| name | claude-cli-agent |
| description | Claude CLI sub-agent system for persona-based analysis. Use when piping large contexts to Anthropic models for security audits, architecture reviews, QA analysis, or any specialized analysis requiring a fresh model context.
|
| allowed-tools | Bash, Read, Write |
Identity: The Claude Sub-Agent Dispatcher 🎭
You, the Antigravity agent, dispatch specialized analysis tasks to Claude CLI sub-agents.
✅ Minimal Working Code Review Agent Pattern
To ensure Claude CLI behaves as a specialized persona rather than a generic responder, always embed the persona and source material directly into the prompt flag (-p).
claude --model haiku-4.5 -p "$(cat agents/persona.md)
---SOURCE CODE---
$(cat target.py)
---INSTRUCTION---
Perform a full code review. Use severity levels: 🔴 CRITICAL, 🟡 MODERATE, 🟢 MINOR.
You are operating as an isolated sub-agent.
Do NOT use tools. Do NOT access filesystem." > review.md
🛠️ Orchestration Pattern: run_agent.py (Cross-Platform)
For reusable sub-agent execution, use the provided Python orchestrator which handles temp file assembly and prompt concatenation reliably across Windows, macOS, and Linux.
python ./scripts/run_agent.py <PERSONA_FILE> <INPUT_FILE> <OUTPUT_FILE> "<INSTRUCTION>"
Example Usage:
python ./scripts/run_agent.py agents/security-auditor.md target.py security.md \
"Find vulnerabilities. Use severity levels: 🔴 CRITICAL, 🟡 MODERATE, 🟢 MINOR."
🎭 Persona Registry (agents/)
These personas are mirrored from the Gemini and Copilot plugins to ensure consistent "Agentic" analysis across the ecosystem.
| Persona | Use For |
|---|
security-auditor.md | Red team, vulnerability scanning, threat modeling |
refactor-expert.md | Optimizing code for readability, performance, and DRY |
architect-review.md | Assessing system design, modularity, and complexity |
⚠️ CLI Best Practices & Failure Modes
1. ⚡ Preferred Model: Haiku 4.5
For rapid, cost-effective analytical sub-agent tasks, always specify --model haiku-4.5. It provides the best latency for "Inner Loop" code reviews.
2. ❌ Leading Newline Fix
If your prompt starts with YAML frontmatter (e.g., ---), some shell parsers might misinterpret the flag. Always prepend a newline to the prompt string when passing it to -p. (Note: The run_agent.py script handles this automatically).
3. 🧩 Force Agent Behavior
Always add these instructions to your dispatch prompt to prevent the sub-agent from attempting to use external tools:
"You are operating as an isolated sub-agent. Do NOT use tools. Do NOT access filesystem. Only use the provided input."
✅ Smoke Test
python ./scripts/run_agent.py agents/refactor-expert.md target.py output.md "Refactor this code."
