default

A set of development rules for a BigQuery MCP project. BigQuery is Google Cloud's service for storing and querying large datasets, while MCP connects assistants to tools and data.

In plain words
What is it for?
It is for writing, checking, testing, documenting, and releasing changes in a Python BigQuery MCP project.
Why use it?
It gives contributors consistent guidance for code quality, versioning, formatting, documentation, and testing.

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/aicayzer/bigquery-mcp/default
Clone the repo
git clone --depth 1 https://github.com/aicayzer/bigquery-mcp

Made for: Cursor.

Per session 361 This file is loaded in full into every session.
When invoked 361 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 $0.00361 $0.00361
Opus 5 $0.00180 $0.00180
Sonnet 5 $0.00072 $0.00072
Haiku 4.5 $0.00036 $0.00036

Measured yesterday against content hash 2841cccb6c13, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

default 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/default.mdc · 54 lines

What it actually says

BigQuery MCP Development Standards

Code Quality

  • Write clean, efficient, minimal code
  • No unnecessary complexity or over-engineering
  • Follow existing patterns and conventions
  • Use descriptive variable names, avoid abbreviations

Version Control

  • Update version numbers consistently across all files when making releases
  • Use semantic versioning (MAJOR.MINOR.PATCH)
  • Keep commits focused and atomic
  • Write clear, concise commit messages

Code Standards

  • Run ruff format before committing
  • Run ruff check --fix to resolve linting issues
  • Add type hints for function parameters and returns
  • Include docstrings for public functions and classes

Testing

  • Add tests for new functionality
  • Run pytest before committing
  • Ensure all tests pass in CI

Documentation

  • Keep documentation minimal and focused
  • Update relevant docs when changing functionality
  • Use clear, direct language - no fluff or emojis
  • Focus on what users need to know, not implementation details

Changelog Formatting

  • Use clean, elegant formatting without bold text
  • Write concise, descriptive entries
  • No unnecessary formatting or emphasis
  • Keep entries focused on what actually changed

Architecture

  • Prefer command-line arguments over config files
  • Keep dependencies minimal
  • Follow MCP protocol standards
  • Maintain backwards compatibility when possible

Error Handling

  • Use custom exception classes for specific error types
  • Provide actionable error messages
  • Log errors appropriately for debugging

User Preferences

  • Avoid over-engineering and unnecessary complexity
  • Don't overthink security implementations unless specifically requested
  • Focus on what's needed, not what could be possible
  • Maintain high repository standards suitable for GitHub
  • Keep configuration clean with proper .example files and gitignored personal configs
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 · 54 lines · 361 tokens per session scan A 2841cccb6c13

Subscribe to this mod's changes

default is a cursor rule published in the GitHub repository aicayzer/bigquery-mcp (2 stars, last pushed 1y ago), licensed MIT. It adds 361 tokens to every session, about $0.0018 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.