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From exa
Exa.ai deep research and answer generation with citations. Use when building research automation, implementing Answer API for Q&A with sources, creating research reports, or using deep search with summaries. Triggers on: Exa Answer, answer endpoint, exa.answer, deep search, research API, Exa Research, async research, research report, citation extraction, summarization with sources, fact verification, streaming answers, research tasks.
npx claudepluginhub ejirocodes/agent-skills --plugin exaHow this skill is triggered — by the user, by Claude, or both
Slash command
/exa:exa-researchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
| Topic | When to Use | Reference |
Conducts AI-powered deep research on any topic via triggers like '/deep-research [topic]' or 'deep research on [topic]'. Uses interactive AskUserQuestion for focus, output, and audience selection.
Conducts AI-powered deep research with citations via the Tavily CLI. Use for multi-source analysis, comparisons, market reports, and literature reviews.
Instructs Claude to conduct thorough, multi-angle research on any topic before answering, synthesizing diverse sources and perspectives.
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| Topic | When to Use | Reference |
|---|---|---|
| Answer API | Q&A with citations, grounded responses | answer-api.md |
| Deep Search | Smart query expansion, high-quality summaries | deep-search.md |
| Citations | Source attribution, verification | citations.md |
from exa_py import Exa
exa = Exa()
response = exa.answer(
"What are the key features of Python 3.12?",
text=True
)
print(response.answer)
for citation in response.citations:
print(f"Source: {citation.url}")
stream = exa.answer(
"Explain the benefits of microservices architecture",
stream=True
)
for chunk in stream:
print(chunk.text, end="", flush=True)
# Access citations after streaming
print("\nSources:", stream.citations)
results = exa.search_and_contents(
"latest developments in quantum computing",
type="neural",
num_results=10,
summary=True,
use_autoprompt=True # Smart query expansion
)
for result in results.results:
print(f"{result.title}")
print(f"Summary: {result.summary}")
| Feature | Use Case | Output |
|---|---|---|
| Answer API | Direct Q&A needing citations | Answer + source URLs |
| Deep Search | Query expansion + summaries | Enhanced search results |
| Exa Research | Long-form async reports | Structured JSON/Markdown |
stream=True for better UX on complex questionsresponse.citations for verifiable responsestext=True - Answer API needs content access; include text=Truecitation.url exists before displaying to users