Exercise 10: Your First AGY Agent¶
Duration: 45 min | Module: 3 — Building AGY Agents
Objective¶
Build a Code Review Agent using the google-antigravity Python SDK. The agent reads files, identifies issues, and produces a structured review report — all running autonomously with a security guard hook that blocks writes.
Setup¶
# Create project directory
mkdir -p ~/agy-review-agent/tools ~/agy-review-agent/hooks ~/agy-review-agent/skills/python-review
# Set up Python environment
cd ~/agy-review-agent
python3 -m venv .venv
source .venv/bin/activate
pip install google-antigravity pydantic
Set your API key:
Part 1: Define the Tools (10 min)¶
Create tools/file_tools.py with two read-only tools:
import os
def read_file(file_path: str) -> str:
"""Read and return the contents of a file at the given path.
Args:
file_path: Absolute or relative path to the file.
Returns:
The file contents as a string, or an error message if not found.
"""
try:
with open(file_path, "r", encoding="utf-8") as f:
return f.read()
except FileNotFoundError:
return f"Error: File not found at {file_path}"
except PermissionError:
return f"Error: Permission denied reading {file_path}"
def list_directory(directory_path: str) -> str:
"""List files and subdirectories at the given path.
Args:
directory_path: Path to the directory to list.
Returns:
A formatted string listing all entries, or an error message.
"""
try:
entries = sorted(os.listdir(directory_path))
result_lines = []
for entry in entries:
full_path = os.path.join(directory_path, entry)
kind = "dir" if os.path.isdir(full_path) else "file"
size = os.path.getsize(full_path) if kind == "file" else ""
result_lines.append(f" [{kind}] {entry}" + (f" ({size} bytes)" if size else ""))
return f"Contents of {directory_path}:\n" + "\n".join(result_lines)
except FileNotFoundError:
return f"Error: Directory not found at {directory_path}"
Create tools/state_tools.py with a stateful tool using ToolContext:
from google.antigravity.tools.tool_context import ToolContext
def record_finding(
severity: str,
message: str,
file_path: str,
line_number: int = None,
ctx: ToolContext = None,
) -> dict:
"""Records a code review finding into session state.
Args:
severity: One of 'critical', 'warning', 'info'.
message: Description of the finding.
file_path: The file where the issue was found.
line_number: Optional line number of the finding.
Returns:
Confirmation dict with the finding index.
"""
finding = {
"severity": severity,
"message": message,
"file_path": file_path,
"line_number": line_number,
}
findings = ctx.get_state("findings", [])
findings.append(finding)
ctx.set_state("findings", findings)
return {"status": "recorded", "index": len(findings) - 1, "total": len(findings)}
Key concept: The
ctx: ToolContextparameter is auto-injected by the SDK at call time and stripped from the schema shown to the model. The model never sees it — it just callsrecord_finding(severity, message, file_path).
Part 2: Write the Review Skill (5 min)¶
Create skills/python-review/SKILL.md:
---
name: python-review
description: Code review rubric for Python projects
---
## Python Code Review Rubric
When reviewing Python code, evaluate against these criteria:
### Correctness
- Are there logic errors or off-by-one bugs?
- Are edge cases handled (empty inputs, None values, large datasets)?
- Are exceptions caught and handled appropriately?
### Security
- Are there hardcoded secrets, API keys, or credentials?
- Is user input sanitised before use in SQL, shell commands, or file paths?
- Are there unsafe uses of `eval()`, `exec()`, or `pickle.loads()`?
### Code Quality
- Does the code follow PEP 8 style conventions?
- Are functions focused (single responsibility)?
- Are variable names descriptive and consistent?
- Are there unnecessary comments or dead code?
### Performance
- Are there N+1 query patterns or repeated expensive operations?
- Are large files read entirely into memory when streaming would suffice?
- Are there blocking calls in async code?
### Severity Classification
- **critical**: Security vulnerabilities, data loss risks, crashes
- **warning**: Logic bugs, performance issues, missing error handling
- **info**: Style issues, minor improvements, documentation gaps
Part 3: Configure the Agent (10 min)¶
Create config.py:
from pathlib import Path
import re
from google.antigravity import LocalAgentConfig
from google.antigravity.hooks import policy
from google.antigravity.types import CapabilitiesConfig
from tools.file_tools import read_file, list_directory
from tools.state_tools import record_finding
def load_skill(skill_name: str) -> str:
"""Load a SKILL.md and strip YAML frontmatter."""
skill_path = Path("skills") / skill_name / "SKILL.md"
if skill_path.exists():
content = skill_path.read_text(encoding="utf-8")
return re.sub(r"^---\n.*?---\n", "", content, flags=re.DOTALL).strip()
return ""
review_rubric = load_skill("python-review")
agent_config = LocalAgentConfig(
model="gemini-3.5-flash",
system_instructions=f"""You are a senior Python code reviewer.
