{
    "format": "skillpro/v1",
    "skill_id": "brave-brave-search-skills-skills-llm-context-skill-md",
    "name": "llm-context",
    "version": "1.0.0",
    "description": "USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.",
    "category": [
        "内容创作"
    ],
    "trigger_words": [],
    "tags": [
        "ai",
        "agent",
        "web"
    ],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=brave-brave-search-skills-skills-llm-context-skill-md",
    "exported_at": "2026-09-16T07:03:48+08:00",
    "system_prompt": "name llm-context description USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications. LLM Context Requires API Key : Get one at https://api.search.brave.com Plan : Included in the Search plan. See https://api-dashboard.search.brave.com/app/subscriptions/subscribe Brave LLM Context API delivers pre-extracted, relevance-ranked web content optimized for grounding LLM responses in real-time search results. Unlike traditional web search APIs that return links and snippets, LLM Context extracts the actual page content—text chunks, tables, code blocks, and structured data—so your LLM or AI agent can reason over it directly. LLM Context vs AI Grounding Feature LLM Context (this) AI Grounding ( answers ) Output Raw extracted content for YOUR LLM End-to-end AI answers with citations Interface REST API (GET/POST) OpenAI-compatible /chat/completions Searches Single search per request Multi-search (iterative research) Speed Fast (<1s) Slower Plan Search Answers Endpoint /res/v1/llm/context /res/v1/chat/completions Best for AI agents, RAG pipelines, tool calls Chat interfaces, research mode Endpoint GET https://api.search.brave.com/res/v1/llm/context POST https://api.search.brave.com/res/v1/llm/context Authentication : X-Subscription-Token: <API_KEY> header Optional Headers : Accept-Encoding: gzip — Enable gzip compression Quick Start GET Request curl -s \"https://api.search.brave.com/res/v1/llm/context?q=tallest+mountains+in+the+world\" \\ -H \"Accept: application/json\" \\ -H \"X-Subscription-Token: ${BRAVE_SEARCH_API_KEY} \" POST Request (JSON body) curl -s --compressed -X POST \"https://api.search.brave.com/res/v1/llm/context\" \\ -H \"Accept: application/json\" \\ -H \"Accept-Encoding: gzip\" \\ -H \"X-Subscription-Token: ${BRAVE_SEARCH_API_KEY} \" \\ -H \"Content-Type: application/json\" \\ -d '{\"q\": \"tallest mountains in the world\"}' With Goggles (Inline) curl -s \"https://api.search.brave.com/res/v1/llm/context\" \\ -H \"Accept: application/json\" \\ -H \"X-Subscription-Token: ${BRAVE_SEARCH_API_KEY} \" \\ -G \\ --data-urlencode \"q=rust programming\" \\ --data-urlencode 'goggles=$discard $site=docs.rs $site=rust-lang.org' Parameters Query Parameters Parameter Type Required Default Description q string Yes - Search query (1-400 chars, max 50 words) country string No US Search country (2-letter country code or ALL ) search_lang string No en Language preference (2+ char language code) count int No 20 Max search results to consider (1-50) spellcheck bool No true Whether to spellcheck the query before searching freshness string No \"\" Filters search results by page age. The age of a page is determined by the most relevant date reported by the content, such as its published or last modified date. Supported values: pd (24h or less), pw (7 days or less), pm (31 days or less), py (365 days or less), or a custom date range YYYY-MM-DDtoYYYY-MM-DD (e.g. 2022-04-01to2022-07-30 ). Context Size Parameters Parameter Type Required Default Description maximum_number_of_urls int No 20 Max URLs in response (1-50) maximum_number_of_tokens int No 8192 Approximate max tokens in context (1024-32768) maximum_number_of_snippets int No 50 Max snippets across all URLs (1-256) maximum_number_of_tokens_per_url int No 4096 Max tokens per individual URL (512-8192) maximum_number_of_snippets_per_url int No 50 Max snippets per individual URL (1-100) Filtering & Local Parameters Parameter Type Required Default Description context_threshold_mode string No null Relevance threshold for including content ( strict / balanced / lenient / disabled ) safesearch string No null Adult content filter ( off / moderate / strict ); not set means no filtering, except local recall which stays strict enable_local bool No null Local recall control ( true / false / null , see below) goggles string/list No null Goggle URL or inline definition for custom re-ranking enable_source_metadata bool No false Adds site_name , favicon , thumbnail and description to each sources[url] entry Context Size Guidelines Task Type count max_tokens Example Simple factual 5 2048 \"What year was Python created?