MapleV Tesla Collision Parts

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

Annotations already declare readOnly/non-destructive, so safety is covered; the description adds real behavioral context — the two service tiers, the 2-hour metro rush, freight quoted at checkout, and the free-delivery threshold on local orders. It stops short of covering rate limits or exact fee values, but for a read-only lookup that's minor.

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-loads the core contract (city in, options with ETA/cut-off/fee out) in the first sentence, then layers geography and fee rules. Slightly long and the sample questions are decorative, but every sentence carries usable 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 no output schema, the description fully carries the return contract (ETA, cut-off time, CAD fee) plus the regional behavior that determines the answer's shape. An agent has everything needed to call this correctly and interpret the result.

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 city, province and orderSubtotalCAD are already documented with examples; the description roughly restates the province guidance rather than adding new syntax. Baseline 3 applies since the schema does the heavy lifting.

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 concrete verb+resource (return MapleV's delivery options) and a precise geographic scope (any city in Canada), then names exactly what comes back: ETA, cut-off time, CAD fee. The local-area vs. rest-of-Canada split further distinguishes it from the catalog siblings, which do entirely different things.

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 when-to-use framing via two sample questions ('can MapleV get this part to my shop in Abbotsford today?', 'how long does shipping to Calgary take?') and tells the caller when the province argument matters. It doesn't name alternatives, but the sibling tools (get_part, search_parts, list_categories) aren't competing for this task, so routing guidance is sufficient.

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 read-only, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds useful context about what is returned—grade, fitment, and CAD list price—which is valuable because there is no 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 two front-loaded sentences that move from purpose to return content with no waste. Every sentence earns its place for a simple lookup 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?

For a one-parameter lookup with rich annotations and no output schema, the description is complete enough: it covers accepted input forms and summarizes the returned fields. No further detail is required for an agent 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%, so the single identifier parameter is already fully documented with examples. The description reinforces accepted formats ('catalog id', 'Tesla OE part number / variant') but adds only marginal meaning beyond the schema, fitting the baseline 3.

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?

It states a specific verb ('Look up'), resource ('a single MapleV part'), and supported identifier types, including examples. The word 'single' implicitly distinguishes it from the sibling search_parts, so an agent can tell the retrieval scope apart 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?

The description implies usage by explaining that it takes a catalog id or OE number, but it does not explicitly say when to use this tool instead of search_parts. There are no named alternatives or when-not conditions, leaving routing 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 readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds that this is an exhaustive enumeration that includes per-category SKU counts, giving useful context about the response content beyond the annotations.

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 verb, the resource, the domain, and the returned data with no 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?

No output schema exists, so the description carries the burden of describing returns, which it does by stating categories come with SKU counts. Adequate for a no-parameter list tool, though ordering, pagination, and whether empty categories appear are unstated.

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, so the schema imposes no semantic burden and there is nothing for the description to disambiguate. Baseline 4 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?

States a specific verb (List) and resource (part categories) scoped to the MapleV Tesla collision catalog, and adds the payload detail (SKU count per category). The resource is clearly distinct from the sibling tools get_part, search_parts, and get_delivery_options.

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?

No explicit when-to-use/when-not guidance or alternative routing is given. For a zero-parameter enumeration tool the intended use is strongly implied, but the description never says to call it before search_parts/get_part or when it should not be used.

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, closed-world, so safety needs no restating. The description adds genuine behavioral context: keyword matching order ('parts matching every word are returned first') and the fallback behavior when nothing matches exactly, which is not derivable from annotations.

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 sentences, zero waste: the searchable surface is front-loaded and the return shape follows. Nothing extraneous for an agent to parse.

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 usefully enumerates the returned fields, and the ranking/fallback behavior is disclosed. It is nearly complete, though it does not state result-limiting behavior beyond the schema's limit parameter or ordering guarantees.

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 all five parameters (including multilingual handling, 7-digit OE base matching, and model-year-as-fitment-filter) are already documented in the schema. The description mostly echoes schema content, so the baseline 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?

Names a specific verb (Search) and resource (MapleV Tesla Model 3/Model Y collision parts catalog) and states the matching dimensions. The catalog scope and the returned fields (names, OE numbers, grade, category, CAD list price) clearly separate it from siblings get_part and list_categories.

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?

Implicit that this is the discovery tool versus get_part (single-part lookup) and list_categories, but no explicit when-to-use/when-not or prerequisite is stated. An agent can infer the routing from the siblings, but the description does not spell it out.

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