{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp","slug":"intellicode-for-c-dev-kit","name":"IntelliCode for C# Dev Kit","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.vscodeintellicode-csharp","page_url":"https://unfragile.ai/intellicode-for-c-dev-kit","categories":["code-editors"],"tags":["c#","csharp"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp__cap_0","uri":"capability://code.generation.editing.semantic.aware.intellisense.member.ranking.with.deep.learning","name":"semantic-aware intellisense member ranking with deep learning","description":"Ranks C# methods, properties, and overloads in VS Code's native IntelliSense dropdown using a deep learning model that analyzes semantic context from the current file, project, and solution scope. The model learns patterns from both standard library members and custom codebase-specific methods, reordering suggestions by relevance rather than alphabetical order and marking top suggestions with star indicators. Integration occurs at the IntelliSense list rendering layer, preserving VS Code's native UI while injecting AI-computed ranking scores.","intents":["I want the most relevant method overload to appear first in autocomplete instead of cycling through alphabetically","I need IntelliSense to understand my codebase patterns and suggest my custom helper methods before standard library alternatives","I want visual indicators (stars) showing which IntelliSense suggestions are most contextually appropriate"],"best_for":["C# developers working in VS Code with solution-based projects","teams with large custom codebases where standard library suggestions are less relevant than internal APIs","developers seeking faster method discovery without manual IntelliSense list navigation"],"limitations":["Requires C# files to be part of a solution context—standalone .cs files receive no ranking functionality","Model architecture and training data are undisclosed, preventing assessment of bias or domain-specific accuracy","No documented SLA or accuracy metrics; ranking quality is opaque and non-tunable","Ranking latency not documented; potential impact on keystroke-to-suggestion responsiveness unknown"],"requires":["C# Dev Kit extension (hard dependency)","C# file must be part of a VS Code solution (not standalone)","VS Code with IntelliSense support enabled","Microsoft telemetry enabled or disabled (feature works either way, but usage data only sent if enabled)"],"input_types":["C# source code (current file context)","Project metadata (solution structure, referenced assemblies)","Semantic context (cursor position, incomplete member access expression)"],"output_types":["ranked IntelliSense list (reordered suggestions)","star indicators (⭐) on top-ranked members","suggestion ordering (semantic relevance instead of alphabetical)"],"categories":["code-generation-editing","intellisense-ranking"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp__cap_1","uri":"capability://code.generation.editing.whole.line.c.code.prediction.with.inline.gray.text.display","name":"whole-line c# code prediction with inline gray-text display","description":"Generates multi-token code completions up to a full line of C# code and displays them as gray-text inline suggestions in the editor. The model analyzes the current file context, cursor position, and semantic state to predict the most likely next statement or expression. Predictions are non-intrusive (gray text) and accepted via TAB key, allowing developers to preview and accept/reject without modal interaction. Implementation uses VS Code's inline completion API to render predictions without disrupting the editing flow.","intents":["I want to complete a full line of C# code with a single keystroke instead of typing character-by-character","I need to see what the AI predicts I'll type next before committing to it","I want to quickly scaffold common patterns like method calls, assignments, or control flow statements"],"best_for":["C# developers writing boilerplate or repetitive code patterns","developers seeking faster keystroke reduction for common statements","teams with consistent coding conventions that the model can learn from"],"limitations":["Predictions limited to single-line scope; multi-line block completions not supported","Cannot predict string literal content—only suggests placeholder strings with cursor positioned for manual entry","Accuracy depends on solution context; predictions may be generic or incorrect for unfamiliar code patterns","No control over prediction aggressiveness or filtering; all predictions shown regardless of confidence threshold","Requires solution context; standalone C# files receive no inline predictions"],"requires":["C# Dev Kit extension","C# file part of a VS Code solution","VS Code inline completion support (standard in recent versions)"],"input_types":["C# source code (current file, cursor position)","Semantic context (incomplete statement, expression type)","Solution scope (for pattern learning)"],"output_types":["inline gray-text prediction (single line of C# code)","cursor position hint (for string placeholders)"],"categories":["code-generation-editing","inline-completion"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp__cap_2","uri":"capability://memory.knowledge.solution.scoped.semantic.context.analysis.for.code.understanding","name":"solution-scoped semantic context analysis for code understanding","description":"Analyzes the entire