CleanOfficeKC Commercial Cleaning

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

No annotations are supplied, so the description carries the full behavioral burden and falls short: it doesn't say what the answer looks like (boolean, object, boundary/caveat details), whether results are authoritative, or any rate or auth constraints. Only the geographic scope is disclosed.

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 sentence, front-loaded, no redundant phrasing. Brevity here is appropriate, though it edges into under-specification rather than elegance.

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, no annotations, and an undocumented required parameter, the definition is missing everything an agent needs beyond the high-level intent: accepted location format and return shape. It is complete on scope and incomplete on operability.

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 explain the single 'location' parameter — yet it says nothing about whether to pass a street address, city/state, ZIP, or coordinates. The most consequential ambiguity in the tool is left entirely unresolved.

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: checking whether a site falls inside the Kansas City metro service region. This is distinguishable from siblings like get_quote_estimate and get_service_info, though it never references them by name.

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 when-to-use or when-not-to-use guidance, and no mention of the sibling tools (get_quote_estimate, get_service_info, request_walkthrough) that an agent might otherwise pick. The purpose implies a pre-qualification check, but that is inference, not guidance.

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 no annotations, the description carries the full burden. It does usefully disclose that the figure is 'rough' and 'non-binding', which sets expectations correctly for a pricing tool, but it says nothing about what happens when location falls outside the metro, whether it errors or assumes KC, or whether a service-area check is a prerequisite.

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 with no filler; every qualifier ('rough', 'non-binding', 'recurring commercial', 'Kansas City metro') narrows interpretation. It is tight, though the compactness comes at the cost of the guidance an agent needs before invoking 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?

Four parameters, no annotations, and no output schema mean the description must explain what comes back. It does not indicate whether the response is a range, a per-square-foot rate, or a monthly total, nor how the optional location and facility_type alter the result — a meaningful gap for a pricing 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 75% and visits_per_week already has a clear example mapping. The description adds real meaning by constraining location to the KC metro and framing the estimate as recurring commercial work, but it does not explain how facility_type influences pricing or clarify the units of the returned figure versus the per-square-foot request.

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 precisely: a rough, non-binding cost-per-square-foot estimate for recurring commercial cleaning in the Kansas City metro. It is a noun phrase without a verb, but the scope and output unit are specific enough to separate it from check_service_area, get_service_info, and request_walkthrough.

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 through scope qualifiers (commercial, recurring, KC metro), which implicitly rule out one-time residential jobs or out-of-area requests. However, no when-to-use statement or alternative is named — notably check_service_area, which an agent might reasonably call first in the same 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?

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing: no statement that this is a read-only, zero-argument static lookup, no indication of whether the content is dynamic or cached, and no hint at return shape. The enumerated topics hint at what content appears but not how it is structured or when it is stale.

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 short sentence with no filler, and the subject is front-loaded. It is terse to the point of being a topic tag rather than a description, which costs it the top score.

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 info tool the bar is low, and listing the covered topics is roughly the minimum viable content. Still missing is any statement of what the response actually contains and how it differs from the three sibling tools.

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 to document and the baseline is 4. Nothing in the description misleads 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?

The description names the subject (CleanOfficeKC) and enumerates content buckets — services, region, why choose us, how to buy — so the agent can infer this returns marketing/informational content. But it never states an action verb or the resource being fetched; 'About CleanOfficeKC' is a topic label rather than a stated function, and 'region'/'how to buy' overlap with what check_service_area and get_quote_estimate appear to handle.

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 guidance, no when-not-to-use, and no reference to the sibling tools. The agent must guess whether general questions about service area or pricing belong here or in check_service_area / get_quote_estimate, which the topic list partially duplicates.

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?

No annotations are supplied, so the description carries the full burden. It does add genuinely useful context not present in the schema: the walkthrough is free, on-site, and produces a written quote, plus an eligibility rule ('business name or contact name, and email or phone'). However, it says nothing about what happens after submission (scheduling, confirmation, follow-up) and its stated requirement conflicts with the schema's zero required parameters, which could mislead an agent.

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 action and value proposition. Minor ambiguity in 'business name or contact name, and email or phone' leaves the boolean grouping unclear, costing a point.

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 12-parameter lead-capture mutation with no annotations and no output schema, the description is thin: it does not explain what the tool returns or how the request is handled, nor does it cover most fields. It is adequate as a one-line pitch but incomplete as guidance for an agent deciding whether and how to call it.

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 17% across 12 parameters, so the description needed to compensate and largely did not. It clarifies only company/contact_name/email/phone as identity fields; sqft, visits_per_week, preferred_times, facility_type, current_vendor, address, notes, and on_behalf_of are left entirely to bare parameter names.

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: 'Book a free on-site walkthrough and written quote.' That is clearly distinct from get_quote_estimate and check_service_area in intent (booking a visit rather than estimating price or checking coverage), although the description never names those siblings 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?

There is no explicit when-to-use guidance relative to the three siblings, which is a real gap given that get_quote_estimate overlaps with the 'written quote' portion. The only usage-like information is the eligibility statement about contact details, and it never says when NOT to use this tool (for example, outside the service area).

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