Your job:
1. Use `list_directory` to understand the project structure
2. Use `read_file` to read each relevant source file
3. For every issue found, call `record_finding` with severity, message, file path, and line number
4. After reviewing all files, provide a final summary
Always read files before commenting. Be specific — cite line numbers.
Never guess at code contents. If you can't read a file, say so.
## Review Rubric
{review_rubric}
""",
tools=[read_file, list_directory, record_finding],
capabilities=CapabilitiesConfig(
enable_subagents=False,
),
policies=[policy.allow_all()],
)
Part 4: Add a Security Guard Hook (5 min)¶
Create hooks/security_guard.py:
from google.antigravity.hooks import hooks
from google.antigravity.types import ToolCall, HookResult
# Tools that could modify the filesystem
WRITE_TOOLS = {"write_to_file", "edit_file", "replace_file_content", "run_command"}
@hooks.pre_tool_call_decide
async def block_writes(tool_call: ToolCall) -> HookResult:
"""Block any tool call that could modify files.
This agent is read-only — it reviews code but never changes it.
"""
if tool_call.name in WRITE_TOOLS:
return HookResult(
allow=False,
message=f"Blocked: {tool_call.name} is not allowed. This agent is read-only.",
)
if tool_call.name == "run_command":
cmd = tool_call.args.get("CommandLine", "")
if any(danger in cmd for danger in ["rm ", "mv ", "chmod", "chown", "dd "]):
return HookResult(
allow=False,
message=f"Blocked dangerous command: {cmd}",
)
return HookResult(allow=True)
Why this matters: Even with
policy.allow_all(), the hook fires before every tool call and can deny it. Defense in depth — policy sets the baseline, hooks enforce guardrails.
Part 5: Wire It Together with Streaming + Structured Output (15 min)¶
Create main.py:
import asyncio
import pydantic
from google.antigravity import Agent
from config import agent_config
from hooks.security_guard import block_writes
class ReviewFinding(pydantic.BaseModel):
severity: str
message: str
file_path: str
line_number: int = None
class ReviewResult(pydantic.BaseModel):
summary: str
findings: list[ReviewFinding]
files_reviewed: list[str]
overall_health: str # 'healthy', 'needs-attention', 'critical'
async def run_review(target_path: str):
"""Run a code review with streaming output, then extract structured result."""
# Add the hook to the config
config = agent_config.model_copy(
update={
"hooks": [block_writes],
}
)
print(f"=== Code Review: {target_path} ===\n")
# Phase 1: Streaming review (human-readable output)
async with Agent(config) as agent:
response = await agent.chat(
f"Review all Python files in {target_path}. "
f"Use record_finding for each issue. Then provide a summary."
)
# Stream the response as it arrives
async for delta in response:
print(delta, end="", flush=True)
print("\n\n=== Structured Report ===\n")
# Phase 2: Structured extraction
structured_config = agent_config.model_copy(
update={
"response_schema": ReviewResult,
"hooks": [block_writes],
}
)
async with Agent(structured_config) as agent:
response = await agent.chat(
f"Review all Python files in {target_path}. "
f"Return your findings as structured output."
)
result = await response.structured_output()
print(f"Overall Health: {result['overall_health']}")
print(f"Files Reviewed: {len(result['files_reviewed'])}")
print(f"Findings: {len(result['findings'])}")
for finding in result["findings"]:
icon = {"critical": "🔴", "warning": "🟡", "info": "🔵"}.get(
finding["severity"], "⚪"
)
loc = f":{finding['line_number']}" if finding.get("line_number") else ""
print(f" {icon} [{finding['severity']}] {finding['file_path']}{loc}")
print(f" {finding['message']}")
if __name__ == "__main__":
import sys
target = sys.argv[1] if len(sys.argv) > 1 else "."
asyncio.run(run_review(target))
Run It¶
# Review the agent's own code (meta!)
python main.py .
# Review a specific project directory
python main.py /path/to/your/project/src
Completion Criteria¶
- [ ] Three tools defined:
read_file,list_directory,record_finding(withToolContext) - [ ]
SKILL.mdcreated with a Python review rubric - [ ]
LocalAgentConfigconstructed withpolicy.allow_all()and tools list - [ ]
@hooks.pre_tool_call_decidesecurity guard blocks write operations - [ ] Agent runs and streams output to the console
- [ ] Structured
ReviewResultreturned with findings, severity levels, and overall health - [ ] Agent successfully reviews at least one Python file and records findings