parcadei / agentica-spawn
Install for your project team
Run this command in your project directory to install the skill for your entire team:
mkdir -p .claude/skills/agentica-spawn && curl -L -o skill.zip "https://fastmcp.me/Skills/Download/2697" && unzip -o skill.zip -d .claude/skills/agentica-spawn && rm skill.zipProject Skills
This skill will be saved in .claude/skills/agentica-spawn/ and checked into git. All team members will have access to it automatically.
Important: Please verify the skill by reviewing its instructions before using it.
Spawn Agentica multi-agent patterns
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Skill Content
---
name: agentica-spawn
description: Spawn Agentica multi-agent patterns
user-invocable: false
---
# Agentica Spawn Skill
Use this skill after user selects an Agentica pattern.
## When to Use
- After agentica-orchestrator prompts user for pattern selection
- When user explicitly requests a multi-agent pattern (swarm, hierarchical, etc.)
- When implementing complex tasks that benefit from parallel agent execution
- For research tasks requiring multiple perspectives (use Swarm)
- For implementation tasks requiring coordination (use Hierarchical)
- For iterative refinement (use Generator/Critic)
- For high-stakes validation (use Jury)
## Pattern Selection to Spawn Method
### Swarm (Research/Explore)
```python
swarm = Swarm(
perspectives=[
"Security expert analyzing for vulnerabilities",
"Performance expert optimizing for speed",
"Architecture expert reviewing design"
],
aggregate_mode=AggregateMode.MERGE,
)
result = await swarm.execute(task_description)
```
### Hierarchical (Build/Implement)
```python
hierarchical = Hierarchical(
coordinator_premise="You break tasks into subtasks",
specialist_premises={
"planner": "You create implementation plans",
"implementer": "You write code",
"reviewer": "You review code for issues"
},
)
result = await hierarchical.execute(task_description)
```
### Generator/Critic (Iterate/Refine)
```python
gc = GeneratorCritic(
generator_premise="You generate solutions",
critic_premise="You critique and suggest improvements",
max_rounds=3,
)
result = await gc.run(task_description)
```
### Jury (Validate/Verify)
```python
jury = Jury(
num_jurors=5,
consensus_mode=ConsensusMode.MAJORITY,
premise="You evaluate the solution"
)
verdict = await jury.decide(bool, question)
```
## Environment Variables
All spawned agents receive:
- `SWARM_ID`: Unique identifier for this swarm run
- `AGENT_ROLE`: Role within the pattern (coordinator, specialist, etc.)
- `PATTERN_TYPE`: Which pattern is running