Frontrun 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 adds some context by specifying sorting ('Sorted by follower_count descending') and the practical use case, but it lacks details on rate limits, authentication needs, error handling, or what the output looks like (e.g., format, pagination). This is a moderate gap for a tool with no annotations.

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 two sentences that efficiently convey the tool's purpose and usage without any wasted words. Every sentence adds value, making it highly concise and well-structured.

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 complexity (a ranking tool with 3 parameters), no annotations, and no output schema, the description is incomplete. It explains the purpose and usage but lacks details on behavioral traits (e.g., performance, errors) and output format, which are crucial for an agent to use it effectively. This is adequate but with clear 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 schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description does not add any parameter-specific information beyond what the schema provides (e.g., it doesn't explain 'since' or 'classify' further), resulting in a baseline score of 3.

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 entities ranked by number of tracked accounts that recently followed them') and resource ('entities'), distinguishing it from siblings like 'frontrun_new_follows' or 'frontrun_enriched_follows' by emphasizing ranking and trending analysis rather than raw data retrieval.

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 usage ('Use this for daily deal flow — see what VCs are paying attention to'), indicating when to use it for trend analysis. However, it does not explicitly state when not to use it or name specific alternatives among the many sibling tools, which would be needed for a score of 5.

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