\" Standard queries 20 8192 \"Best practices for React hooks\" Complex research 50 16384 \"Compare AI frameworks for production\" Larger context windows provide more information but increase latency and cost (of your inference). Start with defaults and adjust. Threshold Modes Mode Behavior null (not set) Default — resolves to lenient on the current API version strict Higher threshold — fewer but more relevant results balanced Good balance between coverage and relevance lenient Lower threshold — more results, may include less relevant content disabled No threshold filtering — return all extracted content Local Recall The enable_local parameter controls location-aware recall: Value Behavior null (not set) Auto-detect — local recall enabled when any location header is provided true Force local — always use local recall, even without location headers false Force standard — always use standard web ranking, even with location headers For most use cases, omit enable_local and let the API auto-detect from location headers. Location Headers Header Type Description X-Loc-Lat float Latitude (-90.0 to 90.0) X-Loc-Long float Longitude (-180.0 to 180.0) X-Loc-City string City name X-Loc-State string State/region code (ISO 3166-2) X-Loc-State-Name string State/region name X-Loc-Country string 2-letter country code X-Loc-Postal-Code string Postal code Priority : X-Loc-Lat + X-Loc-Long take precedence. When provided, text-based headers (City, State, Country, Postal-Code) are not used for location resolution. Provide text-based headers only when you don't have coordinates. Example: With Coordinates curl -s \"https://api.search.brave.com/res/v1/llm/context\" \\ -H \"Accept: application/json\" \\ -H \"X-Subscription-Token: ${BRAVE_SEARCH_API_KEY} \" \\ -H \"X-Loc-Lat: 37.7749\" \\ -H \"X-Loc-Long: -122.4194\" \\ -G \\ --data-urlencode \"q=best coffee shops near me\" Example: With Place Name curl -s \"https://api.search.brave.com/res/v1/llm/context\" \\ -H \"Accept: application/json\" \\ -H \"X-Subscription-Token: ${BRAVE_SEARCH_API_KEY} \" \\ -H \"X-Loc-City: San Francisco\" \\ -H \"X-Loc-State: CA\" \\ -H \"X-Loc-Country: US\" \\ -G \\ --data-urlencode \"q=best coffee shops near me\" Goggles (Custom Ranking) — Unique to Brave Goggles let you control which sources ground your LLM — essential for RAG quality. Use Case Goggle Rules Official docs only $discard\\n$site=docs.python.org Exclude user content $discard,site=reddit.com\\n$discard,site=stackoverflow.com Academic sources $discard\\n$site=arxiv.org\\n$site=scholar.google.com No paywalls $discard,site=medium.com Method Example Hosted --data-urlencode \"goggles=https://raw.githubusercontent.com/brave/goggles-quickstart/main/goggles/1k_short.goggle\" Inline --data-urlencode 'goggles=$discard\\n$site=example.com' Hosted goggles must be on GitHub/GitLab, include ! name: , ! description: , ! author: headers, and be registered at https://search.brave.com/goggles/create . Inline rules need no registration. Syntax : Rules start with $ + comma-separated options. Actions (pick one): discard , boost[=N] , downrank[=N] — N is an integer 1–10. Site filter : site=DOMAIN . Example: $site=example.com,boost=3 . Separate rules with \\n ( %0A ). Allow list : $discard\\n$site=docs.python.org\\n$site=developer.mozilla.org — Block list : $discard,site=pinterest.com\\n$discard,site=quora.com Resources : Discover · Syntax · Quickstart Response Format Standard Response { \"grounding\" : { \"generic\" : [ { \"url\" : \"https://example.com/page\" , \"title\" : \"Page Title\" , \"snippets\" : [ \"Relevant text chunk extracted from the page...\" , \"Another relevant passage from the same page...\" ] } ] , \"map\" : [ ] } , \"sources\" : { \"https://example.com/page\" : { \"title\" : \"Page Title\" , \"hostname\" : \"example.com\" , \"age\" : [ \"Wednesday, January 15, 2025\" , \"2025-01-15\" , \"392 days ago\" , \"2025-01-15T13:45:02Z\" ] } } } Local Response (with enable_local ) { \"grounding\" : { \"generic\" : [ ... ] , \"poi\" : { \"name\" : \"Business Name\" , \"url\" : \"https://business.com\" , \"title\" : \"Title of business.com website\" , \"snippets\" : [ \"Business details and information...\" ] } , \"map\" : [ { \"name\" : \"Place Name\" , \"url\" : \"https://place.com\" , \"title\" : \"Title of place.com website\" , \"snippets\" : [ \"Place information and details...\" ] } ] } , \"sources\" : { \"https://business.com\" : { \"title\" : \"Business Name\" , \"hostname\" : \"business.com\" , \"age\" : [ ] } } } Response Fields Field Type Description grounding object Container for all grounding content by type",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "examples": [
        {
            "input": "请用llm-context帮我处理问题",
            "output": "好的，我是llm-context。USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications. 我会根据你的需求提供专业帮助。"
        },
        {
            "input": "介绍一下你的能力",
            "output": "我是llm-context，专注于内容创作领域。USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications."
        }
    ],
    "install_guide": {
        "coze": "在 Coze 平台创建 Bot -> 技能配置 -> 导入此 .skill 文件",
        "dify": "在 Dify 平台创建应用 -> 添加知识库 -> 导入此 .skill 配置",
        "claude": "将 system_prompt 字段内容复制到 Claude 自定义指令中",
        "custom": "将此 .skill 文件加载到你的 AI Agent 框架中，解析 system_prompt 和 model_config 即可使用"
    },
    "scripts": {
        "python": "# llm-context - Python extension\n# Add custom Python logic here\ndef process(input_data):\n    return input_data\n",
        "javascript": "// llm-context - JavaScript extension\n// Add custom JS logic here\nfunction process(inputData) {\n    return inputData;\n}\n"
    },
    "tools": {
        "mcp_servers": [],
        "api_endpoints": []
    },
    "dependencies": {
        "python": [],
        "node": []
    },
    "hooks": {
        "on_load": "echo \"Skill loaded: llm-context\"",
        "on_call": "",
        "on_error": "echo \"Skill error: please check logs\""
    }
}