agentica-infrastructure

scooter-lacroix/agentica-infrastructure

AI & ML

About

SKILL.md

agentica-infrastructure

scooter-lacroix/agentica-infrastructure

AI & ML

About

Reference guide for Agentica multi-agent infrastructure APIs

SKILL.md

Agentica Infrastructure Reference

Complete API specification for Agentica multi-agent coordination infrastructure.

When to Use

Building multi-agent workflows with Agentica patterns
Need exact constructor signatures for pattern classes
Want to understand coordination database schema
Implementing custom patterns using primitives
Debugging agent tracking or orphan detection

Quick Reference

11 Pattern Classes

Pattern	Purpose	Key Method
`Swarm`	Parallel perspectives	`.execute(query)`
`Pipeline`	Sequential stages	`.run(initial_state)`
`Hierarchical`	Coordinator + specialists	`.execute(task)`
`Jury`	Voting consensus	`.decide(return_type, question)`
`GeneratorCritic`	Iterative refinement	`.run(task)`
`CircuitBreaker`	Failure fallback	`.execute(query)`
`Adversarial`	Debate + judge	`.resolve(question)`
`ChainOfResponsibility`	Route to handler	`.process(query)`
`MapReduce`	Fan out + reduce	`.execute(query, chunks)`
`Blackboard`	Shared state	`.solve(query)`
`EventDriven`	Event bus	`.publish(event)`

Core Infrastructure

Component	File	Purpose
`CoordinationDB`	`coordination.py`	SQLite tracking
`tracked_spawn`	`tracked_agent.py`	Agent with tracking
`HandoffAtom`	`handoff_atom.py`	Universal handoff format
`BlackboardCache`	`blackboard.py`	Hot tier communication
`MemoryService`	`memory_service.py`	Core + Archival memory
`create_claude_scope`	`claude_scope.py`	Scope with file ops

Primitives

Primitive	Purpose
`Consensus`	Voting (MAJORITY, UNANIMOUS, THRESHOLD)
`Aggregator`	Combine results (MERGE, CONCAT, BEST)
`HandoffState`	Structured agent handoff
`build_premise`	Structured premise builder
`gather_fail_fast`	TaskGroup-based parallel execution

Full API Spec

See: API_SPEC.md in this skill directory

Usage Example

from scripts.agentica_patterns.patterns import Swarm, Jury
from scripts.agentica_patterns.primitives import ConsensusMode
from scripts.agentica_patterns.coordination import CoordinationDB
from scripts.agentica_patterns.tracked_agent import tracked_spawn

# Create tracking database
db = CoordinationDB(session_id="my-session")

# Swarm with tracking
swarm = Swarm(
    perspectives=["Security expert", "Performance expert"],
    db=db
)
result = await swarm.execute("Review this code")

# Jury with consensus
jury = Jury(
    num_jurors=3,
    consensus_mode=ConsensusMode.MAJORITY,
    premise="You evaluate code quality",
    db=db
)
verdict = await jury.decide(bool, "Is this code production ready?")

Location

API spec: .maestro/skills/agentica-infrastructure/API_SPEC.md Source: scripts/agentica_patterns/

About

SKILL.md

About

Reference guide for Agentica multi-agent infrastructure APIs

SKILL.md

Agentica Infrastructure Reference

Complete API specification for Agentica multi-agent coordination infrastructure.

When to Use

Building multi-agent workflows with Agentica patterns
Need exact constructor signatures for pattern classes
Want to understand coordination database schema
Implementing custom patterns using primitives
Debugging agent tracking or orphan detection

Quick Reference

11 Pattern Classes

Pattern	Purpose	Key Method
`Swarm`	Parallel perspectives	`.execute(query)`
`Pipeline`	Sequential stages	`.run(initial_state)`
`Hierarchical`	Coordinator + specialists	`.execute(task)`
`Jury`	Voting consensus	`.decide(return_type, question)`
`GeneratorCritic`	Iterative refinement	`.run(task)`
`CircuitBreaker`	Failure fallback	`.execute(query)`
`Adversarial`	Debate + judge	`.resolve(question)`
`ChainOfResponsibility`	Route to handler	`.process(query)`
`MapReduce`	Fan out + reduce	`.execute(query, chunks)`
`Blackboard`	Shared state	`.solve(query)`
`EventDriven`	Event bus	`.publish(event)`

Core Infrastructure

Component	File	Purpose
`CoordinationDB`	`coordination.py`	SQLite tracking
`tracked_spawn`	`tracked_agent.py`	Agent with tracking
`HandoffAtom`	`handoff_atom.py`	Universal handoff format
`BlackboardCache`	`blackboard.py`	Hot tier communication
`MemoryService`	`memory_service.py`	Core + Archival memory
`create_claude_scope`	`claude_scope.py`	Scope with file ops

Primitives

Primitive	Purpose
`Consensus`	Voting (MAJORITY, UNANIMOUS, THRESHOLD)
`Aggregator`	Combine results (MERGE, CONCAT, BEST)
`HandoffState`	Structured agent handoff
`build_premise`	Structured premise builder
`gather_fail_fast`	TaskGroup-based parallel execution

Full API Spec

See: API_SPEC.md in this skill directory

Usage Example

from scripts.agentica_patterns.patterns import Swarm, Jury
from scripts.agentica_patterns.primitives import ConsensusMode
from scripts.agentica_patterns.coordination import CoordinationDB
from scripts.agentica_patterns.tracked_agent import tracked_spawn

# Create tracking database
db = CoordinationDB(session_id="my-session")

# Swarm with tracking
swarm = Swarm(
    perspectives=["Security expert", "Performance expert"],
    db=db
)
result = await swarm.execute("Review this code")

# Jury with consensus
jury = Jury(
    num_jurors=3,
    consensus_mode=ConsensusMode.MAJORITY,
    premise="You evaluate code quality",
    db=db
)
verdict = await jury.decide(bool, "Is this code production ready?")

Location

API spec: .maestro/skills/agentica-infrastructure/API_SPEC.md Source: scripts/agentica_patterns/