Agentica Spawn

by parcadeid07ff4b06b62No license3.9K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 8 months ago

Spawn Agentica multi-agent patterns

Instructions onlyAI & Agents
AI-generated overview

Spawns Agentica multi-agent patterns such as Swarm, Hierarchical, Generator/Critic and Jury for a task.

What it does
This skill maps a selected Agentica multi-agent pattern to the corresponding spawn method and shows how to invoke it. It covers Swarm for research and exploration, Hierarchical for build and implementation work, Generator/Critic for iterative refinement, and Jury for validation. It also lists the environment variables passed to spawned agents, such as SWARM_ID, AGENT_ROLE and PATTERN_TYPE.
When to use it
Use it after an Agentica orchestrator prompts for pattern selection, or when the user explicitly requests a multi-agent pattern. It suits complex tasks that benefit from parallel agents, multi-perspective research, coordinated implementation, iterative refinement or high-stakes validation.
Requirements
No scripts are shipped; it is instructions only. It assumes an Agentica multi-agent runtime with the named pattern classes and an environment that supplies SWARM_ID, AGENT_ROLE and PATTERN_TYPE to spawned agents.

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

Source and attribution

Source:parcadei/continuous-claude-v3in.claude/skills/agentica-spawnat commitd07ff4b

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal