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The extension acts as a VS Code client that marshals the active editor's buffer content to the containerized model service and inserts the generated completion at the cursor position. This explicit-trigger model avoids continuous background inference overhead but requires manual activation for each completion request.","intents":["I want to generate code suggestions without the latency of cloud API calls","I need code completion that runs entirely on my local machine for privacy","I want to trigger completions manually rather than having them appear automatically"],"best_for":["developers prioritizing privacy and offline-first workflows","teams with strict data residency requirements","users with unreliable internet connectivity"],"limitations":["Requires manual keyboard invocation for each completion — no inline/continuous suggestions like GitHub Copilot","Docker container must be running and accessible before extension can function; no graceful fallback if container unavailable","Completion scope (line-level vs block-level vs function-level) undocumented; unclear what context window the model uses","No configurable model selection or inference parameters exposed in UI","Latency unknown but likely includes Docker network round-trip overhead (potentially 100-500ms per request)"],"requires":["Visual Studio Code (version requirement unknown)","Docker installed and running","Docker image vishnoiaman777/openvino:latest pulled and running as a service","Network connectivity between VS Code extension and Docker container (localhost or configured endpoint)"],"input_types":["source code (current file buffer)","cursor position (implicit from editor state)"],"output_types":["generated code text (inserted at cursor or offered for selection)"],"categories":["code-generation-editing","local-inference"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-amanvishnoi777-xcode__cap_1","uri":"capability://code.generation.editing.local.openvino.model.inference.execution","name":"local openvino model inference execution","description":"Executes code completion inference using OpenVINO (Intel's open-source inference optimization framework) running inside a Docker container. The extension delegates all model computation to this containerized service rather than embedding the model in the extension itself. This architecture isolates the inference engine from VS Code's process, allowing independent model updates and preventing extension bloat, but introduces a network service dependency and undocumented model architecture.","intents":["I want to run AI code completion without sending code to external cloud services","I need inference to happen on my hardware without cloud vendor lock-in","I want to update or swap the underlying model without reinstalling the extension"],"best_for":["enterprise teams with data governance policies prohibiting cloud code transmission","developers in regions with poor cloud service availability","organizations wanting to self-host and control model versions"],"limitations":["Model architecture, size, and training data completely undocumented — impossible to assess quality or suitability for specific languages","No mechanism to swap or configure alternative models documented","Docker image is a black box — no visibility into what model weights or inference optimizations are included","OpenVINO framework adds compilation/optimization overhead at container startup","Performance characteristics (latency, throughput, memory usage) unknown and likely variable based on host hardware"],"requires":["Docker runtime (any recent version supporting standard container images)","Docker image vishnoiaman777/openvino:latest accessible from Docker Hub or pre-pulled","Sufficient host machine resources to run containerized inference (CPU/RAM requirements unknown)","Port/network accessibility between VS Code extension and Docker container"],"input_types":["source code text","file type/language context (inferred from VS Code)"],"output_types":["generated code tokens/text"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-amanvishnoi777-xcode__cap_2","uri":"capability://code.generation.editing.vs.code.editor.context.marshaling","name":"vs code editor context marshaling","description":"Captures the current editor state (active file buffer, cursor position, file type) and marshals this context to the Docker-based inference service for code completion. The extension integrates with VS Code's editor API to access the current document content and cursor location, then packages this as input to the completion model. The mechanism for determining context window size (how much surrounding code is sent) and handling multi-file context is undocumented.","intents":["I want completions that understand the code I'm currently editing","I need the completion engine to know my cursor position and file type","I want completions based on my immediate editing context, not just global patterns"],"best_for":["developers editing single files with local context requirements","users who don't need cross-file or project-wide context awareness"],"limitations":["Context window size unknown — unclear if extension sends entire file, visible viewport, or fixed token window","No documented support for multi-file context or project structure awareness","No indication of whether open tabs, imports, or dependency information is included in context","File type detection mechanism undocumented — unclear which languages are supported","No configurable context size or filtering options exposed to user"],"requires":["Active editor with open file in VS Code","File must be readable by VS Code extension (standard text files)","Docker service running and accessible to receive context payload"],"input_types":["source code buffer (current file)","cursor position (line and column)","file extension/language identifier"],"output_types":["context payload sent to inference service (format unknown)"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-amanvishnoi777-xcode__cap_3","uri":"capability://code.generation.editing.completion.insertion.and.editor.mutation","name":"completion insertion and editor mutation","description":"Inserts generated code completions into the VS