Answering Service Care

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by enumerating the returned content (founding date, social profiles, links), which matters because there is no output schema to reveal the shape of the response.

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: the first lists the payload, the second states the use case. Nothing is wasted and the returned-fields inventory is front-loaded where an agent will read 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?

For a no-argument, read-only lookup with no output schema, the description carries exactly the burden it needs to: what data comes back and when to reach for it. Nothing required to invoke or interpret this tool correctly is missing.

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 and the schema is an empty object, so there is nothing for the description to disambiguate. Per the rubric, zero params sets the baseline at 4.

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 (Answering Service Care's identity/contact details) and enumerates exactly which fields come back: description, phone, email, postal address, founding date, social profiles, and key page links. That is far more concrete than a tautology like 'Get company info,' though it does not explicitly distinguish itself from siblings such as get_pricing or read_page.

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 a clear use condition — 'Use it to answer contact or legitimacy questions' — which tells the agent what class of user request this tool serves. There are no explicit exclusions or named alternatives, but the context is unambiguous for a zero-argument static-info tool.

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 non-destructive/closed-world, so the safety profile is covered. The description adds useful behavioral context beyond that: it describes the shape of the response (grouped by service, USD, with overage rates and features), which matters because 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 tight sentences, zero waste. The content/return shape is front-loaded and the filtering advice follows, so an agent gets the payload description before the optional narrowing tip.

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 carries the return-value burden and does so adequately (plans, prices, USD, grouping, minutes/chats, overage rates, features). For a simple two-parameter read-only lookup with full annotation coverage, this is close to complete.

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 both the 'service' and 'billing_cycle' parameters are already fully documented with examples and enum values. The description only restates that filtering is possible and adds the motive ('keep the answer short'), which is baseline value over 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 resource (current plans and prices in USD) and enumerates what it returns (included minutes/chats, overage rates, features, grouped by service). It is clearly distinguishable in intent from siblings like get_company_info or list_services, though it does not name an alternative 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?

The second sentence gives actionable guidance ('filter by service or billing cycle to keep the answer short'), which implies when to narrow results, but there is no explicit when-to-use-vs-alternatives or exclusion guidance against the sibling tools.

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 non-destructive behavior, so the safety profile is covered. The description adds value by disclosing the return shape (description, page URL, markdown URL per service), which is meaningful given 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?

One front-loaded sentence that names the resource first, then the returned fields. The long parenthetical enumeration is slightly heavy but each item earns its place by defining coverage.

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 read tool with annotations covering safety and no output schema, the description supplies the one missing piece, what each returned service record contains. Adequate and self-contained, with only minor room to mention pagination or result size.

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 is 4; there are no parameter semantics to clarify. The description correctly implies an unfiltered full-catalog call with no arguments.

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 (list services) and then enumerates the exact catalog covered (live/AI answering, virtual receptionist, scheduling, chat, SMS, call center), making the scope unambiguous. This clearly separates it from siblings like get_pricing or get_company_info.

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: call this when you need the full service catalog. However, no explicit when-to-use/when-not guidance or alternative tool is named, so an agent must infer selection from the 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 declare readOnlyHint, idempotentHint, destructiveHint=false, and closed-world scope. The description adds the one thing annotations cannot convey: the response is 'clean markdown', which matters since no output schema exists. It omits error behavior for nonexistent paths, which keeps it short of 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 sentences, no filler, with the return-format claim front-loaded ahead of the parameter guidance. Every clause carries information an agent needs.

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 tool with rich annotations, the description covers output format and path conventions adequately; the absent output schema is compensated by the 'clean markdown' statement. Only missing edge-case context (behavior on invalid or missing pages) prevents a 5.

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% and the schema already documents the path parameter, so the baseline is 3. The description earns above baseline by giving concrete path examples ('/pricing/', '/services/virtual-receptionist/', '/' for homepage) that clarify leading-slash and homepage conventions the schema only alludes to.

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 (any ASC page) plus the output format (clean markdown). The word 'any' implicitly distinguishes it from the narrower siblings get_pricing/list_services, but it never names an alternative, so differentiation is left to inference.

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 tells the agent how to call it (pass a site path, '/' for homepage) but not when to prefer it over get_pricing, list_services, or search_site. Usage context is implied rather than stated, and no exclusions are given.

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 and non-destructive, so the safety profile is covered. The description goes further by disclosing the shape of results (each has a markdownUrl) and the read_page follow-up flow, which is valuable given 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?

Two sentences, front-loaded with the search scope, followed immediately by the actionable result-handling instruction. No filler or repetition of schema content.

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 does the important work of naming the markdownUrl field and the read_page handoff, making the tool callable correctly end-to-end. It could say slightly more about other result fields or ordering, but the key actionable detail 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 100%: both 'query' (2-200 chars) and 'limit' (1-20, default 10) are fully documented in the schema. The description adds no syntax or format detail beyond that, so the baseline of 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?

States a specific verb (full-text search) plus the resource and exact scope (ASC's service, industry, location and blog pages), which cleanly separates it from structured siblings like get_pricing and list_services. An agent can identify what this tool covers 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?

Explicitly describes the workflow handoff: take a result's markdownUrl path and pass it to read_page for the full text, which answers the 'what next' question. It doesn't state when to prefer search_site over list_services/get_pricing, though the full-text framing implies it.

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