agentica-spawn

AI Community

Repo stars 3,783
Author repo Continuous-Claude-v3

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Spawn Agentica multi-agent patterns Use this skill after user selects an Agentica pattern. "Security expert analyzing for vulner…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “When to Use”, “Pattern Selection to Spawn Method”, “Swarm (Research/Explore)”, “Hierarchical (Build/Implement)”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name agentica-spawn directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “When to Use / Pattern Selection to Spawn Method / Swarm (Research/Explore)” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write / shell-exec / env-read; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

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 run
AGENT_ROLE: Role within the pattern (coordinator, specialist, etc.)
PATTERN_TYPE: Which pattern is running

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: AI
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @parcadei · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Guided setup
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Python
Detected file/system behavior: Read-only
Write / modify
Shell exec
Env read
Detected network behavior: Local-only
Install commands: None (reference only)

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。

Output preview agentica-spawn.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

# 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:

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> When to Use → Pattern Selection to Spawn Method → Swarm (Research/Explore) → Hierarchical (Build/Implement) → Generator/Critic (Iterate/Refine) → Jury (Validate/Verify)
terms    -> Use this skill after user selects an Agentica pattern.
files/cmd -> SWARMID · AGENTROLE · PATTERNTYPE · Generator/Critic · Research/Explore · Build/Implement · Iterate/Refine · Validate/Verify
body sha256 -> 68e6fdba9894