iddaa-mcp

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'Fetch' which implies a read-only operation, but does not explicitly state safety, required authentication, rate limits, or return format. Minimal transparency is provided.

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 a single, concise sentence that immediately states the tool's purpose. Every word contributes meaning, with no redundancy or filler.

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?

This is a simple tool with one parameter and no output schema, but the description lacks context about the return value shape, any limitations, or typical usage. It is minimally sufficient but leaves room for improvement in terms of what the agent can expect.

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 fully documents the sole parameter 'locale' with its enum values, default, and description. The tool description adds no additional parameter semantics, so the baseline for high schema coverage 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 uses a specific verb 'Fetch' and resource 'competitions' from the Iddaa sportsbook API, making the action unambiguous. It clearly distinguishes from sibling tools like get_events and get_detailed_events by targeting a different resource type.

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?

There is no guidance on when to use this tool versus alternatives, no context about typical workflows, and no mention of prerequisites or exclusions. The description simply states what the tool does without any usage direction.

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 disclosing behavioral traits. It only states what is fetched (events with org names and competition details), but does not mention whether results are paginated, how matching is performed, any rate limits, response structure, or side effects. This is a significant gap for a potentially list-returning 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 a single, front-loaded sentence with no filler words. Every phrase earns its place: 'Fetch events' states the core action, and the modifiers 'matched organization names and competition details' specify the enrichment. This is appropriately sized for a simple read operation.

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 lack of annotations and output schema, the description is too sparse to be complete. It doesn't explain return value shape, pagination, filtering behavior beyond parameter defaults, or how this endpoint relates to the sibling event tools. For a tool with five parameters and multiple nearby alternatives, more context is needed.

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 provides 100% coverage with descriptions for all five parameters, so the baseline is 3. The description itself adds no parameter-specific meaning beyond the schema; it does not clarify how 'st', 'type', 'limit', 'locale', or 'version' affect the enriched event output. The schema already does the heavy lifting.

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 uses a specific verb ('Fetch') and resource ('events'), and adds that it includes 'matched organization names and competition details', which distinguishes it from a plain event fetcher. However, it doesn't explicitly contrast with sibling tools like get_events or get_highlighted_events, so it's clear but not fully differentiated.

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 no guidance on when to use this tool versus alternatives like get_events or get_competitions. It gives no context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Fetch ...' with no mention of read-only guarantees, response format, pagination, authentication, rate limits, or other behavioral traits. The verb 'fetch' weakly implies retrieval but does not disclose meaningful behavioral details.

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 a single concise sentence with no filler or repetition. Every word contributes to identifying the tool's primary function.

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?

While the parameter schema is fully documented, the tool has no output schema and no annotations. The description omits return format, filtering behavior, and how this tool relates to sibling event tools, leaving important gaps for an agent relying solely on the description.

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 describes all four parameters (st, type, locale, version) with defaults and an enum for locale, achieving 100% schema_description_coverage. The description itself adds no parameter-level information, so the baseline 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 uses a specific verb ('Fetch') and identifies the resource ('sports events') and source API ('Iddaa sportsbook API'), clearly stating the core function. However, it does not differentiate this from sibling tools like get_detailed_events or get_highlighted_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 no guidance on when to use this tool versus alternatives. It lacks context such as intended use cases, exclusions, or mention of sibling tools, so an agent cannot determine when this is the right choice.

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?

The description gives no behavioral details beyond 'Fetch'. With no annotations, the burden falls entirely on the description to disclose behavior such as filtering, defaults, or response structure. The term 'highlighted' is undefined, and there is no mention of whether the tool returns a list, how pagination works, or any side effects.

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 a single, efficient sentence that clearly states the core action. It is front-loaded and free of filler. However, it is so brief that it sacrifices informative value for conciseness, but this still earns a high score for structure.

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 has 5 optional parameters, no output schema, and no annotations, the description is insufficient. It fails to explain what highlighted events are, how the parameters interact, or what the response looks like. A more complete description would clarify the filtering context and default behavior.

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 covers all 5 parameters with descriptions and defaults (e.g., 'st' sport type, 'limit' limit results). The description adds no additional parameter context, but since schema coverage is 100%, a baseline of 3 is appropriate. The description does not compensate for any ambiguity beyond the schema.

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 states a specific verb and resource: 'Fetch highlighted events'. It is clear this tool retrieves a subset of events, but it does not define what 'highlighted' means or differentiate it from sibling tools like get_events or get_detailed_events. The resource is identifiable but the distinction is left to the name.

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?

No usage guidance is provided. There is no mention of when to use this tool versus alternatives such as get_events or get_competitions. The description does not explain the intended scenario or how 'highlighted' relates to other event categories.

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?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It fails to mention the presence of simulation parameters (strategy, comeback, baseBet) that suggest non-trivial processing, nor does it confirm read-only behavior or describe any side effects. The description is a bare fetch statement with no transparency about actual tool behavior.

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 a single concise sentence with no redundancy. However, given the tool's complexity (six parameters including simulation logic), a one-sentence description is under-sized and leaves out critical information. It is structurally clean but not adequately informative for the breadth of the tool.

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?

The tool lacks an output schema, so the description should explain return values, but it does not. It also omits any mention of the simulation/filtering parameters (comeback, strategy) and how they affect the result. The description is too sparse for a tool with this complexity and no supplementary annotations.

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 description coverage is 100%, so all parameters have descriptions in the schema. The tool description adds no additional parameter semantics beyond what the schema already provides. The baseline score of 3 is appropriate since the schema does the heavy lifting.

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 (fetch), the resource (fixture data), and the scope (selected leagues from archive source). It is specific enough to convey the tool's core function, though it does not explicitly differentiate from sibling tools like get_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 no guidance on when to use this tool versus alternatives. It does not mention any preconditions, exclusions, or suggestions such as 'use get_events for live matches'. This leaves the agent without context for tool selection.

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