Code editor at the cursor position. The extension receives generated text from the Docker inference service and applies it to the active document, either replacing selected text, appending after the cursor, or presenting options for user selection. The exact insertion strategy (replace vs append vs menu) and handling of multi-line completions is undocumented.","intents":["I want generated code inserted directly into my editor without manual copy-paste","I need completions to respect my current selection or cursor position","I want to accept or reject completions before they're committed to the file"],"best_for":["developers who want seamless completion insertion without extra steps","users editing files that support undo/redo for easy reversal"],"limitations":["Insertion strategy undocumented — unclear if it replaces selection, appends, or offers menu","No documented preview or accept/reject workflow — completions may be inserted immediately without confirmation","Multi-line completion handling unknown — unclear how indentation, formatting, or syntax is preserved","No configurable insertion behavior (e.g., always append vs always replace)","Undo behavior depends on VS Code's undo stack — no explicit transaction management documented"],"requires":["Active editor with writable file","File must support text insertion (not binary or read-only)","VS Code must have focus and the extension must be active"],"input_types":["generated code text from inference service","cursor position and selection state"],"output_types":["modified document buffer in VS Code editor"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-amanvishnoi777-xcode__cap_4","uri":"capability://automation.workflow.docker.container.lifecycle.management","name":"docker container lifecycle management","description":"Manages the connection to and execution of the external Docker container running the OpenVINO inference service. The extension must locate, connect to, and communicate with the running Docker image (vishnoiaman777/openvino:latest). The mechanism for container discovery (hardcoded localhost:port, environment variable, or auto-detection) and error handling if the container is unavailable or unresponsive is completely undocumented.","intents":["I want the extension to automatically find and connect to my running Docker container","I need the extension to handle cases where the Docker container is not running","I want to configure which Docker container endpoint the extension connects to"],"best_for":["developers comfortable with Docker and container management","teams with existing Docker infrastructure and container orchestration"],"limitations":["Container discovery mechanism undocumented — unclear if extension expects container on localhost:5000, localhost:8000, or another endpoint","No error handling documented for when Docker container is unavailable, crashed, or unresponsive","No health check or connection retry logic documented","No configuration UI or settings file documented for specifying container endpoint","Container must be manually started before extension can function — no automatic container launch from extension","No documentation on Docker image versioning or update strategy"],"requires":["Docker installed and running on host machine","Docker image vishnoiaman777/openvino:latest pulled from Docker Hub","Container instance running and listening on expected port/endpoint","Network connectivity between VS Code process and Docker container"],"input_types":["container endpoint configuration (if configurable)","inference requests from extension"],"output_types":["inference responses from container","connection status/health signals"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":38,"verified":false,"data_access_risk":"high","permissions":["Visual Studio Code (version requirement unknown)","Docker installed and running","Docker image vishnoiaman777/openvino:latest pulled and running as a service","Network connectivity between VS Code extension and Docker container (localhost or configured endpoint)","Docker runtime (any recent version supporting standard container images)","Docker image vishnoiaman777/openvino:latest accessible from Docker Hub or pre-pulled","Sufficient host machine resources to run containerized inference (CPU/RAM requirements unknown)","Port/network accessibility between VS Code extension and Docker container","Active editor with open file in VS Code","File must be readable by VS Code extension (standard text files)"],"failure_modes":["Requires manual keyboard invocation for each completion — no inline/continuous suggestions like GitHub Copilot","Docker container must be running and accessible before extension can function; no graceful fallback if container unavailable","Completion scope (line-level vs block-level vs function-level) undocumented; unclear what context window the model uses","No configurable model selection or inference parameters exposed in UI","Latency unknown but likely includes Docker network round-trip overhead (potentially 100-500ms per request)","Model architecture, size, and training data completely undocumented — impossible to assess quality or suitability for specific languages","No mechanism to swap or configure alternative models documented","Docker image is a black box — no visibility into what model weights or inference optimizations are included","OpenVINO framework adds compilation/optimization overhead at container startup","Performance characteristics (latency, throughput, memory usage) unknown and likely variable based on host hardware","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.45,"quality":0.2,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.9,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.118Z","last_scraped_at":"2026-05-03T15:20:42.146Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=xcode","compare_url":"https://unfragile.ai/compare?artifact=xcode"}},"signature":"iIUK7d3R+cgDwvHPzK4lYKgQb6/d8b/8dMVZJllxxVMTJyTQrgHiEfkSt8R3OGnbgFZ+lzi/zq/rzX6WL7obDQ==","signedAt":"2026-06-17T04:40:30.053Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/xcode","artifact":"https://unfragile.ai/xcode","verify":"https://unfragile.ai/api/v1/verify?slug=xcode","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}