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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it is a free-tier endpoint, the value is synthetic, it includes OT/SO goals, and it is the median of per-game primary totals across NHL books. This gives the agent a clear picture of what the number represents and its limitations.

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 compact and front-loaded: it opens with the free-tier and synthetic nature, then defines the resource, then gives concrete use cases. Every sentence earns its place, and the use-case list is a model of efficient guidance.

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 single-parameter read-only tool with no output schema, the description is nearly complete. It explains what the value means, how it is computed, and when to use it. The only minor gap is that it doesn't describe the exact response shape (e.g., whether it returns a number, an object with per-book lines, etc.), but with no output schema and a simple parameter, this is a small omission.

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%, so the schema already documents the single 'date' parameter as YYYY-MM-DD UTC with a default of today. The description adds the important nuance that the date is interpreted as US Eastern time ('for a given US Eastern date'), which is genuinely useful beyond the schema. However, it doesn't elaborate on edge cases like timezone conversion behavior, so a baseline 3 is appropriate.

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 states a specific verb ('Returns'), a precise resource ('synthetic daily NHL goals total'), and a clear scope ('for a given US Eastern date'). It also distinguishes itself from the MLB Grand Salami sibling by explicitly naming the hockey equivalent, so an agent can tell it apart from propline_get_mlb_grand_salami without opening schemas.

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 explicit use cases ('what's the total goal line for tonight's full NHL slate', 'did the Daily Goals Total go over yesterday', 'historical NHL daily-goals results for backtesting') and notes that no retail sportsbook quotes this as a single market, which clarifies when this synthetic metric is relevant. It also implicitly distinguishes from sibling tools like propline_get_odds and propline_get_scores by focusing on the aggregate daily total rather than individual games.

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