cfbd_betting_lines

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

The description goes well beyond the annotations (readOnlyHint, openWorldHint, idempotentHint) by disclosing that the return shape is from vendor docs and 'has NOT been verified against a live response,' advising to 'inspect the actual payload.' It also explains the significance of `*Open` fields for CLV comparisons and notes the auth requirement (CFBD_API_KEY). This adds valuable context without contradicting the safe-read annotations.

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 well-organized and front-loaded: it opens with a one-sentence purpose, then presents the return shape, a caveat about verification, an example, and auth requirement. Each section serves a clear purpose and there is no fluff. It is longer than average but every sentence earns its place due to the tool's complexity and the unverified data warning.

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 that there is no output schema and the return payload is complex (nested `lines` objects), the description compensates by providing a detailed return shape, explaining it is approximate, giving an example call, and stating the auth key requirement. It also clarifies the `*Open` versus closing semantics, making it complete for an agent to understand both the call and the response structure.

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?

Input schema covers all four parameters (team, week, year, seasonType) with descriptions, providing 100% coverage. The description does not elaborate on parameter meanings or formats beyond the schema, except for an example using year and week. This example adds a hint of usage but does not substantially enrich parameter semantics, aligning with the baseline for full schema coverage.

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 identifies the tool as retrieving 'Historical betting lines per game from multiple books — spread, over/under and moneyline.' It specifies the resource (betting lines), the scope (per game), and the content (spread, totals, moneyline), which distinguishes it from sibling tools like cfbd_games or odds aggregation tools. The phrase 'The college-football backtesting dataset' further clarifies its intended use.

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 sets clear context: it is for historical betting lines and backtesting, and it provides a concrete example query (2024 week 1 lines). However, it does not explicitly state when to prefer this over alternatives such as cfbd_games or theoddsapi, nor does it mention exclusions. The usage intent is implied but not explicitly contrasted with other tools.

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