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agentica-spawn
Spawn Agentica multi-agent patterns
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This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Stars
3,611
Hot score
99
Updated
March 20, 2026
Overall rating
C4.8
Composite score
4.8
Best-practice grade
B78.7
Install command
npx @skill-hub/cli install parcadei-continuous-claude-v3-agentica-spawn
Repository
parcadei/Continuous-Claude-v3
Skill path: .claude/skills/agentica-spawn
Spawn Agentica multi-agent patterns
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: parcadei.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install agentica-spawn into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/parcadei/Continuous-Claude-v3 before adding agentica-spawn to shared team environments
- Use agentica-spawn for development workflows
Works across
Claude CodeCodex CLIGemini CLIOpenCode
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
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