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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the closing "Read-only" adds nothing. What does add value is the interpretive constraint on prices — that they are AI-reported as written and must not be compared to the real price because promotions and variants change it — plus the distinction between discovery prompts (which do not name the product) and evaluation prompts, which materially affects how results should be read.

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?

Front-loading is strong — the core action and scope come first, then the payload breakdown. It is a single very long sentence with nested parentheses, which is dense to parse, but nearly every clause carries real content (prompt types, per-model attributes, competitor frequency) rather than 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?

With no output schema, the description carries the full burden of explaining return values, and it does so in detail: numbers, prompts by type, per-prompt-and-model answer attributes (naming, position, sentiment, quoted price, named products), and competitor frequency. For a read-only single-record fetch with complete parameter documentation, nothing an agent needs is missing.

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% and all three parameters are documented there, including the 7/30/90 enum for days and the id-or-name latitude for product and project. The description only obliquely touches the days parameter via "over the period" for competing products, so the baseline of 3 applies.

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 specific verb and resource ("Get one tracked product in detail") and then enumerates exactly what detail means: latest-update numbers, prompts, per-prompt/per-model answers, and competing products. That enumeration lets an agent distinguish it from list_products (which only lists) and compare_products (which compares multiple) without opening a schema.

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?

Usage is implied rather than stated: an agent can infer this is the single-product detail view versus compare_products, but the description never names an alternative or a condition that selects one tool over another. There is no guidance on prerequisites (e.g., whether the product must already be tracked via add_products) or on when a narrower tool like get_answer would suffice.

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