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

With no annotations, the description carries the full burden and does add meaningful behavioral context: data comes from 'stored snapshots' and costs '$0.01 USDC per call on Base'. It does not explicitly state read-only safety, auth/payment mechanics, rate limits, or data freshness beyond 'stored snapshots'.

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 compact sentences: the purpose and output metrics are front-loaded, and the cost is appended without waste. Every phrase carries useful 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?

It covers the core purpose, output metrics, data source, and cost, which is enough to understand the tool at a high level. However, for a paid tool with no output schema and 0% parameter description coverage, it omits how 'days' and 'limit' behave and does not describe the response shape beyond naming the metrics.

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% for the two parameters 'days' and 'limit', and the description provides no information about either. It neither explains the time window semantics nor what the limit applies to, so it does not compensate for the schema gap.

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 gives a clear resource and aggregation scope: 'Aggregated edge trends per event from stored snapshots' with specific metrics like min/max/avg taker edge and best expected maker edge. It implicitly distinguishes itself from the raw sibling get_odds_trends via 'summary' and 'aggregated', but it never explicitly names or routes between the two.

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 explicit guidance on when to use this summary instead of get_odds_trends, estimate_fill, or other siblings. An agent can infer it is for aggregated overviews, but no alternatives or exclusions are stated.

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