Frontrun MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the action ('Add') but fails to specify whether this is a creation, update, or mutation operation, and omits critical details like required permissions, rate limits, idempotency, or what happens if tags already exist. For a tool with 6 parameters and no annotations, this lack of behavioral context is a significant gap.

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 two sentences: the first states the core functionality, and the second provides usage examples. It avoids redundancy and is appropriately sized for the tool's complexity, though it could be slightly more front-loaded with key behavioral details given the lack of annotations.

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 (6 parameters, no annotations, no output schema), the description is incomplete. It covers the basic purpose and usage examples but fails to address behavioral aspects like mutation effects, error handling, or return values. Without annotations or an output schema, the agent lacks sufficient context to invoke this tool confidently in varied scenarios.

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, providing clear documentation for all 6 parameters (e.g., 'twitter_user_id' as 'Twitter user ID of the entity'). The description adds minimal value beyond the schema by listing the types of data that can be added ('custom tags, sector override, or notes') but does not elaborate on parameter interactions, constraints, or usage examples beyond what's already in the schema descriptions.

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 action ('Add custom tags, sector override, or notes') and the resource ('to a specific entity'), with specific examples like 'build custom watchlists, mark competitors, or annotate companies.' However, it doesn't explicitly differentiate this tool from siblings like 'frontrun_list_tags' or 'frontrun_update_rule,' which might handle similar tagging operations, leaving some ambiguity about its unique role.

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 implied usage through examples ('Use this to build custom watchlists, mark competitors, or annotate companies'), suggesting contexts for application. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'frontrun_list_tags' for viewing tags or 'frontrun_update_rule' for rule-based tagging), and does not mention prerequisites or exclusions, leaving the agent to infer best practices.

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