Atlas empowers Tauri developers to automate GitHub issue and pull request triage directly within a workflow, ensuring safe, permission-gated responses from trusted users. It integrates direct with your existing Tauri toolchain, leveraging `cargo test` for Rust-side validation, `cargo (with pnpm frontend)` for dependency management, and `rustfmt` for code consistency, all while respecting your project's `src-tauri/capabilities`.
How does Atlas automate GitHub triage for Tauri projects?
Atlas provides a first-class GitHub entrypoint, the `atlas github` command, designed to automate issue and pull request triage for Tauri projects in 2026. This command reads its inputs directly from the GitHub Actions environment, ensuring that critical parameters like the `MODEL` in `provider/model` form are correctly set before any operation begins.
The `atlas github` command is the core of automating triage for your Tauri codebase. It's engineered to operate within a GitHub workflow, consuming environment variables to configure its behavior. For instance, it requires a `MODEL` input, specified as `provider/model` (e.g., `ollama/llama3`), and will refuse to run if this is missing or malformed. Similarly, event types that require a prompt, such as new issues or pull requests, must be supplied with a `PROMPT` input; otherwise, the handler fails with a clear 'PROMPT input is required for <event> events' message. This upfront validation ensures that Atlas only proceeds when all necessary information is present, preventing misconfigurations in your Tauri project's automation.
How does Atlas ensure safety and trust for Tauri workflow automation?
Atlas prioritizes safety and trust in automated workflows for Tauri projects, implementing multiple checks to prevent unauthorized actions. It verifies that the triggering actor possesses `admin` or `write` collaborator permission before executing any tasks, a critical safeguard in 2026 for maintaining project integrity.
To ensure that only trusted users can trigger automated responses in your Tauri repository, Atlas performs stringent permission checks. Before any action, it verifies the triggering actor's collaborator permission, refusing to run if they lack `admin` or `write` access. Furthermore, to prevent accidental or stray comments from initiating a run, the `atlas github` handler enforces that comments must explicitly mention the configured trigger. This 'mention requirement' ensures that automation is only invoked intentionally. Internally, Atlas's permission-gated tool calls, read-only plan agent, and unified diff for every file edit provide additional layers of safety, requiring explicit approval before any changes are written to your Tauri project's `src-tauri` directory or frontend `package.json`.
What Tauri-specific files and commands does Atlas interact with?
Atlas deeply understands the Tauri ecosystem, interacting directly with core project files and commands to provide relevant automation. It recognizes `src-tauri/tauri.conf.json` for application configuration and `frontend package.json` for webview dependencies, ensuring a comprehensive understanding of your project's structure in 2026.
When working with a Tauri project, Atlas is configured to recognize and interact with its specific toolchain and file structure. It identifies `src-tauri/tauri.conf.json` as the central configuration for your Rust core and the `frontend package.json` for managing your webview's dependencies. Atlas can read your `#[tauri::command]` handlers in the Rust code, understand the corresponding `invoke` calls on the JavaScript side, and interpret the permissions defined in `src-tauri/capabilities`. For instance, if you ask Atlas to expose a new command, it will not only draft the Rust and JavaScript code but also wire the matching capability entry, understanding that a missing permission fails silently at runtime. Atlas can also run `cargo test` within the `src-tauri` directory for your Rust tests and execute the frontend test suite, both behind a permission prompt. After making changes, it can run `rustfmt` on the Rust side and `prettier` on the frontend, ensuring code style consistency across your entire Tauri application.
How does Atlas handle context overflow in Tauri issue triage?
Atlas explicitly handles context overflow during issue and pull request triage for Tauri projects, preventing silent failures due to excessive input. It catches a `ContextOverflowError` by name and re-throws it as a user-friendly 'prompt-too-large' message, listing the offending files, a crucial feature for large codebases in 2026.