C# solution structure, including project dependencies, referenced assemblies, and custom codebase patterns, to build a semantic model that informs both ranking and prediction capabilities. The model extracts type information, method signatures, and usage patterns across files without transmitting source code to external services. This local semantic analysis enables the AI to understand domain-specific APIs and custom conventions that would be unavailable from file-level analysis alone.","intents":["I want the AI to understand my project's custom helper methods and suggest them appropriately","I need IntelliSense to recognize types and APIs specific to my solution, not just standard library","I want predictions that respect my codebase's naming conventions and architectural patterns"],"best_for":["teams with large, multi-project solutions where custom APIs are central to development","developers working in domain-specific codebases with unique conventions","projects where standard library suggestions are less relevant than internal abstractions"],"limitations":["Requires solution context; functionality unavailable for standalone C# files","Semantic analysis scope and depth are undisclosed; unclear what project metadata is extracted","No control over what solution elements are analyzed or how they influence predictions","Analysis latency not documented; potential impact on solution load time unknown","Custom model fine-tuning on solution patterns not supported"],"requires":["C# Dev Kit extension","Valid VS Code solution with proper project structure","Solution must be loaded and indexed by C# Dev Kit language server"],"input_types":["solution structure (project files, references)","type information (from language server)","method signatures and usage patterns (extracted from codebase)"],"output_types":["semantic context model (internal representation)","ranking signals (for IntelliSense reordering)","prediction constraints (for code generation)"],"categories":["memory-knowledge","code-understanding"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp__cap_3","uri":"capability://safety.moderation.privacy.preserving.local.code.analysis.with.telemetry.only.transmission","name":"privacy-preserving local code analysis with telemetry-only transmission","description":"Implements a privacy model where source code never leaves the developer's machine; only anonymized usage metadata (e.g., completion acceptance rate, feature usage frequency) is transmitted to Microsoft servers. The deep learning model executes locally or via secure cloud inference without exposing code content. This architecture separates code analysis (local) from telemetry collection (cloud), respecting the VS Code global telemetry setting to allow developers to opt out of all data transmission.","intents":["I need AI-assisted code completion without sending my proprietary source code to external servers","I want to disable telemetry collection entirely and ensure no usage data is transmitted","I need compliance with data residency or privacy regulations that prohibit code transmission"],"best_for":["enterprises with proprietary codebases subject to data residency regulations","developers working on sensitive projects (security, healthcare, finance) requiring code privacy","teams with strict data governance policies prohibiting cloud code transmission"],"limitations":["Model execution location (local vs. cloud) is undisclosed; unclear if code analysis happens on-device or via secure cloud inference","Telemetry scope is undefined—'usage metadata' is vague and may include more than keystroke counts","No granular telemetry controls; only binary on/off via VS Code's global telemetry setting","No audit trail or transparency report showing what data is collected and transmitted","Privacy guarantees depend on Microsoft's infrastructure security; no independent verification available"],"requires":["VS Code with telemetry setting accessible (respects telemetry.enableTelemetry)","Microsoft account or VS Code authentication (for feature licensing, not code transmission)","Network connectivity (for telemetry transmission if enabled)"],"input_types":["C# source code (local analysis only, never transmitted)","usage events (keystroke counts, completion acceptance, feature activation)"],"output_types":["anonymized telemetry data (transmitted to Microsoft if enabled)","no code content transmitted"],"categories":["safety-moderation","privacy-architecture"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp__cap_4","uri":"capability://code.generation.editing.method.overload.resolution.with.contextual.prioritization","name":"method overload resolution with contextual prioritization","description":"Automatically identifies and prioritizes relevant method overloads in IntelliSense suggestions based on the current code context (parameter types, expected return type, usage pattern). Rather than forcing developers to manually cycle through overloads, the model ranks overloads by semantic fit and displays the most appropriate one first. This capability integrates with the IntelliSense ranking system to reorder overload variants without requiring explicit user selection.","intents":["I want the correct method overload to appear first instead of cycling through 5+ variants","I need the AI to understand my parameter types and suggest the matching overload automatically","I want to avoid manual overload selection when the context