Metabob: Debug and Refactor with AI

Detects logical bugs, vulnerabilities, and code quality issues using a proprietary Graph Neural Network (GNN) model that analyzes code structure as a computational graph rather than text. The GNN operates on Abstract Syntax Trees (ASTs) to identify structural patterns associated with problems, enabling detection of issues that regex or token-based approaches miss. Analysis is triggered automatically on file save and results are cached until the next modification.

Generates human-readable explanations for detected code problems using a configurable Large Language Model backend (default unknown, OpenAI ChatGPT optional). The extension sends detected problem context and code snippets to the LLM, which generates explanations of why the problem matters and how it could impact the code. Backend selection is configurable via VS Code settings, allowing users to choose between Metabob's default model or OpenAI's ChatGPT with API key authentication.

Generates suggested code fixes for detected problems using the configured LLM backend, presenting recommendations inline in the VS Code editor. The LLM receives the problem description, code context, and file language, then generates a corrected code snippet that addresses the issue. Users can preview, accept, or reject recommendations, with acceptance triggering code replacement in the editor.

Automatically runs the GNN problem detection model whenever a Python/JavaScript/TypeScript/C/C++/Java file is saved in VS Code, with analysis enabled by default via the 'Analyze Document On Save' setting. The extension hooks into VS Code's file save event, queues the current file for analysis, and displays results as diagnostic markers in the editor. Analysis can be toggled on/off per workspace via VS Code settings.

Allows developers to endorse or discard detected problems, sending feedback signals back to Metabob's GNN model to improve detection accuracy over time. When a user marks a detection as 'correct' or 'incorrect', the extension logs this feedback (along with the problem context and code) and uses it to retrain or fine-tune the proprietary GNN model. This creates a continuous learning loop where the model improves as more developers use the extension.

Detects problems across six programming languages (Python, JavaScript, TypeScript, C, C++, Java) using a single GNN model trained on multi-language code patterns. The extension automatically detects the file language via VS Code's language mode, routes the code to the appropriate analysis pipeline, and returns language-specific problem categories (e.g., null pointer dereferences in C/C++, type errors in TypeScript). Problem types and severity levels are tailored to each language's common pitfalls.

Allows users to select which Large Language Model powers explanation and fix generation through VS Code settings, with built-in support for OpenAI's ChatGPT models via API key authentication. The extension provides a dropdown menu in settings to choose between Metabob's default LLM backend and OpenAI ChatGPT, with a separate text field for entering OpenAI API keys. The selected backend is used for all explanation and fix generation requests, enabling users to leverage their own OpenAI accounts or API budgets.

Implements a data privacy model where code sent to Metabob's proprietary GNN model for problem detection is automatically deleted after 1 hour, preventing long-term data retention. The extension sends code snippets to Metabob's servers for GNN inference, but the company commits to deleting this data within 1 hour of the last API call. This differs from third-party LLM backends (OpenAI), where data retention is governed by the provider's separate privacy policy.

Integrates detected problems into VS Code's native Problems panel and inline editor diagnostics, displaying issues with severity levels (error/warning/info assumed) and clickable navigation. The extension registers diagnostics with VS Code's diagnostic API, which automatically populates the Problems panel, adds squiggly underlines in the editor, and enables keyboard navigation between issues. Problem details include the issue description, suggested fix, and explanation from the configured LLM backend.

Offers a freemium pricing structure where basic problem detection and explanations are available for free, with premium features (likely advanced fix generation, priority support, or higher API quotas) available through paid subscription. The free tier includes GNN-based problem detection and LLM-powered explanations using Metabob's default backend, while premium tiers likely unlock OpenAI ChatGPT integration, higher analysis quotas, or team features. Pricing details are not publicly documented in the marketplace listing.