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.
Installs into .claude/skills of the current project.
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---
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
dependencies: ["skill:dual-loop"]
---
## Ecosystem Role: Inner Loop Specialist
This skill provides specialized **Inner Loop Execution** for the [`dual-loop`](../../../agent-loops/skills/dual-loop/SKILL.md).
- **Orchestrated by**: [`agent-orchestrator`](../../agent-orchestrator/skills/orchestrator-agent/SKILL.md)
- **Use Case**: When "generic coding" is insufficient and specialized expertise (Security, QA, Architecture) is required.
- **Why**: The CLI context is naturally isolated (no git, no tools), making it the perfect "Safe Inner Loop".
## Identity: The Sub-Agent Dispatcher π
You, the Antigravity agent, dispatch specialized analysis tasks to Claude CLI sub-agents.
## π οΈ Core Pattern
```bash
cat <PERSONA_PROMPT> | claude -p "<INSTRUCTION>" < <INPUT> > <OUTPUT>
```
## β οΈ CLI Best Practices
### 1. Token Efficiency β PIPE, Don't Load
**Bad** β loads file into agent memory just to pass it:
```python
content = read_file("large.log")
run_command(f"claude -p 'Analyze: {content}'")
```
**Good** β direct shell piping:
```bash
claude -p "Analyze this log" < large.log > analysis.md
```
### 2. Self-Contained Prompts
The CLI runs in a **separate context** β no access to agent tools or memory.
- **Add**: "Do NOT use tools. Do NOT search filesystem."
- Ensure prompt + piped input contain 100% of necessary context
### 3. File Size & Permission Limitations
- The `claude` CLI will block reading massive files (e.g. 5MB+) natively via pipe or `--file` flag. If conducting whole-repository analysis, you MUST build a python script to semantically chunk or scan rather than trying to stuff the whole system into a single bash pipe.
- Always run automated scripts containing `claude` with `--dangerously-skip-permissions` if you are passing complex generated files, otherwise the CLI will hang waiting for User UI approval.
- Ensure the operating environment has an active session (`claude login`) before dispatching autonomous CLI commands, or it will fail silently in the background.
### 4. Output to File
Always redirect output to a file (`> output.md`), then review with `view_file`.
### 5. Severity-Stratified Constraints
When dispatching code-review, architecture, or security analysis, explicitly instruct the CLI sub-agent to use the **Severity-Stratified Output Schema**. This ensures the Outer Loop can parse the results deterministically:
> "Format all findings using the strict Severity taxonomy: π΄ CRITICAL, π‘ MODERATE, π’ MINOR."
## π Persona Categories
| Category | Personas | Use For |
|:---|:---|:---|
| Security | security-auditor | Red team, vulnerability scanning |
| Development | 14 personas | Backend, frontend, React, Python, Go, etc. |
| Quality | architect-review, code-reviewer, qa-expert, test-automator, debugger | Design validation, test planning |
| Data/AI | 8 personas | ML, data engineering, DB optimization |
| Infrastructure | 5 personas | Cloud, CI/CD, incident response |
| Business | product-manager | Product strategy |
| Specialization | api-documenter, documentation-expert | Technical writing |
All personas in: `plugins/personas/`
## π Recommended Audit Loop
1. **Red Team** (Security Auditor) β find exploits
2. **Architect** β validate design didn't add complexity
3. **QA Expert** β find untested edge cases
Run architect **AFTER** red team to catch security-fix side effects.