parlayapi_source_quality

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

No annotations are provided, so the description carries the full burden. It usefully discloses that the endpoint is 'public' and does not require an API key, which is meaningful behavioral context. However, it does not describe what happens when freshness data is missing, whether there are rate limits, or how quality is computed, leaving some behavior undocumented.

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?

Two focused sentences, no fluff. The primary purpose is front-loaded, followed by the useful auth note and a concrete use case. Every sentence earns its place.

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 public metadata query with an output schema present, the description covers the essential context: purpose, access requirements, and when to use it. The only notable gaps are parameter meaning and explicit sibling alternatives, but they do not stop an agent from successfully invoking the tool.

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 0%, and the description does not mention the `limit` or `minutes` parameters at all. Although their names and defaults are somewhat self-explanatory, an agent has no guidance on how to choose values for these parameters or what constraints apply. Since the description does not compensate for missing schema docs, this dimension is weak.

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 a specific verb ('Return') and a distinct resource ('public per-source freshness and quality metadata'). This differentiates it from siblings like parlayapi_get_pricing or parlayapi_get_odds because it focuses on metadata quality rather than pricing, odds, or betting execution.

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 gives a concrete context: 'prove that rows are flowing from each source before choosing books for a customer workflow.' This tells an agent when the tool is useful, though it does not explicitly list exclusions or alternative sibling tools.

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