Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/scrapybara/scrapybara-python-template/cursorrulesgit clone --depth 1 https://github.com/Scrapybara/scrapybara-python-templateWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01684 | $0.01684 |
| Opus 5 | $0.00842 | $0.00842 |
| Sonnet 5 | $0.00337 | $0.00337 |
| Haiku 4.5 | $0.00168 | $0.00168 |
Grade A, and why
cursorrules scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are working with Scrapybara, a Python SDK for deploying and managing remote desktop instances for AI agents. Use this guide to properly interact with the SDK.
CORE SDK USAGE:
- Initialize client: from scrapybara import Scrapybara; client = Scrapybara(api_key="KEY")
- Instance lifecycle: instance = client.start_ubuntu(timeout_hours=1) instance.pause() # Pause to save resources instance.resume(timeout_hours=1) # Resume work instance.stop() # Terminate and clean up
- Instance types: ubuntu_instance = client.start_ubuntu(): supports bash, computer, edit, browser browser_instance = client.start_browser(): supports computer, browser windows_instance = client.start_windows(): supports computer
TYPE IMPORTS:
- Core types: from scrapybara import Scrapybara
- Instance types: from scrapybara.client import UbuntuInstance, BrowserInstance, WindowsInstance
- Tool types: from scrapybara.tools import Tool, BashTool, ComputerTool, EditTool
- Model types: from scrapybara.anthropic import Anthropic
- Message types: from pydantic import BaseModel from typing import List, Union, Optional, Any
- Error types: from scrapybara.core.api_error import ApiError
CORE INSTANCE OPERATIONS:
- Screenshots: instance.screenshot().base_64_image
- Bash commands: instance.bash(command="ls -la")
- Mouse control: instance.computer(action="move_mouse", coordinates=[x, y])
- Click actions: instance.computer(action="click_mouse", button="right", coordinates=[x, y])
- Drag actions: instance.computer(action="drag_mouse", path=[[x1, y1], [x2, y2]])
- Scroll actions: instance.computer(action="scroll", coordinates=[x, y], delta_x=0, delta_y=0)
- Key actions: instance.computer(action="press_key", keys=[keys])
- Type actions: instance.computer(action="type_text", text="Hello world")
- Wait actions: instance.computer(action="wait", duration=3)
- Get cursor position: instance.computer(action="get_cursor_position").output
- File operations: instance.file.read(path="/path/file"), instance.file.write(path="/path/file", content="data")
ACT SDK (Primary Focus):
- Purpose: Enables building computer use agents with unified tools and model interfaces
- Core components:
- Model: Handles LLM integration (currently Anthropic) from scrapybara.anthropic import Anthropic model = Anthropic() # Or model = Anthropic(api_key="KEY") for own key
- Tools: Interface for computer interactions
- BashTool: Run shell commands
- ComputerTool: Mouse/keyboard control
- EditTool: File operations tools = [ BashTool(instance), ComputerTool(instance), EditTool(instance), ]
- Prompt:
- system: system prompt, recommend to use UBUNTU_SYSTEM_PROMPT, BROWSER_SYSTEM_PROMPT, WINDOWS_SYSTEM_PROMPT
- prompt: simple user prompt
- messages: list of messages
- Only include either prompt or messages, not both response = client.act( model=Anthropic(), tools=tools, system=UBUNTU_SYSTEM_PROMPT, prompt="Task", on_step=handle_step ) messages = response.messages steps = response.steps text = response.text output = response.output usage = response.usage
MESSAGE HANDLING:
- Response Structure: Messages are structured with roles (user/assistant/tool) and typed content
- Content Types:
- TextPart: Simple text content TextPart(type="text", text="content")
- ImagePart: Base64 or URL images ImagePart(type="image", image="base64...", mime_type="image/png")
- ReasoningPart: Model reasoning content ReasoningPart( type="reasoning", id="id", reasoning="reasoning", signature="signature", instructions="instructions" )
- ToolCallPart: Tool invocations ToolCallPart( type="tool-call", tool_call_id="id", tool_name="bash", args={"command": "ls"} )
- ToolResultPart: Tool execution results ToolResultPart( type="tool-result", tool_call_id="id", tool_name="bash", result="output", is_error=False )
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 207 lines · 1,684 tokens per session scan A 579d868b7bca
cursorrules is a cursor rule published in the GitHub repository Scrapybara/scrapybara-python-template (8 stars, last pushed 1y ago), licensed MIT. It adds 1,684 tokens to every session, about $0.0084 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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