Paper Distill 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 describes the return behavior (structured prompt or POOL_EXHAUSTED message) and the expected AI response format. However, it doesn't mention potential side effects, rate limits, authentication needs, or what 'today's scan batch' entails operationally. The description adds some context but leaves gaps about the tool's full behavior.

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 highly concise and well-structured: three sentences that efficiently cover purpose, output, and error handling. Each sentence earns its place by providing essential information without redundancy. The front-loaded purpose statement immediately clarifies the tool's function.

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 has an output schema (which handles return value documentation), no annotations, and a simple input schema, the description is reasonably complete. It covers purpose, usage context, and error conditions. However, for a tool that prepares review prompts, it could benefit from more detail about what 'today's scan batch' means or how the prompt is structured, leaving 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?

The input schema has 100% description coverage for its single parameter ('dual'), so the baseline is 3. The description doesn't mention parameters directly, but it implies context about 'today's scan batch' and review modes, which adds semantic meaning beyond the schema's technical definition of 'dual'. This elevates the score slightly as it provides operational context.

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: 'Prepare the review prompt for today's scan batch' and specifies it 'Returns a structured prompt listing candidate papers for the AI to review.' This identifies the verb ('prepare'), resource ('review prompt'), and output format. However, it doesn't explicitly differentiate from sibling tools like 'prepare_summarize' or 'rank_papers' that might also involve paper processing.

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 usage guidance: it specifies when to use the tool ('for today's scan batch'), what to do if it fails ('If pool is exhausted, returns "POOL_EXHAUSTED" — call pool_refresh first'), and names an alternative action ('pool_refresh'). This clearly informs the agent about prerequisites and error handling.

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