Skip to main content

agentica-spawn

Spawn Agentica multi-agent patterns

Informations de source

Dépôt
parcadei/Continuous-Claude-v3
Dernière activité de la source
10 janvier 2026 à 01:54
Langue détectée de SKILL.md
anglais
Étoiles
3 942
Forks
303

Options d'installation

Le prompt qui vérifie d'abord la source est sélectionné par défaut. Vous pouvez passer à une commande directe ou télécharger une copie locale.

Vérifiez les fichiers source

Lisez SKILL.md et les fichiers associés affichés par SkillsMP avant de décider de l'installer.

Affichage de SKILL.md

SKILL.md
Instructions source · Aperçu en lecture seule
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
Voir sur GitHub