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

Annotations already declare it read-only, idempotent and non-destructive, yet the description still discloses real behavioral traits: null prices are never guessed, rows are ranked by price.monthly, VAT is added where the list excludes it, web-vs-app comparisons are sourced from store prices, and non-regular plans must not be presented as the generic cheapest. These are decision-relevant facts an agent could not infer from annotations alone.

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-loaded with purpose, but the rest is a single massive run-on paragraph packed with nested parentheticals and long enumerations of vendors. Much of the content earns its place, yet the lack of sentence breaks or grouping makes it hard to parse and far from concise.

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?

Given 14 parameters, a nested usage object and no output schema, the description does substantial work: it documents row fields (source_url, verified_on, fx_date, price.*, inAppPrices, data_location, promo, kind) and the usage-cost outputs. Coverage is close to complete; only the tier/purpose/locale parameters rely wholly on the schema.

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 coverage is 100%, so the baseline is 3, but the description meaningfully extends the usage parameter: messages_per_month with default input/output tokens, cache_share, batch, and the resulting usage_cost, usage_breakdown and break_even_messages outputs. With no output schema, explaining what usage produces is genuine added value; tier, purpose, locale and currency are left to the schema.

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?

States a specific verb and resource: prices of digital services for a buyer's country, cheapest first, with a detailed list of the ten supported categories. An agent can tell this is the digital-subscription comparison tool. It never names a sibling (e.g. digital_price_history or cheaper_abroad) to distinguish scope, so it stops short of a 5.

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 by the category list and by lines like 'omit for the plain price list' and 'usage turns the list into a cost of that use', which tell you when to supply usage. But there is no explicit when-to-use/when-not guidance and no routing to related tools such as digital_price_history for past prices or cheaper_abroad for cross-country checks.

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