agentleFS
Sign inStart free
baofeng-techbaofeng-tech/agent-skills-so/scholar-search/SKILL.md

scholar-search

Skill0 starsChanged 7 months agoMITView on GitHub

Search academic papers and scholarly articles via AIsa Scholar endpoint. Supports year range filtering for targeted research. Use when: the user needs web search, research, source discovery, or content extraction.

  • Reads credentials

4 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 4 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Search academic papers and scholarly articles using the AIsa Scholar Search endpoint.

    line 18
  2. Very specific:

    Run the search client with the scholar subcommand:

    line 26
  3. Distinctive:

    Use this skill when the user needs academic papers, scholarly articles, research citations, or peer-reviewed sources.

    line 61

“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

AIsa Scholar Search

Search academic papers and scholarly articles using the AIsa Scholar Search endpoint. Ideal for finding peer-reviewed research, conference papers, and citations. Supports year range filtering.

Setup

This skill requires the AISA_API_KEY environment variable. When installed as a Claude plugin, the key is configured via the environment variables.

Usage

Run the search client with the scholar subcommand:

python3 scripts/search_client.py scholar --query "<academic query>" --count <max_results> [--year-from YYYY] [--year-to YYYY]

Arguments

ArgumentRequiredDefaultDescription
--query / -qYes—Academic search query
--count / -cNo10Maximum number of results (1–100)
--year-fromNo—Year lower bound (e.g., 2023)
--year-toNo—Year upper bound (e.g., 2026)

Examples

# Search for recent transformer papers
python3 scripts/search_client.py scholar --query "transformer architecture attention mechanism" --count 10 --year-from 2024

# Search papers in a specific year range
python3 scripts/search_client.py scholar --query "reinforcement learning from human feedback" --year-from 2022 --year-to 2025

Output

The script prints structured academic results including:

  • Title — Paper title
  • URL — Link to the paper or abstract
  • Publication info — Journal, conference, or preprint source
  • Snippet — Abstract excerpt

When to Use

Use this skill when the user needs academic papers, scholarly articles, research citations, or peer-reviewed sources. Best for literature reviews, citation lookups, and academic research tasks.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free