Agent Context Isolation
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Guide for integrating Agentica SDK with Claude Code CLI proxy
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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。
Use this skill when developing or debugging the Agentica-Claude proxy integration.
Agentica Agent → S_M_BASE_URL → Claude Proxy → claude -p → Claude CLI (with tools)
(localhost:2345) (localhost:8080)
Claude CLI in -p mode restricts file operations. You MUST add:
subprocess.run([
"claude", "-p", prompt,
"--append-system-prompt", system_prompt,
"--allowedTools", "Read", "Write", "Edit", "Bash", # REQUIRED
])
Without this, agents will report "permission denied" for Write/Edit operations.
Agentica expects SSE streaming, not plain JSON:
# Response format
yield f"data: {json.dumps(chunk)}\n\n"
yield "data: [DONE]\n\n"
Agents MUST return results as Python code blocks with a return statement:
return "your result here"
Agentica's REPL parser extracts code between ```python and ```.
Agents will hallucinate success without actually using tools unless you explicitly warn them:
## ANTI-HALLUCINATION WARNING
**STOP AND READ THIS CAREFULLY:**
You have access to these tools: Read, Write, Edit, Bash
When the task asks you to create/modify/run something:
1. FIRST: Actually invoke the tool (Read, Write, Edit, or Bash)
2. SECOND: Wait for the tool result
3. THIRD: Then return your answer based on what actually happened
**DO NOT** skip the tool invocation and just claim success!
If you didn't invoke a tool, you CANNOT claim the action succeeded.
Both Claude Code and Agentica have sandboxes:
/tmp/ paths are blocked by Claude CodeSolution: Use project-relative paths like workspace/ instead of /tmp/
cat logs/agent-<N>.log
Note: Logs only show final conversational response, not tool invocations.
curl -s http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{"model": "claude", "messages": [{"role": "user", "content": "Create file at workspace/test.txt"}], "stream": false}'
# After agent claims to create file
ls -la workspace/test.txt
cat workspace/test.txt
# Terminal 1: Proxy
uv run python scripts/agentica/claude_proxy.py --port 8080
# Terminal 2: Agentica Server
cd workspace/agentica-research/agentica-server
INFERENCE_ENDPOINT_URL=http://localhost:8080/v1/chat/completions uv run agentica-server --port 2345
S_M_BASE_URL=http://localhost:2345 uv run python your_script.py
curl http://localhost:8080/health # Proxy
curl http://localhost:2345/health # Agentica
scripts/agentica/claude_proxy.pyscripts/agentica/claude_proxy.py:49-155workspace/test_swarm_all_tools.pyscripts/agentica/dependency_swarm.py| Error | Cause | Fix |
|---|---|---|
| "Permission denied" | Missing --allowedTools | Add --allowedTools Read Write Edit Bash |
| Agent claims success but file not created | Hallucination | Add anti-hallucination prompt section |
| "Cannot access /tmp/..." | Sandbox restriction | Use project-relative paths |
| "APIConnectionError" | Wrong response format | Use SSE streaming (data: {...}\n\n) |
| "NameError: view_file" | Agent using REPL functions | Add REPL_BASELINE with native tool examples |
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Agent Context Isolation
中文简介正在准备中。当前显示原文说明。
Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.
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Agentic Workflow Pattern
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Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.
中文简介正在准备中。当前显示英语简介。
Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.
中文简介正在准备中。当前显示英语简介。
Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
中文简介正在准备中。当前显示原文说明。