Extract research results (title, authors, year, snippet) from a Google Scholar search URL. Scholar exposes only the publication year, not an exact date, so freshness confidence is capped at medium.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Google Scholar search URL |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safe-read nature. The description adds a valuable behavioral disclosure: Scholar only provides the publication year, not an exact date, capping freshness confidence at medium. This goes beyond annotations with useful data quality context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first delivers the core purpose, the second adds a concise limitation. No wasted words or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple one-parameter schema and annotations, the description provides the necessary purpose, expected output fields, and a key limitation. The lack of an output schema is compensated by the explicit list of fields (title, authors, year, snippet). It fully covers the tool's scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the single `url` parameter with a description and format, so the schema carries the parameter semantics. The description merely restates that it takes a Scholar URL without adding format or usage details, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extract') and resource ('Google Scholar search URL') and enumerates the extracted fields (title, authors, year, snippet). This clearly distinguishes it from sibling tools like extract_arxiv or extract_reddit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying the input type (Google Scholar URL) and output fields, but lacks explicit guidance on when to prefer it over alternatives or when not to use it. The clarity of the resource makes the intended use evident, but it doesn't name alternative tools or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.