sm_predictions

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

No annotations are provided, so the description must disclose behavioral traits. It only says 'Get' and lists modes without mentioning pagination, required parameters per mode, response format, or potential limitations. This falls short of the burden on an annotation-less tool.

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 two sentences, front-loaded with the primary action, and compactly lists modes. Every phrase earns its place without redundancy or fluff.

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?

With no annotations, no output schema, and low parameter coverage, the description is insufficient. It fails to explain the interplay between modes and parameters, output structure, or error behavior, leaving significant gaps for a tool with multiple modes.

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 coverage is low (25%), but the description explains the 'mode' enum values, adding meaning beyond the raw schema. However, it does not clarify how page, include, or fixtureId relate to each mode, nor that fixtureId is likely required for by_fixture modes.

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 retrieves SportMonks predictions, with explicit modes ('probabilities', 'by_fixture', 'value_bets', 'value_bets_by_fixture') that define scope. This distinguishes it from sibling odds/livescore tools by the resource being predictions.

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 gives implied usage context via the phrase 'Great for model cross-reference' and enumerates modes, but does not explicitly state when to use this tool over sibling tools or provide exclusion criteria. No alternatives are mentioned.

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