B.R.M Chronographes - Watch Configurator

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

Adds substantial context beyond annotations: the email-plus-confirm-button flow, the 72 h link validity, payment methods and their thresholds, that no card details pass through the tool, that the operator never pays or commits, that price/VAT follow the delivery country, and a per-email daily order limit. This is far richer than the destructive/idempotent/openWorld hints 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 the action and the gating condition, then the confirmation flow, then prohibitions. It is dense and long, but nearly every clause carries behavioral information an agent would otherwise get wrong; only the payment-method enumeration could be tightened.

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 consequential write tool with nested objects and four required params, the description covers consent, the deferred-confirmation model, payment handling, rate limits, idempotency and the delivery-date prohibition. Since an output schema exists, return values need not be described.

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?

Reported schema coverage is 0%, so the description must compensate; it meaningfully explains user_consent (agreement to share name/email/address with B.R.M), idempotency_key (makes retries safe) and ties shipping_address to price/currency/VAT. It leaves lang and the customer object's individual fields unaddressed, so it is not fully compensating.

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 ('prepares an order of this configured watch') plus the crucial scope boundary that it does NOT place the order, which separates it from quote_configuration and get_order_status. An agent can identify what this does 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 an explicit gating condition: call only when the user explicitly asked to order and agreed to share name, email and address (user_consent=true), with clear exclusions (never ask for payment details, never promise a delivery date). It does not name sibling alternatives such as quote_configuration for price checks, so it falls short of the top tier.

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 idempotentHint=true, destructiveHint=false, and openWorldHint=true, so 'Idempotent' is largely redundant. However, the description adds genuine behavioral context beyond annotations: it explains that the preview page is public and shared by every identical configuration (an exposure/privacy trait no annotation conveys), and 'Sharing is not ordering' clarifies that no purchase side effect occurs.

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?

A single tight paragraph with the return contract front-loaded and no filler sentences. The nested parentheticals are long but each clause carries distinct information (purpose of each URL, who consumes it).

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?

An output schema exists, so return values did not strictly need explaining, yet the description's account of what each URL is for is the most useful part of the definition. The remaining gap is the input side – no guidance on where configuration.model and options come from – for a nested-object tool with a complex enum parameter.

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?

The description mentions no parameters at all. The nested schema does document model, options, and engraving, but the top-level lang (12-value enum) and view (0-29) have no descriptions anywhere, and with reported schema description coverage of 0% the description needed to compensate for the input contract. It does not.

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?

Names a specific verb and resource (create a share link that reopens 'this exact watch') and details both artifacts produced (configurator_url, preview_url). It does not explicitly contrast itself with siblings like create_order or render_configuration, though the phrase 'the link meant for the user' does real work in distinguishing the two outputs.

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: 'this is the link meant for the user' versus preview_url's public presentation page gives a selection rule between the two outputs, and 'Sharing is not ordering' hints that create_order is the sibling for purchases. There is no explicit when-to-use statement and no stated prerequisite that a model_id/option_id must first be obtained, so the agent must infer the workflow.

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 establish readOnly, idempotent, non-destructive and closed-world behavior, so the safety profile is covered. The description adds semantic meaning (option_id is opaque, name is the user-facing label, depends_on means conditional existence) but discloses nothing operational such as behavior for an unknown model identifier or what lang changes. Useful but modest value on top of structured data.

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?

It is a single compact sentence with no filler, so nothing is wasted. However it is a noun-phrase fragment with no stated subject or verb, which makes the first read ambiguous about whether the tool returns these things or accepts them as input.

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?

Because an output schema exists, the description need not restate return fields, yet it spends its whole length doing exactly that while saying nothing about the required 'model' argument's expected format or the effect of 'lang'. An agent can call it, but the input side and the routing among siblings remain underspecified.

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 0%, with a required 'model' string and a 'lang' enum that the description never mentions. The description only explains fields of the returned payload (option_id, name, exclusive_group, depends_on), which are not parameters of this tool, so it does not compensate for the documentation gap on the two inputs.

