{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-codeviz-codeviz","slug":"codeviz-visual-codebase-maps","name":"CodeViz | Visual codebase maps","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=CodeViz.codeviz","page_url":"https://unfragile.ai/codeviz-visual-codebase-maps","categories":["code-editors"],"tags":["ai","claude","copilot","flash","keybindings","search","sonnet","visual"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-codeviz-codeviz__cap_0","uri":"capability://code.generation.editing.hierarchical.codebase.visualization.with.llm.driven.architecture.mapping","name":"hierarchical codebase visualization with llm-driven architecture mapping","description":"Generates interactive visual maps of codebases by leveraging Anthropic LLMs to analyze code structure and produce Mermaid/Draw.io diagrams spanning from high-level architecture down to individual function calls. The extension processes code locally to generate embeddings, sends minimal context to Anthropic's API (with zero-day retention), and renders interactive webview diagrams where nodes link directly to source locations. Users can click any diagram element to jump to the corresponding code in the editor.","intents":["I need to understand the overall architecture of an unfamiliar codebase quickly without reading every file","I want to visualize how functions and modules interact across my entire project","I need to generate shareable architecture diagrams for documentation or team onboarding","I want to see the call graph and dependency structure from high level down to function level"],"best_for":["solo developers onboarding to large codebases","teams documenting legacy code architecture","engineering leads creating visual system design artifacts","developers migrating or refactoring complex projects"],"limitations":["Requires active internet connection to call Anthropic API; no offline mode or local-only LLM fallback documented","Scope of workspace analysis not explicitly documented — unclear if it analyzes entire workspace or requires explicit file selection","No control over which LLM model is used; appears hardcoded to Anthropic without provider switching mechanism","Diagram generation latency not documented; webview rendering may add perceptible delay for very large codebases","No built-in support for private/self-hosted LLM endpoints; locked to Anthropic's cloud API"],"requires":["VS Code 1.60.0 or later","Active internet connection","Anthropic API access (implicit; no explicit API key configuration documented)","Codebase with supported language (universal language support claimed via LLM, but no hardcoded parser list provided)"],"input_types":["source code files (any language via LLM analysis)","natural language queries about code structure"],"output_types":["Mermaid diagram format (Markdown-compatible)","Draw.io file format","interactive webview with clickable nodes linking to source locations"],"categories":["code-generation-editing","visualization","architecture-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_1","uri":"capability://text.generation.language.natural.language.codebase.querying.with.context.aware.diagram.generation","name":"natural language codebase querying with context-aware diagram generation","description":"Accepts plain English questions about code structure and generates focused, contextual diagrams in response by routing queries through Anthropic's LLM. The extension maintains awareness of the user's current file context and produces diagram suggestions tailored to the query scope. Generated diagrams are rendered interactively in the webview with direct links to relevant source code sections.","intents":["I want to ask 'how does authentication flow through this codebase?' and get a visual diagram showing the relevant modules and functions","I need to understand the data flow for a specific feature without manually tracing through files","I want to ask questions about code relationships and get focused diagrams instead of full codebase maps","I need context-aware suggestions for what to visualize based on the code I'm currently viewing"],"best_for":["developers unfamiliar with codebase conventions","non-expert team members needing quick code comprehension","code reviewers investigating specific feature implementations","technical writers documenting system behavior"],"limitations":["Query processing latency not documented; LLM round-trip time may vary based on query complexity and Anthropic API load","No documented query history or caching mechanism; repeated similar queries will re-invoke the LLM","Query suggestions are generated by LLM without explicit user control over suggestion criteria or filtering","No ability to refine or iterate on diagrams through follow-up questions; each query generates independent diagrams","Telemetry collects user queries (though not code); privacy implications of query logging unclear"],"requires":["VS Code 1.60.0 or later","Active internet connection","Anthropic API access","Open codebase/workspace in VS Code"],"input_types":["natural language text queries","current file context (implicitly captured)"],"output_types":["Mermaid diagrams","Draw.io diagrams","query suggestions (text)","interactive webview with clickable diagram nodes"],"categories":["text-generation-language","planning-reasoning","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_2","uri":"capability://memory.knowledge.one.click.llm.context.generation.for.downstream.ai.tools","name":"one-click llm context generation for downstream ai tools","description":"Generates comprehensive, codebase-wide context summaries in a single click, formatted for consumption by downstream LLM-based tools (e.g., Copilot, Claude, custom agents). The extension analyzes