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

Beyond the readOnlyHint annotation, the description discloses important runtime semantics: only OPEN rows carry tradeable prices, SUSPENDED or CLOSED rows must never be presented as live, null American prices must not be rendered as numbers, and the result is a rolling ~20-row window rather than the full live board. This is exactly the kind of behavioral context annotations do not provide.

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 definition, followed by use cases and hard operational caveats. It is long but every clause earns its place by preventing misuse — the warnings about OPEN/null prices and the rolling window are high-value, not 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?

Even though there is no output schema, the description covers return semantics well enough to use the tool correctly: row statuses, American price nullability, live window size, and live_total as a coverage indicator are all disclosed. It also clarifies persistence and scope, leaving no critical 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?

Schema description coverage is 100%, with both parameters fully documented: limit has bounds and default, and sport has case-insensitive substring behavior. The description adds window context around the limit but does not need to repeat the schema; this lands at the baseline for fully covered parameters.

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 precise definition: in-play rows from the FanLine Wire tape, specifically markets that just ticked while a game is running, with American prices. It clearly separates this live, current-only tool from siblings like get_prematch_fixtures and excludes historical or multi-book comparison tools.

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 lists intended use cases — live odds displays, in-play modelling, feature engineering, cross-book arbitrage checks — and explicitly states exclusions: not bet-placement, not multi-book comparison, not historical archive. It also directs the agent to read live_total for full coverage, which is concrete guidance beyond just saying what the tool is.

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