Use this skill when developing or debugging the Agentica-Claude proxy integration.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionagentica-claude-proxyExecute the skills CLI command in your project's root directory to begin installation:
Fetches agentica-claude-proxy from parcadei/continuous-claude-v3 and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate agentica-claude-proxy. Access via /agentica-claude-proxy in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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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 |
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
parcadei/continuous-claude-v3
parcadei/continuous-claude-v3
aradotso/trending-skills
anthropics/skills
anthropics/skills
JuliusBrussee/caveman
Registry listing for agentica-claude-proxy matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in agentica-claude-proxy — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: agentica-claude-proxy is focused, and the summary matches what you get after install.
agentica-claude-proxy reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added agentica-claude-proxy from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
agentica-claude-proxy fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
agentica-claude-proxy reduced setup friction for our internal harness; good balance of opinion and flexibility.
agentica-claude-proxy is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: agentica-claude-proxy is focused, and the summary matches what you get after install.
I recommend agentica-claude-proxy for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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