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agentica-spawn
by parcadei
Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.
⭐ 3,352🍴 252📅 Jan 23, 2026
agentsclaude-codeclaude-code-cliclaude-code-hooksclaude-code-mcpclaude-code-skillsclaude-code-subagentsclaude-skills
Use Cases
🔗
MCP Server Integration
AI tool integration using Model Context Protocol. Using agentica-spawn.
🔗
API Integration
Easily build API integrations with external services.
🔄
Data Synchronization
Automatically sync data between multiple systems.
📡
Webhook Setup
Enable event-driven integrations with webhooks.
SKILL.md
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)
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
Score
Total Score
95/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
✓LICENSE
ライセンスが設定されている
+10
✓説明文
100文字以上の説明がある
+10
✓人気
GitHub Stars 1000以上
+15
✓最近の活動
1ヶ月以内に更新
+10
✓フォーク
10回以上フォークされている
+5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
✓タグ
1つ以上のタグが設定されている
+5
Reviews
💬
Reviews coming soon

