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apaper_search_google_scholar_papers

Search Google Scholar for academic papers by query, with optional year range and result count filters to narrow results.

Instructions

Search academic papers from Google Scholar

Args: query: Search query string (e.g., 'machine learning', 'neural networks') max_results: Maximum number of papers to return (default: 10) year_low: Minimum publication year (optional) year_high: Maximum publication year (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo
year_lowNo
year_highNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states it 'searches' and lists parameters, but does not mention any behavioral traits such as rate limits, authentication requirements, or potential side effects. The existence of an output schema mitigates some need for return format details, but other behaviors remain opaque.

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?

The description is concise, front-loaded with the main purpose, followed by a structured list of parameters. Every sentence serves a purpose and there is no extraneous information.

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 tool has 4 parameters and an output schema exists, the description adequately covers input semantics. However, it lacks context about output format, pagination, or potential errors. For a search tool, this is fairly complete but could be improved by adding a note about output structure.

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

Parameters5/5

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

The schema description coverage is 0%, meaning the schema provides no parameter descriptions. The description fully compensates by explaining each parameter: query (with example), max_results (default value), year_low, and year_high. It adds meaning beyond the schema's basic type information.

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?

The description clearly states it searches academic papers from Google Scholar, using the verb 'Search' and specifying the resource. It distinguishes from sibling tools like apaper_search_dblp_papers and apaper_search_iacr_papers by indicating the source is Google Scholar.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus other search tools (e.g., DBLP, IACR) or what scenarios are appropriate. It lacks explicit when-to-use or when-not-to-use instructions, leaving the agent without context for selection.

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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