makes the choice obvious"],"best_for":["C# developers working with APIs that have many overloads (e.g., LINQ, string methods)","teams using fluent APIs or builder patterns with multiple overload variants","developers seeking faster method selection without manual disambiguation"],"limitations":["Overload ranking accuracy depends on semantic context extraction; ambiguous contexts may produce incorrect prioritization","No user control over overload ranking; cannot manually adjust or provide hints","Ranking quality not documented; no metrics on overload resolution accuracy","Requires solution context; standalone files receive no overload prioritization"],"requires":["C# Dev Kit extension","C# file part of a solution","Method with multiple overloads in scope"],"input_types":["method call context (parameter types, expected return type)","semantic information (from language server)"],"output_types":["ranked overload list (most relevant first)","IntelliSense suggestion ordering"],"categories":["code-generation-editing","semantic-ranking"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-dotnettools-vscodeintellicode-csharp__cap_5","uri":"capability://code.generation.editing.string.placeholder.suggestion.with.cursor.positioning","name":"string placeholder suggestion with cursor positioning","description":"When the model encounters string literals in code predictions where content cannot be determined from context, it generates a placeholder string (e.g., empty string or generic placeholder) and positions the cursor within the string for immediate manual entry. This prevents the model from hallucinating string content it cannot predict, while maintaining prediction flow by providing a valid syntactic structure that developers can quickly fill in.","intents":["I want the AI to complete a method call with a string parameter without guessing the content","I need the cursor positioned inside string placeholders so I can immediately type the actual value","I want to avoid hallucinated or incorrect string content in code predictions"],"best_for":["developers using whole-line completion for method calls with string parameters","scenarios where string content is domain-specific or user-dependent (file paths, messages, keys)"],"limitations":["Placeholder strings are generic and may not match the intended content type (e.g., no distinction between file paths, error messages, or API keys)","Cursor positioning may not work correctly in all editor contexts or with certain keybinding configurations","No semantic hints provided about what string content is expected"],"requires":["whole-line completion capability enabled","VS Code cursor positioning support"],"input_types":["code context with string parameter requirement","semantic information about parameter type"],"output_types":["placeholder string in prediction","cursor position hint (inside string)"],"categories":["code-generation-editing","prediction-safety"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":48,"verified":false,"data_access_risk":"moderate","permissions":["C# Dev Kit extension (hard dependency)","C# file must be part of a VS Code solution (not standalone)","VS Code with IntelliSense support enabled","Microsoft telemetry enabled or disabled (feature works either way, but usage data only sent if enabled)","C# Dev Kit extension","C# file part of a VS Code solution","VS Code inline completion support (standard in recent versions)","Valid VS Code solution with proper project structure","Solution must be loaded and indexed by C# Dev Kit language server","VS Code with telemetry setting accessible (respects telemetry.enableTelemetry)"],"failure_modes":["Requires C# files to be part of a solution context—standalone .cs files receive no ranking functionality","Model architecture and training data are undisclosed, preventing assessment of bias or domain-specific accuracy","No documented SLA or accuracy metrics; ranking quality is opaque and non-tunable","Ranking latency not documented; potential impact on keystroke-to-suggestion responsiveness unknown","Predictions limited to single-line scope; multi-line block completions not supported","Cannot predict string literal content—only suggests placeholder strings with cursor positioned for manual entry","Accuracy depends on solution context; predictions may be generic or incorrect for unfamiliar code patterns","No control over prediction aggressiveness or filtering; all predictions shown regardless of confidence threshold","Requires solution context; standalone C# files receive no inline predictions","Requires solution context; functionality unavailable for standalone C# files","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.92,"quality":0.22,"ecosystem":0.21000000000000002,"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":"2026-05-24T12:16:34.803Z","last_scraped_at":"2026-05-03T15:20:29.937Z","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=intellicode-for-c-dev-kit","compare_url":"https://unfragile.ai/compare?artifact=intellicode-for-c-dev-kit"}},"signature":"MhmA4F9ti8eJ89YcadTfXg92lYeNX9FC2zHKs8NZBjFpiqs/ZNoq9MiFKA+XGguJ7cIhMY6aK3H31EkCTjUCCw==","signedAt":"2026-06-17T02:13:06.435Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/intellicode-for-c-dev-kit","artifact":"https://unfragile.ai/intellicode-for-c-dev-kit","verify":"https://unfragile.ai/api/v1/verify?slug=intellicode-for-c-dev-kit","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"}}