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 describes the return content well (structured benchmark results) but lacks details on behavioral traits like error handling (e.g., what happens if no results exist), rate limits, authentication needs, or whether it's a read-only operation. The description doesn't contradict any annotations, but it could provide more operational 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 efficiently structured in two sentences: the first states the purpose and return value, the second provides usage guidance. Every sentence adds value, with no redundant information. It's appropriately sized and front-loaded with the core functionality.

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 (single parameter, no output schema, no annotations), the description is reasonably complete. It explains what the tool does, when to use it, and what it returns. However, without an output schema, it could benefit from more detail on the return structure (e.g., format of the 'structured benchmark results'). The lack of behavioral transparency details slightly reduces completeness.

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%, with the single parameter 'arxiv_id' fully documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't clarify format constraints or provide examples). Baseline score of 3 is appropriate since the schema already provides complete parameter documentation.

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 verbs ('Get structured benchmark results') and resource ('for a paper'), distinguishing it from siblings like get_paper (which presumably provides general paper info) and get_benchmark_stats (which likely provides aggregate statistics rather than paper-specific results). The description explicitly mentions what it returns: quantitative results, datasets, metrics, scores, comparisons, and baselines.

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: 'Use this after get_paper to see how a paper performed on benchmarks.' This clearly distinguishes it from get_paper (which comes first) and suggests a workflow. It also implies when not to use it (e.g., for general paper info or aggregate benchmark data).

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