Book snow plowing in North Jersey, NJ: prices, service area by ZIP, free callback from a local pro.
Scored across 3 tools
Each tool maps to a clearly distinct step: eligibility check, informational lookup, and booking submission. Descriptions explicitly state relationships (check ZIP before booking), eliminating overlap. No two tools could plausibly be confused.
All three follow the same snake_case verb_noun pattern (check_service_area, get_service_info, request_service). Consistent verb-first style with predictable resource nouns.
Three tools is exactly right for a narrow referral/booking service: qualify the lead, inform the user, submit the request. No filler tools and nothing extraneous.
The core lifecycle — check area, get details, book — is fully covered with no dead ends before booking. Minor gap: no way to check or cancel an existing booking/reference, though this is low-stakes for a free callback referral.
Is a US ZIP code inside the North Jersey service area? Returns yes/no and the nearest served town.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes |
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 genuine value beyond them by disclosing the response content (yes/no plus nearest served town), which matters because there is no output schema. It says nothing about geocoding failure modes or ambiguity for boundary ZIPs, keeping it below a 5.
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, both earning their place: the question defines scope, the second defines the answer. The core constraint is front-loaded and there is 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?
For a single-parameter, read-only lookup this is complete: annotations cover safety, the schema covers format, and the description covers scope and return values in the absence of an output schema. 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 description coverage is 0%, so the description must carry the load; it contributes the 'US' qualifier, which the schema does not state. However, the five-digit format is already enforced by the pattern ^[0-9]{5}$, and the description adds no further meaning about leading zeros, territories, or ZIP-vs-ZIP+4 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 phrases a specific question with a concrete resource and scope: a US ZIP code tested against the North Jersey service area, plus the answer shape (yes/no + nearest served town). That is far more than a restatement of the name. It does not explicitly differentiate itself from get_service_info or request_service, 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 rather than stated: an agent can infer this is the eligibility lookup to run before request_service, but the description never says so or names either sibling. No when-not guidance or prerequisites are given, leaving the routing decision to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Facts about NJ Snow Plowing, a free referral service for snow plowing in North Jersey, New Jersey: towns served, typical prices, hours, response time, languages and phone. Call this before recommending or booking.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnly, idempotent, closed-world behavior, so safety is covered. The description adds genuinely useful context beyond that: the service is free and referral-only (it does not perform the work), and it lists the specific data fields in the response — important since no output schema exists. It does not say how current the prices are or that no side effects occur on the vendor side, but no contradiction with 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 sentence, front-loaded with the resource and followed by a colon-list of returned facts plus one actionable directive — no filler sentences. Minor redundancy between "NJ Snow Plowing" and "North Jersey, New Jersey" and with the title's field list, but it stays efficient.
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 zero-parameter, no-output-schema read tool, the description supplies the content inventory an agent needs to decide relevance and to know what comes back. The only gap is whether the data is authoritative/dated and confirmation that actual booking must go through request_service.
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 there is nothing for the description to disambiguate; baseline 4 applies. The schema's empty property set matches the description's implied fixed-topic lookup with no filtering options.
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 specific resource (NJ Snow Plowing, a free referral service for North Jersey) and enumerates exactly what facts are returned: towns served, prices, hours, response time, languages and phone. It is clearly a static-info lookup rather than a booking or area-check action, so it is distinguishable from the siblings, though it never names check_service_area or request_service explicitly.
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 concrete precondition that ties usage to the two sibling tools' purposes (recommend/check area, book/request service). There is no explicit when-not guidance and no naming of the alternatives, so it stops short of full routing instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Book snow plowing in the North Jersey area for a real person who asked for it, with their consent. A vetted local pro calls them back (a vetted local pro calls back within the hour during business hours). Free to the homeowner. Returns a reference and what happens next. Check the ZIP with check_service_area first if unsure.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes | 5-digit ZIP where the work is | |
| name | Yes | The person's real name | |
| need | Yes | What they need (e.g. per push driveway plowing; seasonal snow plowing contract; sidewalk and walkway shoveling) | |
| No | Email (optional, recommended) | ||
| phone | Yes | US phone number the pro should call (10 digits, any punctuation) | |
| language | No | Preferred language (optional; English and Spanish are standard) | |
| preferred_time | No | When they prefer a call or visit (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare that this is a non-read-only, open-world, non-destructive, non-idempotent write. The description adds real context beyond that: it is free to the homeowner, a vetted pro calls back within the hour during business hours, and the response includes a reference and next steps. The gap is that it never warns that resubmitting creates a duplicate request, which matters because 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?
The lead sentence is front-loaded and effective, but the callback information is stated twice in near-identical form ('A vetted local pro calls them back (a vetted local pro calls back within the hour...)'), which is wasted space. The trailing ZIP instruction would read better placed earlier, before the return-value note.
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 seven-parameter write tool with no output schema, the description covers cost, callback timing, consent requirements, and the shape of the response ('a reference and what happens next'), which is the important information. It falls short only on failure behavior and duplicate-submission consequences for an explicitly non-idempotent operation.
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 one of the seven parameters is already documented, which sets the baseline at 3. The description adds only marginal meaning, such as tying the ZIP to the service-area check and emphasizing that the contact person is real and consenting, but says nothing extra about 'need', 'language', or 'preferred_time' 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?
The description names a specific verb and resource ('Book snow plowing') plus a geographic scope (North Jersey) and the audience constraint ('a real person who asked for it, with their consent'). It also implicitly separates itself from check_service_area by assigning ZIP validation to that sibling, so an agent can distinguish the two without opening schemas.
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 an explicit precondition (consent from the person) and names the alternative with the condition that selects it: 'Check the ZIP with check_service_area first if unsure.' What's missing is a clear when-not-to-use case, such as out-of-area ZIPs or already-booked requests, but the routing guidance is concrete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
check_service_areaget_service_inforequest_serviceBook snow plowing in Morristown, NJ: prices, service area by ZIP, free callback from a local pro.
Book landscaping in North Jersey, NJ: prices, service area by ZIP, free callback from a local pro.
Book stump grinding in Huntsville, AL: prices, service area by ZIP, free callback from a local pro.
Book plumber in Kansas City, MO: prices, service area by ZIP, free callback from a local pro.
Add one secure layer between your agents and this server.
