sqlglot AGENTS.md

Project instructions for contributing to SQLGlot, a Python library that parses, converts, optimizes, and runs SQL across different SQL dialects.

In plain words
What is it for?
Use them when setting up SQLGlot, installing its optional compiled extension, running all or selected tests, or preparing a contribution.
Why use it?
They give contributors the repository’s installation, build, testing, and contribution commands so changes can be checked consistently.

Instructions file for CodexOpenCode

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 instructions/tobymao/sqlglot/agents-md
Clone the repo
git clone --depth 1 https://github.com/tobymao/sqlglot

Made for: Codex, OpenCode.

Per session 4,258 This file is loaded in full into every session.
When invoked 4,258 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 $0.04258 $0.04258
Opus 5 $0.02129 $0.02129
Sonnet 5 $0.00852 $0.00852
Haiku 4.5 $0.00426 $0.00426

Measured 2d ago against content hash dace0d5e531b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sqlglot AGENTS.md 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.

AGENTS.md · 522 lines

How it starts

The opening of the file, as written. The whole thing — 522 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Contributing to SQLGlot

About SQLGlot

SQLGlot is a no-dependency SQL parser, transpiler, optimizer, and engine written in pure Python. It supports 31+ SQL dialects and can transpile between them while preserving semantics. The codebase is performance-critical despite being pure Python, with an optional mypyc-compiled C extension for speed improvements (sqlglotc/).

Development Commands

Before contributing read CONTRIBUTING.md

Installation

# Basic installation
make install

# Development installation (Python only, no C extension)
make install-dev

# Development installation with mypyc C extension
make install-devc

# Install pre-commit hooks
make install-pre-commit

# With uv (faster):
UV=1 make install-dev

Testing

# Run all tests (pure Python, hides .so files during run)
make test

# Run all tests with mypyc C extension (builds extension first)
make testc

# Run only unit tests (skip integration tests, pure Python)
make unit

# Run only unit tests with C extension
make unitc

# Run specific test file
python -m unittest tests.test_expressions

# Run specific test class
python -m unittest tests.test_expressions.TestExpressions

# Run specific test method
python -m unittest tests.test_expressions.TestExpressions.test_alias

Linting & Type Checking

# Run linter and formatter only
make style

# Run full checks (style + pure Python tests + C extension tests)
make check

Benchmarks

# Run parsing benchmark
make bench

# Run optimization benchmark
make bench-optimize

Architecture Overview

SQLGlot follows a classic compiler architecture with three main phases:

1. Tokenizer (tokens.py)

  • Converts SQL strings into a sequence of tokens (lexical analysis)
  • Pure Python implementation in tokens.py; core logic in tokenizer_core.py (mypyc-compiled when using [c] extra)
  • Maps lexemes to TokenType enum values via KEYWORDS and SINGLE_TOKENS dictionaries
  • Dialects can override tokenizer behavior by customizing these mappings

Read the full file on GitHub · 522 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 · 522 lines · 4,258 tokens per session scan A dace0d5e531b

Subscribe to this mod's changes

sqlglot AGENTS.md is an instructions file published in the GitHub repository tobymao/sqlglot (9,579 stars, last pushed 4d ago), licensed MIT. It adds 4,258 tokens to every session, about $0.0213 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.