agentsclimarketplace

Agentica claude proxy

Skill ulpi-io/plugin-marketplace/plugins/parcadei/skills/agentica-claude-proxy

Guide for integrating Agentica SDK with Claude Code CLI proxyFrom its SKILL.md

Install
npx -y skills add ulpi-io/plugin-marketplace --skill agentica-claude-proxy

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SKILL.md

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Agentica-Claude Code Proxy Integration

Use this skill when developing or debugging the Agentica-Claude proxy integration.

When to Use

  • Setting up Agentica agents to use Claude Code tools
  • Debugging agent hallucination issues
  • Fixing permission errors in file operations
  • Understanding the REPL response format

Architecture Overview

Agentica Agent → S_M_BASE_URL → Claude Proxy → claude -p → Claude CLI (with tools)
                 (localhost:2345)   (localhost:8080)

Critical Requirements

1. --allowedTools Flag (REQUIRED)

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.

2. SSE Streaming Format (REQUIRED)

Agentica expects SSE streaming, not plain JSON:

# Response format
yield f"data: {json.dumps(chunk)}\n\n"
yield "data: [DONE]\n\n"

3. REPL Response Format (REQUIRED)

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 ```.

Anti-Hallucination Prompt Engineering

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.

Path Sandboxing

Both Claude Code and Agentica have sandboxes:

  • /tmp/ paths are blocked by Claude Code
  • Files outside project directory blocked by Agentica

Solution: Use project-relative paths like workspace/ instead of /tmp/

Debugging

Check Agent Logs

cat logs/agent-<N>.log

Note: Logs only show final conversational response, not tool invocations.

Test Proxy Directly

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}'

Verify File Operations

# After agent claims to create file
ls -la workspace/test.txt
cat workspace/test.txt

Server Commands

Start Servers

# 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

Use Swarm

S_M_BASE_URL=http://localhost:2345 uv run python your_script.py

Health Checks

curl http://localhost:8080/health  # Proxy
curl http://localhost:2345/health  # Agentica

Reference Files

  • Proxy implementation: scripts/agentica/claude_proxy.py
  • REPL_BASELINE prompt: scripts/agentica/claude_proxy.py:49-155
  • Comprehensive test: workspace/test_swarm_all_tools.py
  • DependencySwarm: scripts/agentica/dependency_swarm.py

Common Errors

ErrorCauseFix
"Permission denied"Missing --allowedToolsAdd --allowedTools Read Write Edit Bash
Agent claims success but file not createdHallucinationAdd anti-hallucination prompt section
"Cannot access /tmp/..."Sandbox restrictionUse project-relative paths
"APIConnectionError"Wrong response formatUse SSE streaming (data: {...}\n\n)
"NameError: view_file"Agent using REPL functionsAdd REPL_BASELINE with native tool examples

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most context ai engineering skills give in ~1.0k tokens

Counted across 1,193 of the 1,976 authors here whose files we hold, read 2026-08-07

  • Dispatch a fresh implementer subagent per taskin 48 of 1193, across 19 files
  • Dispatch a final code reviewer after all tasksin 33 of 1193, across 8 files
  • Provide full task text to the subagentin 30 of 1193, across 9 files
  • Review spec compliance before code qualityin 27 of 1193, across 10 files
  • Make the hook script executablein 26 of 1193, across 8 files
  • Re-snapshot after navigation or DOM changesin 25 of 1193, across 19 files
  • Read files before editing themin 22 of 1193, across 11 files
  • Answer subagent questions before proceedingin 22 of 1193, across 7 files
  • Mark task complete in TodoWrite after approvalin 22 of 1193, across 6 files
  • Merge hook into existing settingsin 21 of 1193, across 3 files
  • Ask if installation is global or projectin 20 of 1193, across 2 files
  • Copy the hook script to target locationin 20 of 1193, across 2 files

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