Sports Betting MCP

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: data source (Covers.com), refresh schedule (5am and 5pm EST), and that it returns active injury reports. However, it doesn't cover aspects like rate limits, error handling, or authentication needs, which are important for a tool with external data dependencies.

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: a clear purpose statement, data refresh info, and separate Args/Returns sections. Every sentence adds value without redundancy, and it's front-loaded with the core 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?

Given the tool's moderate complexity (1 parameter, external data), no annotations, and an output schema (which handles return values), the description is mostly complete. It covers purpose, usage hints, parameters, and data behavior, though it could better address sibling tool differentiation and more behavioral details like error cases.

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 description adds significant meaning beyond the input schema, which has 0% coverage. It explains the 'sport' parameter's purpose ('Filter by sport'), lists valid values ('nba', 'nhl', 'ncaab', or 'all'), and implies its optional nature through 'Filter by'. This compensates well for the schema's lack of 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 tool's purpose: 'Get current injury flags that may affect today's picks.' It specifies the verb ('Get'), resource ('current injury flags'), and context ('affect today's picks'). However, it doesn't explicitly differentiate from sibling tools like 'get_todays_picks' or 'get_top_pick' in terms of injury-specific focus versus general picks.

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 implies usage context through 'affect today's picks' and data refresh times, suggesting it's for daily sports analysis. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_todays_picks' or 'analyze_game', and doesn't mention prerequisites or exclusions.

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