AgentSkillsCN

exa

使用Exa.ai神经搜索进行语义搜索,优化AI应用场景。当意义比关键词更为重要时——寻找学术论文、相似公司、代码上下文,以及关键词搜索遗漏的概念性内容时,可使用此功能。

SKILL.md
--- frontmatter
name: exa
version: 1.0.0
description: Semantic web search using Exa.ai neural search optimized for AI consumption. Use when meaning matters more than keywords -- find academic papers, similar companies, code context, and conceptual content that keyword search misses.
homepage: https://exa.ai/
metadata:
  clawdbot:
    emoji: "🔍"
    requires:
      mcp: ["exa"]

Exa Semantic Search Skill

YOU MUST invoke this skill (NOT optional) when the user mentions ANY of these triggers:

  • "semantic search", "find papers on", "find articles about"
  • "companies similar to", "find sources about"
  • "Exa", "exa search", "neural search"
  • Any request for conceptual/meaning-based web search (not keyword matching)

Failure to invoke this skill when triggers occur violates your operational requirements.

Exa.ai provides neural semantic search optimized for AI consumption. Use when meaning matters more than keywords.

Decision Flowchart

Use this to decide which search tool to use:

ScenarioToolWhy
"Find papers on emergent AI behavior"mcp__exa__web_search_exaSemantic discovery
"Companies similar to Anthropic"mcp__exa__web_search_exaSimilar content
"How to use React hooks"mcp__exa__get_code_context_exaCoding context
"Latest news on X"WebSearchRecency matters
"Read this URL: [link]"WebFetchKnown URL
"error: module not found XYZ"WebSearchExact keyword match
"CVE-2024-12345"WebSearchSpecific identifier

Decision logic:

  1. Have a specific URL? -> WebFetch
  2. Is this semantic/conceptual (meaning > keywords)? -> Exa
  3. Is it a coding/API question? -> mcp__exa__get_code_context_exa
  4. Need very recent news/events? -> WebSearch
  5. Keyword/identifier match? -> WebSearch

Tool Usage

mcp__exa__web_search_exa

Semantic web search for concepts, topics, and similar content.

code
query: "semantic query describing concepts"
numResults: 8 (default, adjust as needed)
type: "auto" | "fast" | "deep"

mcp__exa__get_code_context_exa

Code-specific search for programming patterns, APIs, and implementations.

code
query: "React useState hook examples" | "Express middleware patterns"
tokensNum: 5000 (default, 1000-50000 range)

mcp__exa__company_research_exa

Company-specific research for competitive analysis and market research.

Integration Patterns

Discovery + Extraction

  1. Exa finds relevant sources semantically
  2. WebFetch extracts full content from best URLs

Multi-Perspective Research

  1. Exa: "academic perspectives on X"
  2. Exa: "industry implementation of X"
  3. Exa: "critiques of X"
  4. Synthesize findings

Fallback Strategy

  1. Try Exa for semantic search
  2. If results poor, fall back to WebSearch with keywords

Anti-Patterns

Don'tDo Instead
"python pandas filter dataframe"Use WebSearch (keyword query)
Run 10 similar queriesConsolidate into 2-3 well-crafted queries
"what is React"Use knowledge or WebSearch
"breaking news today"Use WebSearch

When Results Are Poor

  1. Switch search type: auto vs fast vs deep
  2. Rephrase: more semantic/descriptive
  3. Add domain filters via allowed_domains
  4. Fall back to WebSearch for keyword matching