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 the resource and its concrete parts: components, options with their fields, mutual exclusions (exclusive_group) and dependencies (depends_on). That is specific enough for an agent to know this tool returns the full configurable breakdown of one model. It never differentiates itself from siblings like list_models or quote_configuration, 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?

There is no when-to-use guidance, no prerequisite, and no mention of alternative tools such as list_models (to discover models) or quote_configuration (to price a selection). The agent must infer the usage context entirely from the name and sibling list.

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 cover readOnly/idempotent/non-destructive, so the bar is lower; the description still adds meaningful context by stating "No customer data" (PII exposure) and enumerating every terminal and in-progress state. It does not, however, say what happens with an unknown or expired key.

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 scope are front-loaded in the first clause, followed by two tight, non-redundant sentences. The state enumeration is long but is genuinely informative rather than padding.

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?

An output schema exists, so return formatting need not be explained, and annotations fully cover the safety profile. What an agent needs to call it correctly — the identifier source and the absence of PII — is present.

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 0%, so the description must carry parameter meaning. It does explain where order_id and idempotency_key come from, but it leaves the interaction ambiguous — required parameters are technically 0, yet the tool is useless without one of them, and no precedence rule is given when both are supplied.

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?

"Returns only the state of the order" states a specific verb (returns) and resource (order state), and enumerates the exact values so the agent knows the granularity of the response. It also explicitly scopes out sibling data ("No customer data") and ties itself to create_order as the producer of the id.

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?

"Pass the order_id returned by create_order, or the idempotency_key you used" tells the agent exactly when and how this tool fits into the workflow after create_order. No explicit when-not guidance, but no sibling competes for this purpose either.

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=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds the useful detail that prices are EUR inclusive of French VAT, which is genuine behavioral context, but it does not disclose ordering, result size, or how the rendered picture is delivered.

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?

A single front-loaded sentence that names the resource first and then the returned attributes. No filler, no repetition of the title, nothing that fails to earn its 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?

For a parameterless, read-only listing tool with full annotations and an existing output schema, the description covers what an agent needs to select it. The remaining gap is the lack of routing guidance against the many sibling tools that touch the same model domain.

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?

The tool takes zero parameters, which is the baseline-4 case per the scoring rules. The description correctly implies a no-argument listing and adds nothing misleading about inputs.

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 (Returns) and resource (configurable watch models) and even enumerates the payload fields (base price, diameter, rendered picture). It is clear what the tool does, but it never distinguishes itself from siblings like describe_model or render_configuration, which also deal with model data.

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 only implied: an agent can infer this is the catalog-listing entry point before configuring or rendering. There is no explicit when-to-use statement, no mention of when describe_model or render_configuration should be preferred instead, and no prerequisites noted.

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?

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses substantive behavior: currency is fixed by the delivery country and cannot be chosen, EU deliveries carry French VAT while non-EU carry 0% with duties payable by the buyer, and the result is indicative rather than authoritative. This is exactly the kind of pricing/tax context annotations cannot convey.

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?

A single dense sentence that front-loads the core behavior (currency determined by delivery country) and then layers tax regime and the non-binding caveat. Every clause carries information an agent needs; nothing is padding.

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 an output schema present, return values need no explanation, and the description covers the two things schemas can't: tax treatment and the indicative/non-authoritative nature of the price. The undocumented lang parameter and the unexplained display_currency are the only meaningful gaps.

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 only 25%, so the description must compensate. It usefully clarifies that country drives the billing currency (delivery-country semantics), but gives no meaning for lang or display_currency — and "the currency cannot be chosen" sits in unexplained tension with the existence of a display_currency 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?

The description states a specific outcome — a price quote in the delivery country's billing currency, with the applicable tax regime. It is clearly separable from siblings like validate_configuration, render_configuration, and describe_model, though it never names them. Purpose is unambiguous but lacks explicit sibling differentiation.

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?

"Indicative and non-binding; the checkout on brm-chronographes.com is authoritative" implies this is a preview rather than a committing operation, which hints at when to use it. However, it never says when to prefer validate_configuration or create_order, or that this should precede an order. Usage is implied, not stated.

