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 of behavioral disclosure. It effectively describes key behavioral traits: the tool finds new papers not in the original report, synthesizes follow-up analysis, and importantly discloses execution time ('Takes 20-60 seconds'), which is valuable operational context not captured elsewhere. However, it doesn't mention potential limitations like rate limits or authentication requirements.

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 three sentences that each earn their place: first states the core purpose, second specifies prerequisites, third provides important timing information. No wasted words, front-loaded with the main 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?

For a tool with 5 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It covers the tool's purpose, prerequisites, and execution time. However, without annotations or output schema, it could benefit from more detail about the analysis output format or any constraints on the types of follow-up questions supported.

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 all 5 parameters thoroughly. The description adds minimal parameter semantics beyond what's in the schema - it mentions the 'report_id' requirement but doesn't provide additional context about parameter interactions or usage patterns. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Ask a follow-up question', 'Finds new papers', 'synthesizes a focused follow-up analysis') and identifies the resource ('completed deep_research report'). It distinguishes from sibling tools like 'deep_research' by focusing on follow-up analysis rather than initial research.

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 ('on a completed deep_research report', 'Requires the report_id from a previous deep_research call'), but doesn't explicitly state when not to use it or name specific alternatives among the sibling tools. The guidance is sufficient but lacks explicit exclusion criteria.

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