exa-search
Search the web with Exa AI — neural search, content extraction, similar page discovery, quick research with citations, and async pro research with structured output. Covers all Exa endpoints (/search, /contents, /findSimilar, /answer, /research/v0/tasks). Triggers on web search, find pages, similar pages, research with citations, Exa, neural search.
npx skills add majiayu000/claude-skill-registry --skill exa-search-tdimino-claude-code-minoan --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Exa Search Skill 5 specialized scripts for Exa AI search API—neural search, content extraction, similar pages, research with citations, and async pro research. **Prerequisite:** `EXA_API_KEY` environment variable. Get key at https://dashboard.exa.ai ## Token-Efficient Search Inspired by Anthropic's [dynamic filtering](https://claude.com/blog/improved-web-search-with-dynamic-filtering)—always filter before reasoning. ~24% fewer tokens, ~11% better accuracy. ### The Principle: Search Cheaply → Filter → Extract Selectively → Reason **DO:** ```bash # Step 1: Search with --no-text (titles/URLs only — cheapest) python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" -n 20 --no-text # Step 2: Evaluate titles, pick best 3-5 URLs # Step 3: Extract only those URLs with bounded content python3 ~/.claude/skills/exa-search/scripts/exa_contents.py URL1 URL2 --highlights --max-chars 3000 ``` **DON'T:** Search with full text for 50 results, then reason over all of it. ### Use API-Level Filters First (Free Filtering) These reduce results at the API level before you ever see them: - `--must-include "term"` — results must contain this string - `--must-exclude "term"` — removes irrelevant
- Token-Efficient Search
- The Principle: Search Cheaply → Filter → Extract Selectively → Reason
- Use API-Level Filters First (Free Filtering)
- Use Summaries Over Full Text
- Use Bounded Context for RAG
- Post-Process with filterwebresults.py
- Cost Tiers — Match to Task
- Structured Deep Search (Exa Deep)
- Available Scripts
- 1. exasearch.py — Neural Web Search
- 2. exacontents.py — URL Content Extraction
- 3. exasimilar.py — Find Similar Pages
- 4. exaresearch.py — AI-Powered Research
- 5. exaresearchasync.py — Async Pro Research
Step 1: Search with --no-text (titles/URLs only — cheapest) python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" -n 20 --no-text Step 2: Evaluate titles, pick best 3-5 URLs Step 3: Extract only those URLs with bounded content python3 ~/.claude/skills/exa-search/scripts/exa_contents.py URL1 URL2 --highlights --max-chars 3000 AI-distilled summaries — much smaller than full text python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --summary "Key findings" -n 5 Capped context string — prevents unbounded token usage python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --context --context-chars 5000 python3 ~/.claude/skills/exa-search/scripts/exa_search.py "query" --json | \
What does the exa-search skill do?
Search the web with Exa AI — neural search, content extraction, similar page discovery, quick research with citations, and async pro research with structured output. Covers all Exa endpoints (/search, /contents, /findSimilar, /answer, /research/v0/tasks). Triggers on web search, find pages, similar pages, research with citations, Exa, neural search.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill exa-search-tdimino-claude-code-minoan --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.