the full codebase locally to extract relevant code snippets, architecture patterns, and dependency information, then produces a structured prompt or context block that can be copied and pasted into other AI tools without requiring those tools to re-analyze the codebase.","intents":["I want to give Claude or Copilot full context about my codebase so it can generate better code suggestions","I need to create a comprehensive codebase summary to include in a custom LLM agent's system prompt","I want to avoid re-explaining my codebase structure every time I ask an AI tool for help","I need to share codebase context with team members or external AI tools without exposing raw code files"],"best_for":["developers using multiple LLM tools (Copilot, Claude, custom agents)","teams building custom AI agents that need codebase awareness","developers working with context-limited LLM APIs who need to optimize token usage","engineering teams creating AI-assisted code generation pipelines"],"limitations":["Context generation latency not documented; full codebase analysis may be slow for very large projects","No control over context format or granularity; output format appears fixed to a single template","No built-in token counting or optimization; generated context may exceed downstream LLM context windows","Context becomes stale over time; no automatic refresh mechanism documented","No versioning or change tracking; users cannot see what changed in context between generations"],"requires":["VS Code 1.60.0 or later","Active internet connection","Anthropic API access","Codebase loaded in VS Code workspace"],"input_types":["full codebase (implicit)","user trigger via command palette"],"output_types":["formatted text context block (copyable to clipboard)","LLM-optimized prompt format"],"categories":["memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_3","uri":"capability://code.generation.editing.interactive.click.to.code.navigation.from.diagram.nodes","name":"interactive click-to-code navigation from diagram nodes","description":"Enables direct navigation from generated diagram elements to source code by maintaining bidirectional links between diagram nodes and file locations. When a user clicks any node or connection in a Mermaid/Draw.io diagram rendered in the CodeViz webview, the extension automatically opens the corresponding source file and scrolls to the relevant function, class, or module definition. This is achieved through the extension's access to VS Code's editor API and file system context.","intents":["I want to click on a function in the architecture diagram and jump directly to its implementation","I need to navigate from a high-level architecture view down to specific code without manually searching files","I want to explore code relationships by clicking through connected nodes in the diagram","I need to verify that a diagram accurately represents the actual code by quickly jumping to source"],"best_for":["developers exploring unfamiliar codebases interactively","code reviewers tracing feature implementations","architects validating system design against actual code","developers debugging complex call chains"],"limitations":["Navigation accuracy depends on LLM's ability to correctly identify source locations; hallucinations may cause incorrect jumps","No fallback if source file has been moved or refactored since diagram generation; links may break","Webview sandbox may restrict direct file system access; navigation relies on VS Code extension API which may have latency","No history or breadcrumb navigation; users cannot easily backtrack through multiple clicks","Works only for files within the current workspace; cannot navigate to external dependencies or node_modules"],"requires":["VS Code 1.60.0 or later","Generated diagram (from visualization or query capability)","Source files present in current workspace","VS Code editor API access (implicit in extension)"],"input_types":["user click on diagram node or connection"],"output_types":["opened source file in VS Code editor","cursor positioned at relevant code location"],"categories":["code-generation-editing","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_4","uri":"capability://automation.workflow.multi.format.diagram.export.with.shareable.artifacts","name":"multi-format diagram export with shareable artifacts","description":"Exports generated codebase diagrams in multiple formats (Mermaid, Draw.io) to enable sharing and reuse across teams and tools. Mermaid diagrams are Markdown-compatible and can be embedded in documentation, GitHub READMEs, and wikis. Draw.io exports create editable diagram files that can be opened in Draw.io, Lucidchart, or other compatible tools. The extension handles format conversion and file generation locally without requiring external services.","intents":["I want to include architecture diagrams in my project's README or documentation","I need to share codebase structure with non-technical stakeholders in an editable format","I want to create diagrams in CodeViz and then refine them in Draw.io for presentation","I need to version control architecture diagrams alongside code in Git"],"best_for":["technical writers documenting system architecture","engineering teams creating onboarding materials","architects presenting system design to stakeholders","teams maintaining architecture decision records (ADRs)"],"limitations":["Mermaid format has limited styling and layout control compared to Draw.io; complex diagrams may render poorly","Draw.io export format not documented; unclear if exports are fully editable or read-only","No built-in version control or diff mechanism; diagram changes are not tracked alongside code changes","Export file size not documented; very large