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 cover safety, idempotency and closed-world behavior, and the description adds real context beyond them: the JPEG output format and the 30-view rotation model (12° per step). It does not mention render latency, errors, or how width affects the image, but the additions are substantive.

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?

Two tight sentences with zero filler; the primary purpose is front-loaded and the view semantics follow immediately as the most actionable detail.

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?

An output schema exists, so return values need no explanation, and the description covers the most important behavioral nuance (view rotation) plus output format. The only real gap is the meaning of 'width' and any prerequisite chaining, which the nested schema partially covers by pointing at list_models/describe_model.

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?

Top-level schema descriptions are absent, and the description fully explains only one of three params: view (0 = three-quarter view, 30 views rotating 12° each). 'width' is left unexplained (no pixels/aspect-ratio meaning), and 'configuration' relies on the nested schema's own descriptions of model/options/engraving.

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 (composes/renders) and resource (photographic rendering of the configured watch), with the output format (JPEG) named. It is clearly distinct from siblings like quote_configuration and validate_configuration, though it never explicitly contrasts itself with them.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative sibling is named. The phrase 'the configured watch' only weakly implies a prerequisite configuration must already exist.

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?

Beyond the annotations, it discloses that the message cannot be recalled once sent, that explicit consent (user_consent=true) is mandatory, and that usage is limited to a few requests per day. These are exactly the behavioral traits (irreversibility, rate limit, auth/consent) the annotations alone do not convey, and they are consistent with destructiveHint=true.

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 the core action and the kind taxonomy, then the hard constraints. The parenthetical glosses are dense but each adds real meaning; a slight trimming of the kind explanations would improve it without losing information.

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 an output schema present, return values need not be described, and the annotations carry safety signals. The description supplies the consent, rate-limit, and irreversibility context an agent needs, but the role of configuration and idempotency_key in a submission flow is left implicit.

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 only 13%, so the description has to compensate, and it does so for the most consequential fields: it defines all three 'kind' enum values and ties user_consent to the email-sharing agreement. It leaves lang, country, idempotency_key, and the contact sub-fields unexplained, so a residual gap remains.

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 ('sends the user's request to the B.R.M team') and enumerates the three request kinds, so the agent can tell it apart from create_order, quote_configuration, and validate_configuration. The explicit 'Never an order, never a payment' boundary further sharpens the distinction.

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?

Explains when each kind applies ('quote' = personalised quote by email, 'special_request' = anything the configurator does not offer) and states the consent precondition and the rate limit. It stops short of naming which sibling tool to use first (e.g. describe_model/validate_configuration before submitting), so it is clear but not fully routing.

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 establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description still adds real value beyond that: it discloses the resolution of defaults/exclusions/dependencies, the valid=false contract, and the concrete error codes (unknown_option, dependency_unmet) and warning code (exclusive_conflict) that make the result actionable.

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?

One dense sentence that front-loads the core behavior (resolves defaults/exclusions/dependencies) and then the return contract. Every clause carries information; nothing is padding.

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?

An output schema exists, so the description is not obligated to explain return values, yet it usefully summarizes them. Combined with the annotations, an agent knows this is a safe, repeatable pre-flight check. The one missing piece is the relationship to quote_configuration, which matters given the overlapping price output.

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 reported at 0%, and the description compensates for none of it: the top-level 'lang' parameter is never mentioned, and neither 'configuration', 'options' nor 'engraving' is explained in the description text (only the nested schema does that). An agent gets no semantic help from the description on how to shape the input.

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 gives a specific verb+resource (validate/resolve a configuration) and enumerates what it returns: resolved defaults, errors, warnings, selections and total price. It does not, however, differentiate itself from the sibling quote_configuration, which plausibly also returns a price — the agent has to guess the boundary between them.

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?

There is no when-to-use guidance at all: nothing says to call this before create_order, nor how it differs from quote_configuration or describe_model. The only routing signal is implicit in the error/warning vocabulary.

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