Academic Research Skill: Bring Scholarly Search to Your AI Agent

Where this fits

Your agent is asked: "Summarize the latest findings on ketamine for treatment-resistant depression." Without a dedicated research skill, it scrapes blog posts and news articles, missing the peer-reviewed evidence. The academic-research skill plugs into SandBase's scholarly search APIs, letting your agent query academic databases, retrieve papers, and return citable, source-backed answers.

Why agents benefit

• Finds scholarly sources via scholar_search_scholar instead of generic web results, so claims rest on peer-reviewed literature.
• Distinguishes preprints from published work — the skill's operating principles push agents to flag publication status, reducing hallucinated authority.
• Produces structured citations (title, authors, year, source) that can be dropped directly into a response or a reference list.
• Handles literature review tasks — from "what's the state of the art in X" to "find papers citing Y" — without building custom API integrations.
• Falls back to web search (scholar_search_web) when the query needs broader context, keeping the agent flexible.

Practical scenarios

Preparing a literature review draft

A research assistant agent receives a request: "Outline key papers on federated learning privacy." It uses the skill to search scholarly databases, retrieves 10 recent papers, and organizes them by theme, noting which are preprints and which are published in journals.

Answering evidence-based questions in a support bot

A customer asks about the efficacy of a supplement. The agent queries academic search, finds a meta-analysis, and replies with a citation and a caveat about study limitations — avoiding the hype typical of general web results.

Building a citation trail for a technical report

An engineering agent writing a design doc needs to back a claim about TCP congestion control. It calls the skill to locate the original RFC and subsequent academic evaluations, then formats the references correctly.

Add it to your agent workflow

Install the skill with:

npx skills add sandbaseai/sandbase-skills --skill academic-research

Then, in your agent's tool definitions, expose the skill's capabilities. For example, when a user asks for a literature review, your agent calls scholar_search_scholar with a query, then uses sandbase_describe_tool to validate the input schema before each call. The skill's README guides you through the exact workflow — see the full skill details for implementation notes.

Compare before adopting

Evaluate this skill against alternatives by checking:

• Quality signals — Does it clearly separate peer-reviewed sources from preprints? Does it enforce citation formatting?
• Maintenance freshness — SandBase APIs can change; check the repo's last commit and issue tracker.
• Alternatives — Other academic search tools (e.g., Semantic Scholar API, arXiv wrappers) might fit narrower use cases.
• Workflow fit — Does the skill's operating principle align with your agent's need for evidence vs. speed? If you need only arXiv, a lighter tool may be better.

Why it is worth tracking

With 31 stars and an active author, this skill is young but promising. The real value is its opinionated workflow — telling agents to cite properly and distinguish preprint vs. peer-reviewed — which most generic search tools lack. Track it if you're building agents that must answer research-heavy queries credibly; as SandBase's API matures, this skill could become a standard building block for academic agent workflows.