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

Beyond the read-only annotation, the description discloses important behavioral context: the tool is live in-season and opens NFL Week 1, a pro key is required, and every Kalshi prop is an 'X or more' contract. It also explains the call semantics (YES/NO) and what each returned row contains, which is especially valuable without an output schema.

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 information-dense with no filler: each sentence adds a distinct fact, the core purpose is front-loaded, and the return payload, lifecycle, auth requirement, and example queries all earn their 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?

With no output schema, the description compensates by explicitly listing the fields returned per row: contract, call, odds, Kalshi price, model projection, edge, and raw over/under inputs. It also covers availability timing, auth requirements, and example queries, making the tool fully usable from the description alone.

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 all three parameters well. The description adds market context and enumerates prop categories, but it does not add meaning to the limit, minEdge, or propType parameters beyond what is already in the schema. 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 clearly identifies the resource as NFL player-prop edges comparing the PredictionMarketsPicks projection against Kalshi lines, and enumerates the exact prop types covered. It distinguishes itself from sibling tools by specifying the Kalshi comparison and the row-level output fields, so an agent can select it confidently.

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-case queries such as 'NFL player prop edges', 'best NFL props today', and 'passing yards over under', which tells the agent when this tool is appropriate. It does not name alternative siblings or state when not to use it, so it misses the explicit exclusion part of a 5.

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