project-guidelines

Project rules for an AI-agent playground that creates scripts and workflows for tasks such as web automation, bookings, research, and administration.

In plain words
What is it for?
Guiding multi-step agent projects, deciding when to write Python or TypeScript, using web-search tools, and streaming script results.
Why use it?
They give agents a common process for planning work, choosing tools, handling web data, and communicating through command-line input and output.

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/maccman/agent-playground/project-guidelines
Clone the repo
git clone --depth 1 https://github.com/maccman/agent-playground

Made for: Cursor.

Per session 677 This file is loaded in full into every session.
When invoked 677 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 $0.00677 $0.00677
Opus 5 $0.00338 $0.00338
Sonnet 5 $0.00135 $0.00135
Haiku 4.5 $0.00068 $0.00068

Measured yesterday against content hash 6f80c5740c3d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

project-guidelines 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.

.cursor/rules/project-guidelines.mdc · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Playground - Project Guidelines

Project Overview

This is an AI agent playground for generating autonomous scripts and workflows. All agents are designed to perform complex, multi-step tasks including web automation, bookings, data research, and administrative functions.

Agent Development Process

  1. Planning First: Always come up with a good plan before executing any task
  2. Write and run typescript or python code: Write and run typescript/python code to test your ideas. For anything that is best done programmatically, like math or other types of logic, then just write a quick TypeScript/python program and run it.
  3. ALWAYS prefer running executables vs writing scripts: Running executables is faster than writing scripts.
  4. Data from the web: Use the web_search and mcp_browsermcp tools to get data from the web. Never use the mcp_browsermcp tool to Google search - you should use the dedicated web_search tool for that as it's more reliable.
  5. Use unix principles: Use unix principles to build your scripts. Use stdin and stdout. Use | to chain commands together.
  6. Stream output: Stream output to the console. e.g. when processing CSVs, output line by line.
  7. Never alter a file in the data/ directory in-place: Always either produce a copy or, if you're editing textual data, use stdin and stdout to edit the data.

AI SDK

To communicate with AI providers, use the Vercel AI SDK.

  • Use Vercel AI SDK: Use the AI SDK directly with providers like @ai-sdk/openai, @ai-sdk/anthropic, @ai-sdk/google
  • No Custom Abstractions: Don't create custom AI client wrappers - use the SDK directly
  • Environment variables for AI providers are automatically handled by Vercel AI SDK
  • No need to manually check or validate API keys in code
  • Standard variables: OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_GENERATIVE_AI_API_KEY

Project Structure

  • lib/ - Reusable utilities and shared code
  • scripts/ - Runnable task scripts (use tsx for execution)
  • types/ - Shared TypeScript type definitions
  • data/ - Storage for data files (Markdown and CSV)

Read the full file on GitHub · 59 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. yesterday First seen · 59 lines · 677 tokens per session scan A 6f80c5740c3d

Subscribe to this mod's changes

project-guidelines is a cursor rule published in the GitHub repository maccman/agent-playground (2 stars, last pushed 6mo ago), licensed MIT. It adds 677 tokens to every session, about $0.0034 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.