In complex Tauri projects with extensive codebases or lengthy issue descriptions, the context provided to the AI model can exceed its limits. Atlas is designed to gracefully manage these situations. When a `ContextOverflowError` occurs, Atlas catches it specifically by name. Instead of a cryptic error, it re-throws a clear 'prompt-too-large' message, which includes a list of the files that contributed to the overflow. This explicit handling allows Tauri developers to understand precisely which parts of the codebase or issue content are causing the context to exceed the model's capacity, enabling them to refine their prompts or adjust the scope of the automation effectively. This mechanism ensures transparency and prevents unexpected behavior during automated triage.
Step by step
- 01Configure your GitHub workflow to invoke the `atlas github` command, ensuring the `MODEL` input is set in `provider/model` format (e.g., `ollama/llama3`).
- 02Provide the `PROMPT` input for specific event types that require it, such as new issues or pull requests, to guide Atlas's responses for your Tauri project.
- 03Ensure the GitHub workflow is configured to only trigger for actors with `admin` or `write` collaborator permissions on your Tauri repository.
- 04Require a specific mention in comments or issue bodies to trigger Atlas, preventing unintended runs on your Tauri codebase.
- 05Allow Atlas to read your `src-tauri/tauri.conf.json`, `frontend package.json`, `#[tauri::command]` handlers, and `src-tauri/capabilities` for comprehensive context.
- 06Approve Atlas's proposed changes, including any new `#[tauri::command]` handlers or `src-tauri/capabilities` entries, after reviewing the unified diff.
- 07Permit Atlas to run `cargo test` in `src-tauri` and the frontend test suite, and then `rustfmt` on Rust files and `prettier` on frontend files, all behind a permission prompt.
Frequently asked questions
- How does Atlas integrate with my existing Tauri project structure?
- Atlas integrates by recognizing key Tauri project files like `src-tauri/tauri.conf.json` and `frontend package.json`. It understands `#[tauri::command]` handlers, `invoke` calls, and `src-tauri/capabilities` permissions, allowing it to propose and implement changes that align with your Tauri application's architecture. It can also run `cargo test` and `rustfmt` on the Rust side, and `prettier` on the frontend.
- What specific commands does Atlas use for Tauri code quality?
- For Tauri code quality, Atlas uses `rustfmt` for Rust code within `src-tauri` and `prettier` for the frontend code. It can also execute `cargo test` in `src-tauri` and the frontend's test suite, ensuring that any proposed changes maintain code integrity and pass existing tests, all behind a permission prompt.
- Can Atlas automatically add new `#[tauri::command]` handlers?
- Yes, Atlas can expose new `#[tauri::command]` handlers. When asked, it will draft the necessary Rust code, wire the corresponding `invoke` calls on the JavaScript side, and crucially, add the matching capability entry in `src-tauri/capabilities`. This ensures the new command functions correctly at runtime, as missing permissions would otherwise fail silently.
- How does Atlas prevent unauthorized automation in my Tauri repository?
- Atlas prevents unauthorized automation by enforcing strict security measures. It checks that the triggering GitHub actor has `admin` or `write` collaborator permission. Additionally, it requires a specific mention in comments or issue bodies to activate, ensuring that automated runs are always intentional and from trusted sources within your Tauri project.
- What happens if a GitHub issue is too long for Atlas to process in Tauri?
- If a GitHub issue or pull request is too long, causing the context to exceed the model's capacity, Atlas will catch a `ContextOverflowError`. It then re-throws a clear 'prompt-too-large' message, explicitly listing the files or sections that contributed to the overflow. This allows you to understand and address the context limitations for your Tauri project's automation.
- Does Atlas support local embeddings for Tauri code indexing?
- Yes, Atlas supports building its code index with local Ollama embeddings. This capability is crucial for Tauri developers who prioritize data privacy, as it keeps your sensitive code off third-party servers. Atlas indexes code by AST declarations using tree-sitter, providing precise context for your Rust and frontend code.
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