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 full burden. It discloses key behavioral traits: the tool finds datasets where at least 2 specified models have been evaluated and enables direct score comparison. However, it lacks details on output format, error handling, or performance characteristics like rate limits.

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: the first sentence states the core functionality, the second explains the matching logic, and the third provides a concrete example. Every sentence earns its place without 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 no annotations and no output schema, the description is moderately complete for a read-only comparison tool. It covers the purpose and basic behavior but lacks details on return values, error cases, or data freshness, which are important for a tool with 3 parameters and complex matching logic.

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%, providing a solid baseline. The description adds minimal value beyond the schema by mentioning '2-10 models/methods' (implied in schema's min/max) and giving an example, but does not explain parameter interactions or provide additional semantic context for 'dataset' or 'metric'.

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 ('compare side-by-side across shared benchmarks') and resources ('models/methods'), and distinguishes it from siblings by focusing on comparative analysis rather than individual lookups or searches. The example concretely illustrates the scope.

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 '2-10 models/methods' and 'shared benchmarks', but does not explicitly state when to use this tool versus alternatives like 'get_benchmark_stats' or 'search_benchmarks'. It provides clear functional boundaries but lacks direct sibling comparisons.

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