# Gemini CLI Agent

> Gemini 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.

- Skill: `richfrem/gemini-cli-agent-4` (Agent Skill)
- Install (CLI): `npx skillmds@latest add richfrem/gemini-cli-agent-4`
- Raw SKILL.md: https://api.skillmd.com/api/skills/richfrem/gemini-cli-agent-4/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: richfrem (https://skillmd.com/u/richfrem)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/richfrem/gemini-cli-agent-4

---


## 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 🎭

You, the Antigravity agent, dispatch specialized analysis tasks to Gemini CLI sub-agents.

## 🛠️ Core Pattern
```bash
cat <PERSONA_PROMPT> | gemini -p "<INSTRUCTION>" < <INPUT> > <OUTPUT>
```
*Note: Gemini uses `-p` or `--prompt` for headless execution where output is desired without interactive prompts.*

## ⚠️ CLI Best Practices

### 1. Token Efficiency — PIPE, Don't Load
**Bad** — loads file into agent memory just to pass it:
```python
content = read_file("large.log")
run_command(f"gemini -p 'Analyze: {content}'")
```
**Good** — direct shell piping:
```bash
gemini -p "Analyze this log" < large.log > analysis.md
```

### 2. Self-Contained Prompts
The CLI runs in a **separate context** — 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.
- **Model Selection**: Gemini supports the `-m <model>` flag (e.g., `-m gemini-2.5-pro` or `-m gemini-2.5-flash`).

### 3. Output to File
Always redirect output to a file (`> output.md`), then review with `view_file`.

### 4. 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: 🔴 CRITICAL, 🟡 MODERATE, 🟢 MINOR."

## 🎭 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/`

## 🔄 Recommended Audit Loop
1. **Red Team** (Security Auditor) → find exploits
2. **Architect** → validate design didn't add complexity
3. **QA Expert** → find untested edge cases

Run architect **AFTER** red team to catch security-fix side effects.