cursorrules

A usage guide for Scrapybara, a TypeScript toolkit for starting and controlling remote computer environments for AI agents.

In plain words
What is it for?
Use it when writing code that starts, pauses, resumes, or stops Ubuntu, browser, or Windows environments and uses their tools.
Why use it?
It gives the coding agent the correct setup, types, and commands for working with the toolkit.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/scrapybara/scrapybara-ts-template/cursorrules
Clone the repo
git clone --depth 1 https://github.com/Scrapybara/scrapybara-ts-template

Made for: Cursor.

Per session 1,857 This file is loaded in full into every session.
When invoked 1,857 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5 $0.01857 $0.01857
Opus 5 $0.00928 $0.00928
Sonnet 5 $0.00371 $0.00371
Haiku 4.5 $0.00186 $0.00186

Measured 2d ago against content hash d887bc1966bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d ago.

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.

.cursorrules · 204 lines

How it starts

The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are working with Scrapybara, a TypeScript 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: import { ScrapybaraClient } from "scrapybara"; const client = new ScrapybaraClient({ apiKey: "KEY" });
  • Instance lifecycle: const instance = await client.startUbuntu({ timeoutHours: 1 }); await instance.pause(); // Pause to save resources await instance.resume({ timeoutHours: 1 }); // Resume work await instance.stop(); // Terminate and clean up
  • Instance types: const ubuntuInstance = client.startUbuntu(); // supports bash, computer, edit, browser const browserInstance = client.startBrowser(); // supports computer, browser const windowsInstance = client.startWindows(); // supports computer

TYPE IMPORTS:

  • Core types: import { ScrapybaraClient, UbuntuInstance, BrowserInstance, WindowsInstance } from "scrapybara";
  • Tool types: import { bashTool, computerTool, editTool } from "scrapybara/tools";
  • Model types: import { anthropic } from "scrapybara/anthropic";
  • Message types: import { z } from "zod";
  • Error types: import { ScrapybaraError } from "scrapybara";
  • Request/Response types: import { Scrapybara } from "scrapybara"; // Namespace containing all request/response types

CORE INSTANCE OPERATIONS:

  • Screenshots: const base64Image = await instance.screenshot().base64Image;
  • Bash commands: await instance.bash({ command: "ls -la" });
  • Mouse control: await instance.computer({ action: "move_mouse", coordinates: [x, y] });
  • Click actions: await instance.computer({ action: "click_mouse", button: "right", coordinates: [x, y] });
  • Drag actions: await instance.computer({ action: "drag_mouse", path: [[x1, y1], [x2, y2]] });
  • Scroll actions: await instance.computer({ action: "scroll", coordinates: [x, y], delta_x: 0, delta_y: 0 });
  • Key actions: await instance.computer({ action: "press_key", keys: ["a", "b", "c"] });
  • Type actions: await instance.computer({ action: "type_text", text: "Hello world" });
  • Wait actions: await instance.computer({ action: "wait", duration: 3 });
  • Get cursor position: await instance.computer({ action: "get_cursor_position" });
  • File operations: await instance.file.read({ path: "/path/file" }), await 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:
  1. Model: Handles LLM integration (currently Anthropic) import { anthropic } from "scrapybara/anthropic"; const model = anthropic(); // Or model = anthropic({ apiKey: "KEY" }) for own key
  2. Tools: Interface for computer interactions
    • bashTool: Run shell commands
    • computerTool: Mouse/keyboard control
    • editTool: File operations const tools = [ bashTool(instance), computerTool(instance), editTool(instance), ];
  3. 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 const { messages, steps, text, output, usage } = await client.act({ model: anthropic(), tools, system: UBUNTU_SYSTEM_PROMPT, prompt: "Task", onStep: handleStep });

MESSAGE HANDLING:

  • Response Structure: Messages are structured with roles (user/assistant/tool) and typed content
  • Content Types:
  • TextPart: Simple text content { type: "text", text: "content" }
  • ImagePart: Base64 or URL images { type: "image", image: "base64...", mimeType: "image/png" }
  • ReasoningPart: Model reasoning content { type: "reasoning", id: "id", reasoning: "reasoning", signature: "signature", instructions: "instructions" }
  • ToolCallPart: Tool invocations { type: "tool-call", toolCallId: "id", toolName: "bash", args: { command: "ls" } }
  • ToolResultPart: Tool execution results { type: "tool-result", toolCallId: "id", toolName: "bash", result: "output", isError: false }

Read the full file on GitHub · 204 lines

Changes

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.

  1. 2d ago First seen · 204 lines · 1,857 tokens per session scan A d887bc1966bf

Subscribe to this mod's changes

cursorrules is a cursor rule published in the GitHub repository Scrapybara/scrapybara-ts-template (11 stars, last pushed 1y ago), licensed MIT. It adds 1,857 tokens to every session, about $0.0093 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 2026-08-30.