{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-ms-vscode-vscode-websearchforcopilot","slug":"web-search-for-copilot","name":"Web Search for Copilot","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=ms-vscode.vscode-websearchforcopilot","page_url":"https://unfragile.ai/web-search-for-copilot","categories":["browser-extensions","code-editors"],"tags":["chat-participant","language-model-tools","tools"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-ms-vscode-vscode-websearchforcopilot__cap_0","uri":"capability://search.retrieval.natural.language.web.search.query.execution.within.copilot.chat","name":"natural language web search query execution within copilot chat","description":"Accepts natural language questions prefixed with @websearch in VS Code's Copilot chat interface, converts them to optimized search queries, executes searches via Tavily's search engine API, and returns ranked results with metadata. The extension acts as a chat participant that intercepts user intent, formats queries for Tavily's API, and streams results back into the chat context for further processing by the language model.","intents":["I need to search the web for current information not in my training data while coding","I want to ask Copilot a question that requires real-time web results without leaving VS Code","I need to find documentation, tutorials, or examples for a library or framework that's too recent for my LLM's training data"],"best_for":["developers building applications that require current information (APIs, frameworks, best practices)","teams working on projects with rapidly evolving dependencies or standards","solo developers who want to stay in VS Code without context-switching to a browser"],"limitations":["Requires active Tavily API key and internet connectivity; searches fail silently if API quota is exhausted","Search quality is entirely dependent on Tavily's index freshness and ranking algorithm — no control over result ordering or filtering","Automatic intent detection for web-relevant queries is optional and may miss queries that would benefit from web context","No caching of search results documented; every query incurs API latency and potential rate-limiting costs"],"requires":["GitHub Copilot extension installed and authenticated in VS Code","Tavily API key (free tier available; requires signup at tavily.com)","VS Code version (minimum version not documented; assume recent stable release)","Active internet connection"],"input_types":["natural language text (questions, queries)"],"output_types":["structured search results (title, URL, snippet, metadata from Tavily)","processed or raw results depending on websearch.useSearchResultsDirectly setting"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-vscode-vscode-websearchforcopilot__cap_1","uri":"capability://text.generation.language.web.search.result.synthesis.and.context.injection.into.language.model.responses","name":"web search result synthesis and context injection into language model responses","description":"Processes raw Tavily search results and injects them as context into GitHub Copilot's language model, enabling the LLM to synthesize web-sourced information into natural language responses. The extension optionally post-processes results (controlled by websearch.useSearchResultsDirectly setting) before passing them to the LLM, allowing either raw result injection or filtered/summarized context.","intents":["I want Copilot to answer my question using current web information, not just its training data","I need Copilot to cite sources from the web when answering my question","I want to see how Copilot synthesizes web results into a coherent explanation"],"best_for":["developers seeking current best practices, API documentation, or framework recommendations","teams building applications that depend on rapidly changing external information","developers who want LLM-synthesized answers rather than raw search result lists"],"limitations":["Post-processing behavior is controlled by a single boolean setting (websearch.useSearchResultsDirectly); no granular control over result filtering, ranking, or summarization","LLM synthesis quality depends on Copilot's model version and training; no control over how results are interpreted or prioritized","No documented mechanism to force source attribution or citation format in responses","Result freshness is bounded by Tavily's index update frequency; real-time data (stock prices, live events) may be delayed"],"requires":["GitHub Copilot extension with language model access","Tavily API key with active quota","VS Code version with support for chat participant context injection"],"input_types":["structured search results from Tavily (JSON with title, URL, snippet, metadata)"],"output_types":["natural language text (LLM-synthesized response incorporating web context)","chat message with embedded source references (format not documented)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-vscode-vscode-websearchforcopilot__cap_2","uri":"capability://tool.use.integration.programmatic.web.search.tool.invocation.for.other.vs.code.extensions","name":"programmatic web search tool invocation for other vs code extensions","description":"Exposes the web search capability as a reusable tool via VS Code's vscode.lm.invokeTool API, allowing other extensions and chat participants to programmatically invoke web