SuperAPI AI Directory

agy-cli-agent

Agents & models

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Updated 10-16 08:00

About this skill

Execution Contract

See references/execution-contract.md (full rules) and references/backend-capabilities.md (backend selection).

Key rules: (1) One backend per task — no silent fallback. (2) Run output-validator or self-critic when output quality is uncertain. (3) Architecture/high-risk tasks require architect-review → red-team-reviewer → debate-synthesizer. (4) Backend failure → halt and log to references/map-debt.md. No workarounds.


Identity: The Antigravity Sub-Agent Dispatcher

You dispatch tasks to Google Gemini (and other) models via the agy binary.

[!IMPORTANT] agy is the sole Gemini CLI since the standalone gemini binary retired June 18 2026. All Gemini model work — including cost-efficient older models — routes through agy.

Model Strategy: Flash by Default, Pro for Deep Reasoning

See references/agy-models.json for the full model catalog, cost tiers, and strategy field.

# Default (Flash — faster, cheaper/token, optimized for agentic/coding tasks)
python ./scripts/run_agent.py <PERSONA> <INPUT> <OUTPUT> "<INSTR>" --cli agy
# ↑ run_agent.py loads gemini-3.5-flash from references/cheapest_models.json

# Explicit Low thinking (recommended for CLI loops to control Thought Preservation cost)
python ./scripts/run_agent.py <PERSONA> <INPUT> <OUTPUT> "<INSTR>" --cli agy --model "Gemini 3.5 Flash (Low)"

# Pro — escalate for deep reasoning / architecture decisions
python ./scripts/run_agent.py <PERSONA> <INPUT> <OUTPUT> "<INSTR>" --cli agy --model gemini-3.1-pro

Flash vs Pro: Which to Use

Gemini 3.5 Flash Gemini 3.1 Pro
Price (in/out per 1M) $1.50 / $9.00 $2.00 / $12.00
Speed 4× faster Baseline
Agentic tool use / MCP / terminal Best Good
Coding (edit-test loops) Best Better for final review
Deep abstract reasoning Good Best
Architecture planning Good Best
Max output tokens 65,536 32,768

Default: Flash. Use Pro only when the task requires deep multi-step reasoning or expert-level judgment.

Thinking level note: Flash with High thinking can inflate tokens via Thought Preservation. Use Low thinking level for high-frequency CLI dispatch loops.


Minimal Working Pattern

agy --dangerously-skip-permissions --model "Gemini 3.1 Pro (Low)" -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

python ./scripts/run_agent.py <PERSONA_FILE> <INPUT_FILE> <OUTPUT_FILE> "<INSTRUCTION>" --cli agy

run_agent.py calls agy --dangerously-skip-permissions -p and streams output live to stdout and the output file simultaneously. Loads model from references/cheapest_models.json (currently gemini-3.1-pro).

Health Check

agy -p "HEARTBEAT CHECK: Respond with HEARTBEAT_OK only."
# or via run_agent.py:
python ./scripts/run_agent.py /dev/null /dev/null ./heartbeat.md "HEARTBEAT CHECK: Respond HEARTBEAT_OK only." --cli agy
grep -q "HEARTBEAT_OK" ./heartbeat.md && echo "OK" || echo "FAIL"

Example

python ./scripts/run_agent.py agents/security-auditor.md target.py security.md \
"Find vulnerabilities. Use severity levels: 🔴 CRITICAL, 🟡 MODERATE, 🟢 MINOR." --cli agy

Available Models

Display Name (agy models) --model ID Thinking Rec
Gemini 3.5 Flash (Low) gemini-3.5-flash-low Low Best for CLI loops — cheapest, fastest
Gemini 3.5 Flash (Medium) gemini-3.5-flash Medium Default — standard dispatch
Gemini 3.5 Flash (High) gemini-3.5-flash-high High Single-shot deep tasks only
Gemini 3.1 Pro (Low) gemini-3.1-pro Low Deep reasoning, architecture
Gemini 3.1 Pro (High) gemini-3.1-pro-high High Most demanding reasoning only
Claude Sonnet 4.6 (Thinking) claude-sonnet-4.6-thinking — Anthropic quality via agy
Claude Opus 4.6 (Thinking) claude-opus-4.6-thinking — Critical tasks only
GPT-OSS 120B (Medium) gpt-oss-120b Medium OpenAI OSS via agy

Full pricing data and strategy field: references/agy-models.json


Persona Registry (agents/)

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 Flags Reference

Flag Purpose
-p "prompt" / --prompt "prompt" Pass prompt non-interactively
--model <id> Select model (see table above)
--dangerously-skip-permissions Headless mode — skip all permission prompts
--sandbox Run in sandboxed environment

CLI Best Practices

Path

agy is typically at /opt/homebrew/bin/agy. Confirm with which agy.

Avoid Shell Expansion for Large Contexts

$(cat ...) > 10KB can silently fail. run_agent.py writes to a temp file automatically.

Backgrounding & TTY (SIGTTIN)

nohup agy --dangerously-skip-permissions -p "..." >> log.txt 2>&1 < /dev/null &

< /dev/null is required to prevent SIGTTIN stops in background processes.


Smoke Test

agy -p "hello"
python ./scripts/run_agent.py agents/refactor-expert.md target.py output.md "Refactor this code." --cli agy