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Exa Research

skill-ejirocodes-agent-skills-exa-research · by ejirocodes

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 verificat…

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Install

$ agentstack add skill-ejirocodes-agent-skills-exa-research

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Exa Research & Answer API

Quick Reference

| Topic | When to Use | Reference | |-------|-------------|-----------| | Answer API | Q&A with citations, grounded responses | [answer-api.md](references/answer-api.md) | | Deep Search | Smart query expansion, high-quality summaries | [deep-search.md](references/deep-search.md) | | Citations | Source attribution, verification | [citations.md](references/citations.md) |

Essential Patterns

Answer API (Python)

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}")

Streaming Answers

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)

Deep Search with Summaries

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}")

When to Use

| 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 |

Common Mistakes

  1. Not using streaming for long answers - Use stream=True for better UX on complex questions
  2. Ignoring citations - Always include response.citations for verifiable responses
  3. Missing text=True - Answer API needs content access; include text=True
  4. Over-complex queries - Answer API works best with clear, focused questions
  5. Not validating citations - Check citation.url exists before displaying to users

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.