richfrem

copilot-cli-agent

Copilot CLI sub-agent system for persona-based analysis. Use when piping large contexts to GitHub Copilot models for security audits, architecture reviews, QA analysis, or any specialized analysis requiring a fresh model context.

richfrem 5 1 Updated 7mo ago

Resources

2
GitHub

Install

npx skillscat add richfrem/project-sanctuary/copilot-cli-agent

Install via the SkillsCat registry.

SKILL.md

Ecosystem Role: Inner Loop Specialist

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

  • Orchestrated by: `agent-orchestrator`
  • 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 Copilot CLI sub-agents.

🛠️ Core Pattern

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

Note: Copilot uses -p or --prompt for non-interactive scripting runs.

⚠️ 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"copilot -p 'Analyze: {content}'")

Good — direct shell piping:

copilot -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.
  • Security Check: Copilot CLI has explicit permission flags (e.g. --allow-all-tools, --allow-all-paths). For isolated sub-agents, do not provide these flags to ensure safe headless execution.

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."

✅ Smoke Test (Copilot CLI)

Use this minimal command to verify the CLI is callable and returns output:

copilot -p "Reply with exactly: COPILOT_CLI_OK"

Expected result:

  • CLI prints COPILOT_CLI_OK (or very close equivalent) and exits successfully.

If the test fails:

  • Confirm copilot is on PATH.
  • Ensure you are authenticated in the Copilot CLI session.
  • Retry without any permission flags; keep the test minimal and isolated.

🎭 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.