Spocal Sports MCP

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 indicates the tool returns capability information and implies a read-only action via the verb 'list,' but it does not explicitly state that it is side-effect-free, describe the return format, or mention any prerequisites beyond calling it first. This is adequate but not rich in behavioral detail.

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 long, front-loaded with the core purpose and followed by a practical usage instruction. Every sentence contributes value with no redundancy or filler, 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?

For a zero-parameter tool with no output schema, the description adequately covers what the tool does, the scope of capabilities, and when to call it. It could be slightly more explicit about the output format (e.g., whether it returns a list or instructions), but the description sufficiently conveys the tool's role as an entry point.

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 zero parameters, which sets a baseline of 4. The description does not need to explain parameters since there are none, and it adds no parameter-related semantics beyond what the schema already provides.

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 lists Spocal MCP capabilities, specifying both sports data tools and the article authoring workflow. It distinguishes itself from siblings by positioning itself as the first call to learn how to embed matches, players, and prediction markets, making the purpose specific and actionable.

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 explicitly says 'Call this first,' providing clear when-to-use guidance for discovering capabilities and workflows. However, it does not explicitly mention alternatives or when not to use this tool relative to sibling tools like list_supported_competitions, so it lacks full exclusionary guidance.

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

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 details critical output semantics: the 'url' field is canonical, URLs must be used verbatim, and 'external_url' fields are not Spocal entities. This goes well beyond a basic list operation.

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 front-loaded with the purpose and every sentence earns its place by conveying essential usage rules around URL handling. It is concise without being under-specified.

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?

For a simple list tool with no output schema, the description provides sufficient context: it explains the capped nature, the absence of schedule rows, and the key URL-related behaviors needed to correctly consume the results. It is complete for the tool's complexity.

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 already documents the single 'limit' parameter with its maximum and exclusivity. The description's 'capped set' aligns with the schema but adds no additional parameter-level detail, so the baseline score of 3 is appropriate.

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 function with a specific verb ('List') and resource ('supported competitions'), including the 'capped set' and 'without schedule rows' qualifiers. However, it does not explicitly differentiate from sibling tools like list_capabilities or preview_today_events.

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 about what the tool returns and how to use the URLs, and the phrase 'without schedule rows' implies a limitation. However, it does not explicitly state when to use this tool versus alternatives or give when-not-to-use guidance.

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

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 that paid fields are removed, explains the canonical URL behavior, and warns against constructing URLs from event_id or slug. It also clarifies the distinct nature of external_url for broadcasts/streaming services, which is valuable behavioral context beyond a simple read operation.

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 front-loaded with the core purpose in one sentence. The subsequent paragraph about URL usage is detailed but focused on critical pitfalls, and there is no redundant filler. It earns its length given the importance of the usage caveats.

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?

Even without an output schema, the description explains the most important output fields (url and external_url) and how they should be handled. It could be more complete by describing the overall response structure or behavior when no events exist, but for a simple preview tool with one optional parameter, it is largely sufficient.

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 already provides 100% coverage for the single date parameter, including its pattern and default behavior. The description adds no further parameter-level details, so the baseline score of 3 applies.

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 opens with a specific verb phrase, 'Preview up to three events for a Japan date with paid fields removed,' which clearly defines the action, resource, and scope. This distinguishes it from sibling tools list_capabilities and list_supported_competitions, which serve obviously different purposes.

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 implicitly clarifies when to use the tool (for previewing a date's events) and even provides detailed usage instructions for citing URLs. However, it does not explicitly state when not to use it or contrast it with alternatives, so it stops short of a full 5.

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