Scholar Feed MCP Server

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

No annotations are provided, so the description carries the full burden. It discloses the scope ('covers 20k+ datasets from 24k+ papers') and return format ('matching benchmark names with paper counts and available metrics'), but lacks details on behavioral traits like error handling, rate limits, or authentication needs. The description doesn't contradict any annotations, but could be more comprehensive for a search tool.

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 front-loaded with the core purpose, followed by usage guidance and scope details. Every sentence adds value: the first states what it does, the second explains when to use it, and the third provides context on coverage. No wasted words or redundancy.

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 (search with 2 parameters), no annotations, and no output schema, the description does well by explaining purpose, usage, and scope. However, it could be more complete by detailing the output structure (e.g., format of returned metrics) or search behavior (e.g., fuzzy matching). It's adequate 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 fully documents both parameters. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain search syntax or result ordering). With high schema coverage, the baseline score of 3 is appropriate.

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's purpose with specific verb ('search for') and resource ('datasets/benchmarks by name'), distinguishing it from siblings like 'search_papers' or 'search_by_method'. It explicitly mentions what it returns ('matching benchmark names with paper counts and available metrics'), making the purpose unambiguous.

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 explicit guidance on when to use this tool ('to find the exact benchmark name before calling get_leaderboard'), which clearly differentiates it from sibling tools. It also implies when not to use it (e.g., for searching papers or methods), though it doesn't explicitly list all alternatives.

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