Scholar Feed MCP Server

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

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it uses semantic search, returns factual count-based aggregates (methods, benchmarks, authors, etc.), and explicitly states 'no rankings or editorial labels.' However, it misses details like rate limits, error handling, or performance characteristics (e.g., speed implications of 'limit' parameter).

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 specific details on methodology and outputs. Every sentence adds value: the first states the action, the second explains the process, and the third clarifies the data nature. No redundant or wasted words, making it efficient and well-structured.

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 no annotations and no output schema, the description does a good job covering the tool's behavior and outputs (e.g., lists aggregates like methods, benchmarks, authors). However, it lacks details on return format (e.g., JSON structure) and error cases, which would be helpful for an agent. For a tool with 2 parameters and rich functionality, it's 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 both parameters ('q' and 'limit') thoroughly. The description adds minimal value beyond the schema by mentioning 'semantic search' for 'q' and implying 'limit' affects breadth and speed, but does not provide additional syntax or format details. Baseline 3 is appropriate given 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's purpose: 'Get aggregated research landscape statistics for a topic.' It specifies the verb ('get aggregated statistics') and resource ('research landscape'), and distinguishes from siblings by detailing its unique semantic search approach and count-based aggregates, unlike tools like 'search_papers' or 'get_author_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 implies usage context through 'for a topic' and mentions 'semantic search to find relevant papers,' but lacks explicit guidance on when to use this tool versus alternatives like 'search_papers' or 'deep_research.' It does not specify exclusions or direct comparisons with sibling tools.

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