Scholar Feed MCP Server

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 adds useful context beyond basic functionality by mentioning the source ('extracted from 78k+ papers'), scope of returns ('papers that introduce or evaluate the method'), and additional data ('with benchmark result counts'). However, it does not cover important behavioral aspects like rate limits, authentication needs, error conditions, or pagination details, leaving gaps for a tool with no annotation coverage.

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 appropriately sized and front-loaded, with the first sentence clearly stating the purpose and key differentiator. Every sentence adds value: the second explains the structured field source, and the third details the return scope and additional data. There is no wasted text, making it highly efficient.

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 tool's moderate complexity (4 parameters, no output schema, no annotations), the description does a good job of covering core functionality, differentiation, and return context. However, it lacks details on output format, error handling, or performance characteristics, which would be beneficial for an agent to use it correctly without an output schema. It is mostly complete but has minor gaps.

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds marginal value by providing examples of the 'q' parameter (e.g., 'LoRA', 'YOLO', 'DPO', 'attention') and hinting at the tool's focus on methods, but it does not explain parameter interactions, default behaviors beyond the schema, or semantic nuances. This meets the baseline for high schema coverage.

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 clearly states the tool searches papers by method/technique name, specifies it searches a structured field extracted from 78k+ papers, and distinguishes it from keyword search. It explicitly mentions the verb 'search', resource 'papers', and scope 'method or technique name' with examples, making it highly specific and differentiated from siblings like search_papers.

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 provides clear context for when to use this tool by contrasting it with keyword search ('Unlike keyword search, this searches the structured method_name field'), but it does not explicitly mention when not to use it or name specific alternatives among siblings. This gives good guidance but lacks explicit exclusions or named alternatives.

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