searches and consume results. This enables extensions to compose web search into larger workflows without reimplementing search logic, using a standard tool-calling interface compatible with GitHub Copilot's function-calling patterns.","intents":["I'm building a VS Code extension that needs web search capability without implementing Tavily integration myself","I want my custom chat participant to invoke web searches as part of a multi-step workflow","I need to compose web search results with other tools in a chain-of-thought reasoning pattern"],"best_for":["extension developers building AI-powered tools that require real-time web context","teams creating custom chat participants that need to augment responses with web data","developers implementing agent-like workflows that combine multiple tools including web search"],"limitations":["Tool invocation is asynchronous and adds latency per call; no documented timeout or cancellation mechanism","Error handling for Tavily API failures (quota exceeded, network errors) is not documented; calling extensions must implement their own retry logic","No built-in result caching across tool invocations; repeated searches for identical queries incur duplicate API costs","Tool schema and return format are not publicly documented; extensions must reverse-engineer or rely on undocumented behavior"],"requires":["VS Code extension development environment (Node.js, TypeScript)","Access to vscode.lm.invokeTool API (requires VS Code version with LM API support)","Tavily API key configured in the host VS Code instance","Web Search for Copilot extension installed and activated"],"input_types":["tool invocation parameters (query string, optional configuration)"],"output_types":["structured search results (format not documented; likely JSON with title, URL, snippet)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-vscode-vscode-websearchforcopilot__cap_3","uri":"capability://automation.workflow.configurable.search.result.post.processing.with.raw.processed.toggle","name":"configurable search result post-processing with raw/processed toggle","description":"Provides a single configuration setting (websearch.useSearchResultsDirectly) that controls whether search results are post-processed before injection into the language model or passed raw from Tavily. When enabled, raw results bypass any filtering or summarization; when disabled, results undergo unspecified post-processing (likely summarization or relevance filtering) before context injection.","intents":["I want to see raw search results without any filtering or summarization applied","I want Copilot to receive pre-processed, summarized results to reduce context window usage","I need to control the trade-off between result freshness and processing latency"],"best_for":["developers who want fine-grained control over search result quality vs. latency","teams with limited context window budgets who need to minimize result verbosity","users who distrust automatic summarization and prefer to see raw data"],"limitations":["Only one boolean toggle available; no granular control over post-processing strategy (filtering, ranking, summarization method)","Post-processing behavior when toggle is disabled is not documented; users cannot predict or customize the transformation","No performance metrics provided for raw vs. processed results; impact on latency and context window usage is unknown","Setting is global; no per-query override mechanism documented"],"requires":["VS Code settings UI or settings.json access","Web Search for Copilot extension installed"],"input_types":["boolean configuration value (true/false)"],"output_types":["modified search result processing behavior (affects downstream LLM context injection)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-vscode-vscode-websearchforcopilot__cap_4","uri":"capability://safety.moderation.secure.api.key.management.via.vs.code.secret.storage","name":"secure api key management via vs code secret storage","description":"Manages Tavily API keys using VS Code's built-in secret storage API, which encrypts credentials and integrates with the system's credential manager (e.g., macOS Keychain, Windows Credential Manager, Linux Secret Service). On first use, the extension prompts for an API key, stores it securely, and retrieves it transparently for all subsequent Tavily API calls without requiring manual re-entry.","intents":["I want to securely store my Tavily API key without hardcoding it in my VS Code settings","I need my API key to be encrypted and managed by VS Code's credential system","I want to share my VS Code settings across machines without exposing my API key"],"best_for":["individual developers who want secure credential management without external tools","teams sharing VS Code configurations via dotfiles or settings sync","developers working on machines with system credential managers (macOS, Windows, Linux with Secret Service)"],"limitations":["API key is stored per VS Code instance; syncing settings across machines does not sync the API key (requires re-entry on new machines)","No mechanism to rotate or revoke API keys from within the extension; users must manually update via settings","Secret storage is tied to the VS Code installation; uninstalling and reinstalling VS Code may lose the stored key","No audit log or visibility into when/how the API key is being used; users must trust