diagrams may create unwieldy files","No batch export capability; users must export diagrams one at a time"],"requires":["VS Code 1.60.0 or later","Generated diagram (from visualization or query capability)","File system write access to workspace or designated export directory"],"input_types":["generated Mermaid or Draw.io diagram (internal format)"],"output_types":["Mermaid text format (.md compatible)","Draw.io XML format (.drawio file)","exported files saved to disk"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_5","uri":"capability://data.processing.analysis.local.embedding.generation.with.privacy.preserving.analysis","name":"local embedding generation with privacy-preserving analysis","description":"Generates code embeddings locally within the VS Code extension process without transmitting raw code to external servers. The extension uses these embeddings to identify relevant code sections for diagram generation and context extraction. Embeddings are computed on-device using an unspecified embedding model, enabling semantic code analysis while maintaining code privacy. Only minimal processed context (not raw code) is sent to Anthropic's API for LLM analysis.","intents":["I want to analyze my codebase without exposing proprietary code to external AI services","I need semantic understanding of code relationships without transmitting source files to the cloud","I want to ensure my code never leaves my machine except for minimal LLM queries","I need to comply with data residency or privacy regulations that restrict code transmission"],"best_for":["enterprises with strict code privacy requirements","developers working on proprietary or sensitive codebases","teams in regulated industries (finance, healthcare, government)","organizations with data residency compliance requirements"],"limitations":["Embedding model and provider not documented; unclear if embeddings are computed using local models or cloud APIs","No control over embedding parameters or model selection; appears to use a fixed, non-configurable approach","Embedding computation latency not documented; local processing may be slow for very large codebases","No caching mechanism documented; embeddings may be recomputed on every analysis","Telemetry still collects user queries and session data; local analysis does not eliminate all data transmission"],"requires":["VS Code 1.60.0 or later","Sufficient local compute resources for embedding generation (CPU/memory requirements not documented)","Codebase loaded in VS Code workspace"],"input_types":["source code files (any language)"],"output_types":["vector embeddings (internal representation)","semantic similarity scores","relevant code section identification"],"categories":["data-processing-analysis","memory-knowledge","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_6","uri":"capability://automation.workflow.automatic.architecture.regeneration.with.command.driven.refresh","name":"automatic architecture regeneration with command-driven refresh","description":"Provides explicit commands to regenerate architecture visualizations and diagrams on demand via the command palette (`CodeViz: Regenerate Architecture`). When triggered, the extension re-analyzes the codebase, recomputes embeddings, and regenerates all diagrams to reflect recent code changes. This enables users to keep visualizations in sync with evolving codebases without manual diagram updates.","intents":["I've made significant code changes and want to update the architecture diagram to reflect the new structure","I want to refresh the codebase visualization to ensure it's current before sharing with the team","I need to regenerate diagrams after a major refactoring to verify the new architecture","I want to see how my recent changes affected the overall system architecture"],"best_for":["developers actively refactoring codebases","teams maintaining living architecture documentation","architects validating design changes against code","developers using CodeViz as a continuous architecture verification tool"],"limitations":["Regeneration latency not documented; full codebase re-analysis may take significant time for large projects","No incremental update mechanism; regeneration always re-analyzes the entire codebase rather than just changed files","No diff or change visualization; users cannot see what changed in the architecture between regenerations","No scheduled or automatic regeneration; users must manually trigger updates (no CI/CD integration documented)","Regeneration consumes API quota; frequent regenerations may incur costs if using a paid Anthropic plan"],"requires":["VS Code 1.60.0 or later","Active internet connection","Anthropic API access","Previously generated diagram or visualization"],"input_types":["user command via command palette","current codebase state"],"output_types":["updated Mermaid diagrams","updated Draw.io diagrams","refreshed webview visualization"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_7","uri":"capability://safety.moderation.optional.telemetry.collection.with.granular.privacy.control","name":"optional telemetry collection with granular privacy control","description":"Collects usage telemetry (error logs, webview open events, session replays, user queries) to improve the extension, with a binary toggle in extension settings to disable all telemetry. When enabled, telemetry is transmitted to CodeViz servers; when disabled, no usage data is collected. Notably, raw code and LLM prompts are explicitly NOT collected, and all data sent to Anthropic, GCP, and AWS has zero-day retention (deleted immediately after processing).","intents":["I want to help improve CodeViz by sharing usage data while maintaining code privacy","I need to disable telemetry to comply with corporate privacy policies","I want to verify that my code is not being collected or stored by CodeViz","I need to understand what data CodeViz collects before using it in my organization"],"best_for":["developers comfortable with telemetry sharing","enterprises with strict data collection policies","teams evaluating CodeViz for compliance requirements","organizations needing to audit extension data practices"],"limitations":["Telemetry toggle is all-or-nothing; no granular control over which data types are collected","Session replay collection raises privacy concerns; unclear what constitutes a 'session' or what is captured","User query collection means search/question history is transmitted even though code is not; query patterns could reveal proprietary logic","No data retention policy for CodeViz's own servers; zero-day retention applies only to Anthropic/GCP/AWS, not CodeViz infrastructure","No audit log or transparency report; users cannot verify what data was actually collected or transmitted"],"requires":["VS Code 1.60.0 or later","Access to extension settings (Preferences)"],"input_types":["user toggle in extension settings"],"output_types":["telemetry enabled/disabled state","usage data transmission (if enabled)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-codeviz-codeviz__cap_8","uri":"capability://automation.workflow.automatic.extension.updates.with.user.controlled.scheduling","name":"automatic extension updates with user-controlled scheduling","description":"Automatically checks for and installs CodeViz extension updates in the background, with commands to disable or enable auto-updates (`CodeViz: Disable Auto Updates`, `CodeViz: Enable Auto Updates`). When auto-updates are enabled, the extension periodically checks for new versions and installs them without user intervention. Users can disable auto-updates to maintain a stable version or control update timing.","intents":["I want to automatically receive bug fixes and new features without manual updates","I need to disable auto-updates to maintain a stable version during critical development","I want to control when extension updates are applied to avoid disruptions","I need to ensure my team is using the same extension version for consistency"],"best_for":["individual developers who want hands-off updates","teams with strict change management policies","developers working on time-sensitive projects","organizations requiring update approval workflows"],"limitations":["Update frequency not documented; unclear how often the extension checks for updates","No staged rollout or beta channel; all users receive the same version simultaneously","No update changelog or preview; users cannot see what changed before updating","Disabling auto-updates requires manual command execution; no UI toggle documented","No rollback mechanism documented; users cannot easily revert to a previous version if an update causes issues"],"requires":["VS Code 1.60.0 or later","Active internet connection (for update checks)","Access to command palette"],"input_types":["user command via command palette"],"output_types":["auto-update enabled/disabled state","extension version updates (if enabled)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":42,"verified":false,"data_access_risk":"high","permissions":["VS Code 1.60.0 or later","Active internet connection","Anthropic API access (implicit; no explicit API key configuration documented)","Codebase with supported language (universal language support claimed via LLM, but no hardcoded parser list provided)","Anthropic API access","Open codebase/workspace in VS Code","Codebase loaded in VS Code workspace","Generated diagram (from visualization or query capability)","Source files present in current workspace","VS Code editor API access (implicit in extension)"],"failure_modes":["Requires active internet connection to call Anthropic API; no offline mode or local-only LLM fallback documented","Scope of workspace analysis not explicitly documented — unclear if it analyzes entire workspace or requires explicit file selection","No control over which LLM model is used; appears hardcoded to Anthropic without provider switching mechanism","Diagram generation latency not documented; webview rendering may add perceptible delay for very large codebases","No built-in support for private/self-hosted LLM endpoints; locked to Anthropic's cloud API","Query processing latency not documented; LLM round-trip time may vary based on query complexity and Anthropic API load","No documented query history or caching mechanism; repeated similar queries will re-invoke the LLM","Query suggestions are generated by LLM without explicit user control over suggestion criteria or filtering","No ability to refine or iterate on diagrams through follow-up questions; each query generates independent diagrams","Telemetry collects user queries (though not code); privacy implications of query logging unclear","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.58,"quality":0.28,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.75,"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":"2026-05-03T15:20:40.998Z","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=codeviz-visual-codebase-maps","compare_url":"https://unfragile.ai/compare?artifact=codeviz-visual-codebase-maps"}},"signature":"am/RfrejzYRDdjiSOC65N5pJF6SH8lG0NtHrNTNfVwpEQbRTUClG33FFTyc9TAFp/dD6P/o1G0tMnKv1UUG/Dg==","signedAt":"2026-06-21T11:13:44.790Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/codeviz-visual-codebase-maps","artifact":"https://unfragile.ai/codeviz-visual-codebase-maps","verify":"https://unfragile.ai/api/v1/verify?slug=codeviz-visual-codebase-maps","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"}}