agentica-spawn
- Repo stars 3,783
- Author updated Live
- Author repo Continuous-Claude-v3
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @parcadei · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- Python
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Env read
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: agentica-spawn
description: Spawn Agentica multi-agent patterns Use this skill after user selects an Agentica pattern. "Secu…
category: ai
runtime: Python
---
# agentica-spawn output preview
## PART A: Task fit
- Use case: Spawn Agentica multi-agent patterns Use this skill after user selects an Agentica pattern. "Security expert analyzing for vulnerabilities", "Performance expert optimizing for speed", "Architecture expert reviewing design" aggregate_mode=AggregateMode.MERGE, runs entirely locally; runs on Python. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Use / Pattern Selection to Spawn Method / Swarm (Research/Explore)” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Spawn Agentica multi-agent patterns Use this skill after user selects an Agentica pattern. "Security expert analyzing for vulnerabilities", "Performance expert optimizing for speed", "Architecture expert reviewing design" aggregate_mode=AggregateMode.MERGE, runs entirely locally; runs on Python. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “When to Use / Pattern Selection to Spawn Method / Swarm (Research/Explore)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands, read environment variables; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands, read environment variables; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands, read environment variables.
Validate with a small run
Start with a small task and check whether the result follows “When to Use / Pattern Selection to Spawn Method / Swarm (Research/Explore)”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: agentica-spawn
description: Spawn Agentica multi-agent patterns Use this skill after user selects an Agentica pattern. "Secu…
category: ai
source: parcadei/Continuous-Claude-v3
---
# agentica-spawn
## When to use
- Spawn Agentica multi-agent patterns Use this skill after user selects an Agentica pattern. "Security expert analyzing…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to Use / Pattern Selection to Spawn Method / Swarm (Research/Explore)” and keep inference separate from source facts.
- read files, write/modify files, run shell commands, read environment variables; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "agentica-spawn" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to Use / Pattern Selection to Spawn Method / Swarm (Research/Explore)
rules -> SKILL.md triggers / order / output contract
runtime -> Python | read files, write/modify files, run shell commands, read environment variables | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}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)
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)
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)
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)
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 runAGENT_ROLE: Role within the pattern (coordinator, specialist, etc.)PATTERN_TYPE: Which pattern is running
Decide Fit First
Design Intent
How To Use It
Boundaries And Review