Tobymao/SQLGlot is a Python library that parses SQL, converts it between more than 30 SQL dialects, formats queries, and can optimize or execute them. It is used by developers who need to analyze, generate, validate, or translate SQL programmatically. The catalogue instructions provide workflows for using SQLGlot.
Borrowing it
Nothing to install: this file belongs to tobymao/sqlglot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tobymao/sqlglot/main/AGENTS.mdgit clone --depth 1 https://github.com/tobymao/sqlglotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/tobymao/sqlglot/agents-md)<a href="https://agentmods.dev/instructions/tobymao/sqlglot/agents-md"><img src="https://agentmods.dev/badge/instructions/tobymao/sqlglot/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/tobymao/sqlglot/agents-md"><img src="https://agentmods.dev/badge/instructions/tobymao/sqlglot/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.04258 | $0.04258 |
| Opus 5.5 | $0.01703 | $0.01703 |
| Sonnet 5.5 | $0.00852 | $0.00852 |
| Haiku 4.5 | $0.00426 | $0.00426 |
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 2mo 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.
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 intokenizer_core.py(mypyc-compiled when using[c]extra) - Maps lexemes to
TokenTypeenum values viaKEYWORDSandSINGLE_TOKENSdictionaries - Dialects can override tokenizer behavior by customizing these mappings
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.
- 2mo ago First seen · 522 lines · 4,258 tokens per session scan A dace0d5e531b
sqlglot AGENTS.md is an instructions file published in the GitHub repository tobymao/sqlglot (9,764 stars, last pushed today), licensed MIT. It adds 4,258 tokens to every session, about $0.0170 per session on Opus 5.5. 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.
sqlglot AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| sqlglot AGENTS.mdtobymao/sqlglot | Instructions file | 9.8k | today | MIT | A | 4,258 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |