Agent skill · Content & Marketing

exa-research

Use Exa AI for neural search, content retrieval, and automated deep research. Requires EXA_API_KEY.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill exa-research-closedloop-technolog-awesome-deep-researc-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 2 KB
Bundled scripts: none
Path: skills/ai-llm/exa-research-closedloop-technolog-awesome-deep-researc-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Exa Research Skill This skill leverages the Exa AI API for neural search, finding similar content, and autonomous research via their Research endpoint. ## Setup 1. **Dependencies:** Requires `exa-py` and `openai` (for research endpoint compatibility). ```bash pip install exa-py openai python-dotenv ``` 2. **API Key Configuration:** Requires `EXA_API_KEY`. ```bash # If the script fails due to a missing key, run the following: echo "It seems the Exa API key is not set up." read -p "Enter your Exa API key: " EXA_KEY echo "EXA_API_KEY=$EXA_KEY" >> .env if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi echo "API key saved to .env." ``` ## Usage The script `scripts/exa_tools.py` supports multiple operations. ### 1. Search and Contents Perform a neural search and retrieve content or highlights. ```bash python3 scripts/exa_tools.py search "<query>" [--num-results <N>] [--highlights] ``` **Example:** ```bash python3 scripts/exa_tools.py search "innovative sustainable urban planning" --num-results 5 --highlights ``` ### 2. Research (Automated) Automate in-depth research and receive a structured report. ```bash python3 scripts/exa_tools.py research "<qu

What's inside
Steps it walks through
  1. Setup
  2. Usage
  3. 1. Search and Contents
  4. 2. Research (Automated)
  5. 3. Find Similar
  6. Output
Ships with 1 file
  • metadata.json
Commands it runs
pip install exa-py openai python-dotenv
echo "It seems the Exa API key is not set up."
read -p "Enter your Exa API key: " EXA_KEY
echo "EXA_API_KEY=$EXA_KEY" >> .env
if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi
echo "API key saved to .env."
python3 scripts/exa_tools.py search "<query>" [--num-results <N>] [--highlights]
python3 scripts/exa_tools.py search "innovative sustainable urban planning" --num-results 5 --highlights
python3 scripts/exa_tools.py research "<query>" [--model <exa-research|exa-research-pro>]
python3 scripts/exa_tools.py research "Analyze the impact of quantum computing on cryptography" --model exa-research-pro
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About this skill
What does the exa-research skill do?

Use Exa AI for neural search, content retrieval, and automated deep research. Requires EXA_API_KEY.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill exa-research-closedloop-technolog-awesome-deep-researc-2 --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.

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