Formquote

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

Beyond the readOnly/idempotent annotations, it discloses that results are published list prices rather than live checkout quotes, that existing supplier credits can be counted, and enumerates the returned fields (ranked packs within comparable groups, cost for this job, unconfirmed items, price-check date, seller page). The date-staleness caveat is exactly the kind of behavioral context annotations cannot carry.

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?

Purpose and the when-to-use triggers are front-loaded in the first two sentences, and every later sentence carries distinct information (input constraint, credit handling, return shape, caveats). It is on the long side and could tighten the returns enumeration, but there is no redundant 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 takes on the burden of describing return values and does so concretely, including ranking groups and unconfirmed fields. Combined with the schema's full parameter documentation and the safety annotations, an agent has everything needed to invoke and interpret this tool.

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; the description earns extra credit by clarifying intent behind two parameters: the count-only rule for 'emails' and the fact that pre-held credits ('existing_credits') are factored into the comparison. It does not restate the goal/lang enum semantics, which the schema already handles well.

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 names a specific verb (compare) and resource (email verification prices), lists the exact suppliers covered, and scopes the input to a count of addresses. This clearly separates it from siblings like compare_font_licenses and compare_sound_effects_licenses.

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?

It gives explicit triggers ('when the user asks how much it costs to verify a number of emails, which service is cheapest for their list size, or how many credit packs to buy') plus an operational constraint ('Give only the number of emails, never the addresses'). It also states what the tool does not do (verify emails, buy anything), which routes the agent away from a purchase/verification sibling.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds genuinely non-obvious behaviour: results expose which requirements fail or are unconfirmed (pageview caps, PV vs UV, styles chosen at the foundry), that prices are published-only and 'nothing is bought', and that some dimensions are only partially confirmed. It stops short of describing price-source freshness or ranking effects of the goal parameter.

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 before caveats, and the closing 'Published prices; nothing is bought' is a well-placed boundary statement. The first sentence is dense and stacks enumeration inside a clause, but nothing is padding for a 14-parameter tool.

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 14 parameters and no output schema, the description carries the return-value burden and does: it says the answer contains per-offer published prices, failing or unconfirmed requirements, and the foundry page. Combined with the covered-fonts boundary and the no-purchase statement, an agent needs nothing more to call it correctly.

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 every parameter including goal, lang, traffic_metric and medium is already documented in the schema itself, and the baseline is 3. The description restates the input dimensions (users, websites, pageviews/unique visitors, years) but adds no syntax, units or interaction detail beyond 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 (check which licence a use needs and what it costs) and pins the exact covered corpus: six named offers from Pangram Pangram, Fontwerk, Grilli Type and Fontfabric. It also draws a hard boundary — 'Other typefaces are not covered' — so an agent can separate it from any broader pricing tool without opening the 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?

Gives explicit trigger conditions ('Use this when the user asks whether one of these fonts can be used on a website, on desktop, in print, in an app or game, in a logo or in paid ads') and an explicit exclusion with a fallback behaviour ('say so instead of guessing'). The when-not case is stated as an instruction, not left to inference.

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

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

Annotations already declare readOnlyHint/idempotentHint/non-destructive, so the safety profile is covered; the description usefully reinforces it with 'Published prices; nothing is bought' and adds context the annotations do not: a hand-checked set of 8 packs, an explicit return shape (price, eligible/conditional/not eligible, and licence points awaiting seller confirmation). It stops short of describing latency or freshness of pricing.

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 on purpose and scope, then usage conditions, then output contract, in a single tight paragraph. The catalogue of sound types ('UI clicks and snaps, motion-graphics sounds, desert wind and train ambiences, and a kettle whistle') is somewhat redundant with the intent enum, costing a little density.

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 an 8-parameter, read-only comparison tool with no output schema, the description supplies the missing return contract and an explicit failure-mode instruction ('say so if none fits'), plus the scope ceiling. An agent has everything needed to select and call this correctly.

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%, including all enums and defaults, so the schema already carries the parameter meaning and a 3 is the baseline. The description echoes the licence factors that map to seats, ai_use, commercial_use, standalone_resale and pure_sfx_percent but adds no syntax, format or precedence detail beyond 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 (compare/check) and resource (prices and licence fit for named sound effect packs), enumerates the exact scope (8 packs, three vendors) and says what comes back. It is unmistakably distinct from compare_font_licenses and compare_email_verification_prices.

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?

Gives a clear trigger: 'Use this when the user wants sound effects for an app, game, video or interface and asks what a pack costs or whether its licence allows their use', with the decision factors (commercial work, seats, AI training, resale, proportion) spelled out. It also sets a when-not boundary ('covers only these packs, not whole sound libraries'), though it does not name a sibling tool to use instead.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description adds real behavioural context beyond that: it discloses the return payload (each listed price, billing period, date checked, seller's page) and that Formquote's own notes stay in their original language, which explains the lang parameter's partial effect.

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?

Purpose is front-loaded and the trailing sentence handles routing. The middle enumeration of suppliers is long, but each name earns its place by telling the agent whether a given query is in scope; the parenthetical lists are the only mild density cost.

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?

There is no output schema, so the description carries the burden of describing returns, and it does: prices, billing period, check date and seller page. Combined with the routing guidance and the two documented parameters, an agent has everything needed to call it correctly.

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% and both parameters carry their own descriptions, so the baseline is 3. The description's enumeration of email verification, sound effects and font licences loosely mirrors the category enum, but it adds no new semantics and never mentions the lang parameter.

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 (list the Formquote catalogue) and enumerates exactly which supplier families are covered, so an agent can tell it apart from the compare_* siblings at a glance. The scope statement 'price evidence' is precise rather than generic.

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?

Explicitly names both the use case ('see what is covered', 'user asks for one of these suppliers' listed prices') and the alternative with the selecting condition ('To price a specific need, use the compare_* tools instead'). Nothing is left to inference.

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