VS Code の TOML用拡張機能の「Tombi」についてのメモ VS Code の TOML用拡張機能の「Tombi」についてのメモ

TOML has quietly become one of the most widely used configuration formats in modern software development, appearing in everything from Rust's Cargo.toml and Python's pyproject.toml to numerous CI, linter, and tooling configuration files. Because so much project setup now lives in TOML files, editor support for the format matters more than it once did. Tombi is a Visual Studio Code extension, distributed through the Visual Studio Marketplace, that aims to improve the experience of writing and maintaining TOML files inside the editor.

At a high level, Tombi appears to position itself as a TOML toolchain rather than a single-purpose helper. Extensions in this category typically bundle a set of related capabilities: syntax highlighting so that keys, values, tables, and arrays are visually distinct; a formatter that normalizes spacing, indentation, and alignment according to consistent rules; and validation that flags syntax errors or structural problems before a file is committed or consumed by a build tool. The value of this kind of tooling is that configuration mistakes, which can be easy to overlook in plain text, are surfaced directly in the editor as you type.

A useful piece of background here is the Language Server Protocol, or LSP, which underpins many modern editor extensions. Rather than reimplementing language intelligence separately for every editor, an LSP-based tool runs a language server that handles parsing, diagnostics, completion, and formatting, while the editor acts as a client. Tombi is likely built around this model, which would allow its core logic to be reused beyond VS Code in other LSP-compatible editors. This architecture has become the standard approach for language tooling and is part of why high-quality support for niche formats like TOML has improved over recent years.

One of the more practical features to look for in a TOML extension is schema-aware editing. Many TOML files follow a known structure, and that structure can be described using JSON Schema. When an extension is connected to the right schema, it can offer context-sensitive autocompletion for keys, show inline documentation, and warn when a value has the wrong type or an unexpected field is present. Community resources such as SchemaStore collect schemas for common configuration files, and tools that integrate with them can validate files like pyproject.toml against published specifications. It is reasonable to expect a TOML-focused extension to support some form of schema-based assistance, though the exact scope and configuration options should be confirmed in its documentation.

It is worth placing Tombi in the context of the existing ecosystem. The most established option in this space has been Even Better TOML, which is widely installed and built on top of the Taplo toolchain. Taplo provides a TOML parser, formatter, and language server, and is also usable as a standalone command-line tool. Because that combination is already popular, a newer entrant such as Tombi is entering a field with mature alternatives, and prospective users may want to compare formatting behavior, schema support, performance, and configurability before switching or adopting it for a team. Differences in default formatting rules, in particular, can matter when multiple developers share the same repository, since inconsistent formatters can produce noisy diffs.

For anyone evaluating the extension, a few standard checks apply. Reviewing the Marketplace listing for the publisher, version history, install count, and update cadence gives a sense of maturity and maintenance. Looking at the linked source repository, if one is available, helps clarify which features are implemented, what license applies, and how actively issues are addressed. It is also sensible to test the extension on a representative TOML file and confirm how it interacts with any formatter or linter settings already configured in the workspace, so that two tools do not compete to reformat the same file.

In short, Tombi reflects a broader trend of dedicated, increasingly capable tooling for configuration languages that were once treated as an afterthought. The original note that inspired this overview is brief and exploratory, framed as a memo from someone searching for a TOML extension, so readers should treat specific capabilities as items to verify against the official listing rather than settled facts. As TOML continues to spread across language ecosystems, having reliable editor support that catches errors early and keeps files consistently formatted is a modest but genuine productivity benefit.