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 and does well by disclosing key behavioral traits: execution time (60-300s), reliability note ('quick' depth is most reliable), and output format (structured report as JSON). It could improve by mentioning potential errors, rate limits, or authentication needs, but covers essential 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 appropriately sized and front-loaded, with the core purpose in the first sentence. However, it has minor redundancy (repeating 'may take 60-300s') and could be more streamlined, though every sentence contributes useful information without waste.

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 complexity (research synthesis with variable depth), no annotations, and no output schema, the description does well by covering purpose, behavior, timing, and output format. It could be more complete by detailing error handling or example outputs, but it provides sufficient context for effective use.

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 baseline is 3. The description adds minimal parameter semantics beyond the schema—it reiterates timing for depth options and implies topic scope but doesn't provide additional syntax, format, or constraints. This meets the baseline without significant added value.

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 ('run a deep research session', 'searches', 'synthesizes') and resources ('512k+ CS/AI papers'), distinguishing it from siblings like search_papers or get_research_landscape by emphasizing synthesis into structured reports with specific components (clusters, gap analysis, evidence chains).

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 (for deep research with synthesis vs. simple searches) and includes timing guidance ('60-300 seconds'), but does not explicitly state when not to use it or name specific alternatives among siblings, though the depth parameter guidance ('quick' is most reliable) offers implicit usage advice.

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