workflow Phases
17
18	### Phase 1: Agent Design
19
20	#### Skills to Invoke
21	- `ai-agents-architect` - Agent architecture
22	- `autonomous-agents` - Autonomous patterns
23
24	#### Actions
25	1. Define agent purpose
26	2. Design agent capabilities
27	3. Plan tool integration
28	4. Design memory system
29	5. Define success metrics
30
31	#### Copy-Paste Prompts
32	```
33	Use @ai-agents-architect to design AI agent architecture
34	```
35
36	### Phase 2: Single Agent Implementation
37
38	#### Skills to Invoke
39	- `autonomous-agent-patterns` - Agent patterns
40	- `autonomous-agents` - Autonomous agents
41
42	#### Actions
43	1. Choose agent framework
44	2. Implement agent logic
45	3. Add tool integration
46	4. Configure memory
47	5. Test agent behavior
48
49	#### Copy-Paste Prompts
50	```
51	Use @autonomous-agent-patterns to implement single agent
52	```
53
54	### Phase 3: Multi-Agent System
55
56	#### Skills to Invoke
57	- `crewai` - CrewAI framework
58	- `multi-agent-patterns` - Multi-agent patterns
59
60	#### Actions
61	1. Define agent roles
62	2. Set up agent communication
63	3. Configure orchestration
64	4. Implement task delegation
65	5. Test coordination
66
67	#### Copy-Paste Prompts
68	```
69	Use @crewai to build multi-agent system with roles
70	```
71
72	### Phase 4: Agent Orchestration
73
74	#### Skills to Invoke
75	- `langgraph` - LangGraph orchestration
76	- `workflow-orchestration-patterns` - Orchestration
77
78	#### Actions
79	1. Design workflow graph
80	2. Implement state management
81	3. Add conditional branches
82	4. Configure persistence
83	5. Test workflows
84
85	#### Copy-Paste Prompts
86	```
87	Use @langgraph to create stateful agent workflows
88	```
89
90	### Phase 5: Tool Integration
91
92	#### Skills to Invoke
93	- `agent-tool-builder` - Tool building
94	- `tool-design` - Tool design
95
96	#### Actions
97	1. Identify tool needs
98	2. Design tool interfaces
99	3. Implement tools
100	4. Add error handling
101	5. Test tool usage
102
103	#### Copy-Paste Prompts
104	```
105	Use @agent-tool-builder to create agent tools
106	```
107
108	### Phase 6: Memory Systems
109
110	#### Skills to Invoke
111	- `agent-memory-systems` - Memory architecture
112	- `conversation-memory` - Conversation memory
113
114	#### Actions
115	1. Design memory structure
116	2. Implement short-term memory
117	3. Set up long-term memory
118	4. Add entity memory
119	5. Test memory retrieval
120
121	#### Copy-Paste Prompts
122	```
123	Use @agent-memory-systems to implement agent memory
124	```
125
126	### Phase 7: Evaluation
127
128	#### Skills to Invoke
129	- `agent-evaluation` - Agent evaluation
130	- `evaluation` - AI evaluation
131
132	#### Actions
133	1. Define evaluation criteria
134	2. Create test scenarios
135	3. Measure agent performance
136	4. Test edge cases
137	5. Iterate improvements
138
139	#### Copy-Paste Prompts
140	```
141	Use @agent-evaluation to evaluate agent performance
142	```
143
144	## Agent Architecture
145
146	```
147	User Input -> Planner -> Agent -> Tools -> Memory -> Response
148	\| \| \| \|
149	Decompose LLM Core Actions Short/Long-term
150	```
151
152	## Quality Gates
153
154	- [ ] Agent logic working
155	- [ ] Tools integrated
156	- [ ] Memory functional
157	- [ ] Orchestration tested
158	- [ ] Evaluation passing
159
160	## Related Workflow Bundles
161
162	- `ai-ml` - AI/ML development
163	- `rag-implementation` - RAG systems
164	- `workflow-automation` - Workflow patterns
165
166	## Limitations
167	- Use this skill only when the task clearly matches the scope described above.
168	- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
169	- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

People who liked this also viewed

6 picks

Type