Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →codealive-ai/exa-research-paper-search
Find academic papers with Exa — by topic, author, recency, or as surveys/reviews.
Passed 6 of 12 test cases with the skill, and 3 of 12 without it.
and 5 more in the full report
5 fixed6 passed either way11 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
Provide the terminal command to run a search for contrastive language-image pre-training vision transformers, returning 7 results.
| Checked | Without skill | With skill |
|---|---|---|
| Encloses topic string in double quotes when calling python scripts/research_paper_search.py. | Missed | Passed |
| Passes -n 7 to scripts/research_paper_search.py. | Missed | Passed |
The instructions your model reads when the skill loads.
Find academic papers and preprints via Exa's research-paper index (arXiv and beyond). Calls the Exa REST API through a local script; no MCP server needed, only an EXA_API_KEY.
export EXA_API_KEY=your-key # or EXA_API_KEY=... in a .env at the repo root
Get a key at https://dashboard.exa.ai/api-keys. Shared details: exa-native-base.
python scripts/research_paper_search.py "<topic / method>" [-n N] [--json]
Examples:
python scripts/research_paper_search.py "sparse attention mechanisms for long context transformers" -n 12
python scripts/research_paper_search.py "diffusion models comprehensive survey review" -n 10
python scripts/research_paper_search.py "Geoffrey Hinton forward-forward algorithm" -n 5
Defaults to category=research paper.
# By topic
python scripts/research_paper_search.py "category:research paper retrieval augmented generation robustness" -n 12
# Survey / review papers (best entry point into a field)
python scripts/research_paper_search.py "category:research paper <topic> comprehensive survey review" -n 10
# By author
python scripts/research_paper_search.py "category:research paper <author name> <topic>" -n 5
# By recency — encode the year(s) in the query (don't rely on date filters alone)
python scripts/research_paper_search.py "category:research paper large language model agents 2025 2026" -n 15
test cases passed, vs 3 / 12 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.