skipodds

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

With no annotations, the description must disclose behavioral traits. It mentions the time window constraints and that data consists of timestamped snapshots, but it omits important aspects like whether the operation is read-only, rate limits, data freshness, or any side effects. This is minimal transparency for a data retrieval 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, each serving a distinct purpose: the first defines the core functionality, and the second clarifies parameter limits. No redundant or irrelevant information is present, making it 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?

Given the absence of an output schema, the description partially compensates by stating the output type ('timestamped consensus snapshots'). However, it does not describe the structure of the returned data (e.g., fields, format), which would be helpful for an agent to interpret results. It is adequate but not comprehensive.

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%, providing baseline clarity. The description adds value by specifying tier-dependent maximums for the 'hours' parameter ('max 72, or 336 on the Scale tier'), which goes beyond the schema's default mention. This additional constraint enhances parameter understanding.

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 returns 'How the SkipOdds Index moved over time for one fixture — timestamped consensus snapshots.' It specifies the resource and the nature of the data, effectively distinguishing it from sibling tools like list_fixtures or get_fixture. However, it lacks an explicit verb like 'get' or 'retrieve,' which slightly reduces clarity.

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 some usage hints through parameter details (e.g., 'hours defaults to 24 (max 72, or 336 on the Scale tier)' and 'Omit for soccer' via schema), but it does not explicitly state when to use this tool over alternatives or when not to use it. No direct comparison to siblings is given.

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 provided, so description carries full burden. It discloses that the tool returns de-vigged consensus data and lists fields. Does not mention side effects, rate limits, or error cases, but is adequate for a read-only retrieval 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?

Single sentence with no filler, efficiently conveying purpose, key inputs, and output nature.

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 simple two-parameter tool with no output schema, description sufficiently covers purpose, return value, and parameter usage. No gaps remain for agent selection.

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 100%, but description adds meaningful context: ID source ('from list_fixtures') and default behavior for sport ('Omit for soccer'). This goes beyond raw schema definitions.

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?

Description clearly states it retrieves a single fixture by ID and lists specific returned metrics (fair probability, fair odds, bookmaker count, last update). Distinguishes from siblings like 'list_fixtures' which lists many, and 'fixture_movement' which tracks changes.

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?

Specifies that ID comes from list_fixtures and provides explicit guidance on the sport parameter ('Omit for soccer' and 'Any other sport must be named explicitly'). Lacks explicit when-not-to-use or alternative tools.

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 present, and the description provides minimal behavioral information. It mentions the tool outputs probabilities and fields, but does not disclose side effects, idempotency, or whether it is read-only.

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 concise at two sentences with no unnecessary words. However, it could be restructured to separate the list behavior from the detail behavior for clarity.

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 no output schema, the description partially explains the return structure (list of tournaments with probabilities, or full field for one). It is insufficiently explicit about whether the list vs. detail is based on the presence of the key, leaving some ambiguity.

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 the key parameter, and the description adds meaning by explaining that passing a key retrieves the 'full priced player field' for that tournament. This adds value beyond the schema's minimal description.

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 specifies the tool returns golf tournaments with normalized outright-winner probabilities and can provide full player field for a specific tournament. This distinguishes it from siblings like tournament_outrights, though the verb 'Pass' is ambiguous.

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 explicit guidance on when to use this tool versus siblings. It implies that passing a key retrieves full details, but does not explain scenarios or when to prefer tournament_outrights.

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 present, so the description carries full burden. It explains the de-vigged odds concept and data breadth (13 sports, 69+ bookmakers), which adds transparency. However, it omits details on caching, freshness, or pagination, leaving some behavioral aspects unclear.

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 exceptionally concise: two sentences that pack the core purpose, technical concept, coverage, and a critical usage hint. No word is wasted, and key information is front-loaded.

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 list tool with three well-documented parameters and no output schema, the description adequately explains the data returned (fixtures with de-vigged odds) and coverage. It lacks details on sorting/ordering (upcoming vs recent) and response format, but overall it provides sufficient context for an agent to assess usage.

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 100% with descriptions for all three parameters. The description adds meaningful context: the sport parameter can be omitted for soccer and that 'any other sport must be named explicitly' (though this slightly contradicts the limited enum). This goes beyond the schema's field 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 lists upcoming and recent fixtures with the SkipOdds Index, specifying coverage of 13 sports from 69+ bookmakers and explicitly noting that omitting the sport parameter yields soccer. It effectively distinguishes itself from sibling tools like fixture_movement and get_fixture.

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 a key usage hint (omit sport for soccer) but does not explain when to use this tool versus alternatives like get_fixture or fixture_movement. The agent must infer from sibling names without guidance on trade-offs or prerequisites.

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 provided, so description carries full burden. It discloses normalization and exclusion of eliminated teams, but does not mention read-only nature, rate limits, or what happens if competition slug is invalid.

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?

Single sentence that front-loads purpose and key behavioral details. No redundant information.

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?

Adequate for a simple one-parameter tool. Could optionally mention return format (e.g., decimal or percentage) but not strictly necessary given tool simplicity.

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 100% for the single parameter 'competition'. The description adds value by connecting the parameter to soccer tournament context and explaining normalization behavior, going beyond the parameter schema alone.

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 returns 'soccer tournament-winner probabilities' and specifies they are 'normalised across the still-alive field (eliminated teams excluded).' This distinguishes it from sibling tools like fixture_movement or get_fixture which deal with fixtures.

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 guidance on when to use this tool versus alternatives (sibling tools are listed but not explained). No mention of prerequisites or limitations.

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