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SMABoundless

semantic-scholar-mcp-server

by SMABoundless

paper_autocomplete

Autocomplete partial paper titles to disambiguate or quickly find papers. Get up to 10 suggestions from Semantic Scholar.

Instructions

Autocomplete a partial paper title, returning up to 10 suggestions. Use for title disambiguation or quick lookup of papers by partial title.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPartial paper title to autocomplete (max 100 characters).
response_formatNoOutput format: 'markdown' for human-readable text (default), 'json' for raw structured datamarkdown
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries the burden. It mentions returning up to 10 suggestions but lacks details on ordering, case sensitivity, or behavior when no matches are found. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences pack essential information: what the tool does and its use cases. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (2 params, no output schema), the description covers the key aspects: action, limit, use cases. Could mention the source of suggestions but sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage with descriptions for both parameters. The description adds minimal extra meaning beyond the schema, so baseline score applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool action: autocomplete a partial paper title, returning up to 10 suggestions. It also specifies use cases for disambiguation and quick lookup, distinguishing it from sibling tools like paper_search or paper_get.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance provided: 'Use for title disambiguation or quick lookup of papers by partial title.' This implies when to use it, though it doesn't explicitly state when not to use or list alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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