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vsceasy is a scaffolding CLI and small framework—not an extension itself. Two projects described by creator Jairo Fernández show how it can support different VS Code extension types: Code Trainer uses an interactive React webview and editor integration, while a TOML project uses language-support assets such as a grammar, configuration, and snippets. The examples illustrate different uses for the tool, rather than competing extensions.
What vsceasy provides
Fernández describes vsceasy as a way to scaffold VS Code extension projects. Its documented project types are ui, language, and empty. A UI scaffold includes a React webview, a typed RPC bridge for communication between the extension host and webview, and file-based registration for elements such as panels, commands, menus, and tree views. A language scaffold supplies a different foundation: a grammar, language configuration, snippets, and an optional file-icon theme. The package documentation lists these capabilities; it does not independently verify the behavior of the two projects Fernández showcases.
The UI example’s layout includes an extension entry point, a command, a panel, a shared API contract, and a React interface. The creator’s article gives bunx @vsceasy/cli create my-extension as a UI scaffold command. For setup, that article describes installing dependencies and launching with bun run launch. The npm documentation presents a separate quick-start workflow using bun run dev, followed by F5 to open the Extension Development Host. These are distinct documented workflows, not interchangeable steps in one combined procedure.
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Code Trainer is presented as an algorithm-practice extension built around typing solutions, rather than simply reading or pasting them. Its features span VS Code’s sidebar, a webview, commands, and the editor itself.
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Problems, learning material, and practice setup
- A sidebar tree view groups problems by interview pattern and displays progress.
- A React Learn panel presents problem statements and theory, using VS Code theme tokens for its styling.
- Commands and quick picks let users choose a programming language and practice mode.
Typing practice and feedback
In its editor typing mode, a reference solution appears as ghost text. A typing guard blocks incorrect characters, while live words-per-minute and accuracy feedback show how the session is going. This is the example’s defining editor interaction: it turns the editor into a guided typing exercise rather than only a place to inspect the answer.
Exercise checks and session features
Fernández says generated exercises go into a scratch directory and are checked against two solutions: the reference solution must pass, and the starter solution must fail. Other outcomes are rejected and the exercise is regenerated. This is the creator’s account of the validation design, not an independently reproduced result.
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The article’s captured terminal shows bun test with three passing tests. That count is a single project demonstration reported by the creator; it should not be read as an independently audited benchmark or a general measure of test coverage.
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The creator also describes using a local Ollama model to write a session summary. Sessions, streaks, and weak topics are stored as ORM entities. A coaching chat shares conversation history between the panel and sidebar through typed RPC events, illustrating how the UI scaffold’s bridge can keep separate extension surfaces in sync.
How the TOML example uses the language scaffold
The TOML project demonstrates language support rather than the React UI path. Its described components include a TextMate grammar and language configuration for .toml files and related files such as Cargo.lock, poetry.lock, and Pipfile. It also includes snippets named table, kvstr, and inline, as well as scoped token colors.
An optional file-icon theme is included, but the example leaves activation to the user. As Fernández notes, activating an icon theme affects file icons across the workbench, so making it opt-in avoids changing that broader presentation without the user’s choice. The creator says vsceasy doctor checks that grammar, snippet, and icon files referenced in the package configuration exist before packaging.
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How the two extension types differ
| Aspect | Code Trainer | TOML support |
|---|---|---|
| Purpose | Algorithm practice through an interactive UI and editor integration | Editing support for TOML and related files |
| Core implementation | React webview, extension features, and typed RPC | Language-support assets: grammar, configuration, snippets, and optional icons |
| React webview and RPC | Part of the described UI architecture | Not part of the described language-support approach |
The distinction is architectural, not a ranking. Code Trainer shows how a UI scaffold can connect a webview to VS Code commands, views, and editor behavior; the TOML project shows how a language scaffold can organize editor support without building a React interface or RPC layer.
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Fernández’s DEV Community article, posted September 27, 2026, is the source for the projects’ reported behavior and demonstration details. The @vsceasy/cli npm documentation separately describes the package’s project types, scaffolding, and setup. The package documentation corroborates what the tool offers, but it is not independent validation of Code Trainer’s or the TOML project’s reported behavior. The demonstrations and local-model behavior remain creator-reported.
The title-specific article calls its algorithm-practice showcase “Code Trainer.” A GitHub profile search result describes a related project as “Code Coach,” but the available evidence does not establish that the names refer to identical releases.
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