Vegas Mobile Mech — book mobile mechanic in Las Vegas

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

Annotations already declare readOnly, idempotent and a closed-world scope, so safety is covered. The description adds the return behavior (yes/no plus nearest served town), which is meaningful context given no output schema exists.

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 short sentences, front-loaded with the core question, followed by the answer shape. Zero wasted words.

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 boolean lookup with no output schema, the description supplies both purpose and return shape, which is nearly everything an agent needs. Edge-case behavior (invalid or out-of-country ZIPs) is the only omission.

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 0% for the single parameter, so the description must carry the load: it identifies the input as a US ZIP code, complementing the schema's 5-digit pattern. It does not clarify handling of non-US or malformed codes.

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 check: whether a US ZIP code falls inside the Las Vegas service area, which separates it from get_service_info and request_service by intent. It lacks an explicit pointer to those siblings, but the verb+resource is unambiguous.

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 question framing implies this is a pre-qualification check before requesting service, but the description never states when to prefer it over get_service_info or request_service, nor when-not to use it. Usage is inferable rather than 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 declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds that this is a free referral service and lists the returned facts, but says nothing about data freshness, sourcing, or whether the listed prices/hours can change.

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 entity, its nature, and the returned fields, closing with an actionable imperative. The enumerated list is long but each item is informative 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 and no parameters, the description compensates by enumerating exactly what facts come back (towns, prices, hours, response time, languages, phone). An agent knows what to expect from a call; only freshness/caveats on that data are unaddressed.

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 baseline of 4 applies; there is no parameter semantics burden to carry.

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 resource (facts about Vegas Mobile Mech) and enumerates the content returned: towns served, prices, hours, response time, languages, phone. It is distinguishable from request_service, though 'towns served' overlaps with the sibling check_service_area, so the boundary between the two read tools is not fully drawn.

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?

'Call this before recommending or booking' gives a clear usage trigger and implicitly routes booking to request_service. It never names check_service_area as the alternative for area questions, so the when-to-use guidance is clear but not exhaustive.

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?

With annotations covering safety (non-read-only, non-idempotent, open-world, non-destructive), the description adds real value beyond them: the call is free to the homeowner, a vetted pro calls back within the hour during business hours, and a reference is returned. It does not warn that repeated calls may create duplicate requests, which matters given idempotentHint=false.

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 routing hint comes last, which is good structure. However, the parenthetical 'a vetted local pro calls back within the hour during business hours' nearly repeats the preceding clause, wasting space in a description that should make every clause count.

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 booking-style tool with no output schema, the description covers outcome ('returns a reference and what happens next'), cost, callback timing, service area, and the sibling check to perform first. Enough for an agent to invoke correctly, though duplicate-request behavior remains unaddressed.

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 seven parameters are already documented in the schema; the description adds only the consent framing and implies the ZIP matters. Baseline 3 is appropriate since the schema does the heavy lifting with no extra syntax or format guidance added.

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 (Book) and resource (mobile mechanic), plus scope (Las Vegas area) and a precondition (real person who asked, with consent). It also names the sibling tool check_service_area for ZIP verification, so an agent can distinguish it from siblings 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 a clear precondition (only for a real person who asked, with their consent) and routes the agent to check_service_area first when the ZIP is uncertain. The 'when not to use' case is only implied by the consent constraint rather than stated as an exclusion.

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