Tavily's logging"],"requires":["VS Code with secret storage API support (recent stable versions)","System credential manager available (Keychain on macOS, Credential Manager on Windows, Secret Service on Linux)","Tavily API key (obtained from tavily.com)"],"input_types":["API key string (provided via prompt dialog on first use)"],"output_types":["encrypted credential stored in system credential manager"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-ms-vscode-vscode-websearchforcopilot__cap_5","uri":"capability://planning.reasoning.optional.automatic.web.search.intent.detection.for.chat.queries","name":"optional automatic web search intent detection for chat queries","description":"Provides an optional feature that automatically detects when a user's chat query would benefit from web search (e.g., questions about current events, recent API releases, or time-sensitive information) and invokes the web search tool without explicit @websearch prefix. The detection mechanism uses heuristics or LLM-based classification to identify web-relevant intent, though the specific algorithm is not documented.","intents":["I want Copilot to automatically search the web when I ask about current information, without typing @websearch","I want the extension to intelligently decide when web context is needed based on my question","I want a seamless experience where web search is invoked transparently for relevant queries"],"best_for":["developers who want a hands-off experience with minimal explicit tool invocation","teams building workflows where automatic context augmentation improves response quality","users who frequently ask time-sensitive questions and want to avoid manual @websearch prefix"],"limitations":["Intent detection algorithm is not documented; users cannot predict when web search will be triggered","No false-positive prevention mechanism documented; may invoke web search for queries that don't need it, wasting API quota","No per-query override to disable automatic search for specific questions; users must disable the feature globally","Configuration method for enabling/disabling automatic detection is not documented; may require extension settings or undocumented configuration","Automatic search adds latency to all chat queries, even those that don't need web context"],"requires":["Web Search for Copilot extension installed","Automatic intent detection feature enabled (configuration method unknown)","Tavily API key with sufficient quota"],"input_types":["natural language chat query"],"output_types":["automatic web search invocation (transparent to user) if intent is detected as web-relevant"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":41,"verified":false,"data_access_risk":"high","permissions":["GitHub Copilot extension installed and authenticated in VS Code","Tavily API key (free tier available; requires signup at tavily.com)","VS Code version (minimum version not documented; assume recent stable release)","Active internet connection","GitHub Copilot extension with language model access","Tavily API key with active quota","VS Code version with support for chat participant context injection","VS Code extension development environment (Node.js, TypeScript)","Access to vscode.lm.invokeTool API (requires VS Code version with LM API support)","Tavily API key configured in the host VS Code instance"],"failure_modes":["Requires active Tavily API key and internet connectivity; searches fail silently if API quota is exhausted","Search quality is entirely dependent on Tavily's index freshness and ranking algorithm — no control over result ordering or filtering","Automatic intent detection for web-relevant queries is optional and may miss queries that would benefit from web context","No caching of search results documented; every query incurs API latency and potential rate-limiting costs","Post-processing behavior is controlled by a single boolean setting (websearch.useSearchResultsDirectly); no granular control over result filtering, ranking, or summarization","LLM synthesis quality depends on Copilot's model version and training; no control over how results are interpreted or prioritized","No documented mechanism to force source attribution or citation format in responses","Result freshness is bounded by Tavily's index update frequency; real-time data (stock prices, live events) may be delayed","Tool invocation is asynchronous and adds latency per call; no documented timeout or cancellation mechanism","Error handling for Tavily API failures (quota exceeded, network errors) is not documented; calling extensions must implement their own retry logic","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.64,"quality":0.22,"ecosystem":0.34,"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":"2026-05-24T12:16:34.803Z","last_scraped_at":"2026-05-03T15:20:32.168Z","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=web-search-for-copilot","compare_url":"https://unfragile.ai/compare?artifact=web-search-for-copilot"}},"signature":"OBGGY5iMRNohdYp0hIq8f4dVBmJETFaoVkuroInTNsQGs7MpOU0ddsaJxCK/e07wKcNETCoazIZDpqo8GKGKCQ==","signedAt":"2026-06-20T21:23:10.717Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/web-search-for-copilot","artifact":"https://unfragile.ai/web-search-for-copilot","verify":"https://unfragile.ai/api/v1/verify?slug=web-search-for-copilot","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"}}