Agent Context Isolation
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Agent Orchestration Rules
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
When the user asks to implement something, use implementation agents to preserve main context.
Wrong - burns context:
Main: Read files → Understand → Make edits → Report
(2000+ tokens consumed in main context)
Right - preserves context:
Main: Spawn agent("implement X per plan")
↓
Agent: Reads files → Understands → Edits → Tests
↓
Main: Gets summary (~200 tokens)
| Task Type | Use Agent? | Reason |
|---|---|---|
| Multi-file implementation | Yes | Agent handles complexity internally |
| Following a plan phase | Yes | Agent reads plan, implements |
| New feature with tests | Yes | Agent can run tests |
| Single-line fix | No | Faster to do directly |
| Quick config change | No | Overhead not worth it |
Agents read their own context. Don't read files in main chat just to understand what to pass to an agent - give them the task and they figure it out.
Implement Phase 4: Outcome Marking Hook from the Artifact Index plan.
**Plan location:** thoughts/shared/plans/2025-12-24-artifact-index.md (search for "Phase 4")
**What to create:**
1. TypeScript hook
2. Shell wrapper
3. Python script
4. Register in settings.json
When done, provide a summary of files created and any issues.
When user says these, consider using an agent:
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Agent Context Isolation
中文简介正在准备中。当前显示原文说明。
Agentic Workflow Pattern
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Guide for integrating Agentica SDK with Claude Code CLI proxy
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Reference guide for Agentica multi-agent infrastructure APIs
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Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity
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Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
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