claude-cli-agent

Dependencies

This skill requires Python 3.8+ and standard library only. No external packages needed.

To install this skill's dependencies:

pip-compile ./requirements.in
pip install -r ./requirements.txt

See ./requirements.txt for the dependency lockfile (currently empty — standard library only).

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Ecosystem Role: Inner Loop Specialist

This skill provides specialized Inner Loop Execution for the dual-loop skill.

• Orchestrated by: the agent-orchestrator skill (see the dual-loop plugin)
• 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 Claude CLI sub-agents.

🛠️ Core Pattern

cat <PERSONA_PROMPT> | claude -p "<INSTRUCTION>" < <INPUT> > <OUTPUT>

⚠️ CLI Best Practices

1. Token Efficiency — PIPE, Don't Load

Bad — loads file into agent memory just to pass it:

content = read_file("large.log")
run_command(f"claude -p 'Analyze: {content}'")

Good — direct shell piping:

claude -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

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: 🔴 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 are documented in the table above. Load the persona prompt file from your CLI plugin's agents/ directory.

🔄 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.