菜单
Perform an internet search using the official Brave Search MCP server. Use when the user asks to search with Brave, needs image/video/news/local search, or wants Brave's privacy-focused index.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | brave-search |
| description | Perform an internet search using the official Brave Search MCP server. Use when the user asks to search with Brave, needs image/video/news/local search, or wants Brave's privacy-focused index. |
| argument-hint | <query> |
Perform an internet search using the official Brave Search MCP server.
IMPORTANT: You MUST use the mcp__brave-search__brave_web_search tool for this command. Do NOT use the built-in WebSearch tool.
.mcp.json using @brave/brave-search-mcp-serverBRAVE_API_KEY environment variable set (get one at https://brave.com/search/api/)query: The search terms (everything after /brave-search)When invoked:
mcp__brave-search__brave_web_search call with the provided query — never fire multiple searches per invocation/brave-search latest Next.js features
/brave-search how to configure ESLint for TypeScript
/brave-search React Server Components best practices
## Brave Search: [query]
### Results
[Summarized findings from search results]
### Sources
- [Title](URL)
- [Title](URL)
- [Title](URL)
mcp__brave-search__brave_local_searchIf the search fails:
BRAVE_API_KEY is set correctly/mcp to verify status)/web-search as a fallback/web-search - Uses Claude's built-in WebSearch (no MCP required)internet-researcher agent - For deep, multi-query research using Brave SearchSQL engineering standards for writing correct, safe, cross-dialect SQL across PostgreSQL, MySQL, SQL Server, SQLite, DuckDB, and Oracle. Use when writing SQL queries, exploring schemas, running migrations, optimizing queries, transpiling between dialects, or connecting to databases via native CLIs.
MongoDB engineering standards for querying collections, building aggregation pipelines, designing document schemas, managing indexes, and administering deployments via mongosh. Use when writing MongoDB queries, exploring collections, designing schemas, optimizing performance, or managing replica sets and sharding.
Engineering planning standards for creating design docs, DRI working docs, ADRs, and weekly updates. Use when planning projects, writing design docs, creating RFCs, tracking risks, writing status updates, or reviewing engineering plans. Covers structure, operational tracking, context engineering, and scaling from startup to enterprise.
Multi-agent PR review that spawns parallel domain-specific subagents (python-expert, rust-expert, dbt-expert, dotnet-expert, kedro-expert, d2-tala-expert, ui-designer) based on changed file types, posts inline review comments on GitHub, GitLab, and Azure DevOps.
dbt engineering standards for building clean, modular, well-tested data transformations. Use when writing dbt models, configuring sources, designing project structure, writing tests, managing materializations, or preparing for dbt Fusion. Covers dbt Core 1.8–1.11, Fusion v2.0, SQL style, testing, governance, and deployment.
Langfuse observability platform standards for querying traces, managing prompts, debugging LLM applications, and accessing Langfuse data programmatically. Use when interacting with Langfuse, querying traces or sessions, managing prompts, instrumenting applications, or looking up Langfuse documentation. Covers CLI-based API access (via npx) and documentation retrieval.