Kay1 Electric (Vancouver electrician)

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

Annotations already establish that this is a read-only, idempotent, non-destructive, closed-world operation. The description adds useful return-content context beyond those annotations by specifying the exact business information domains the agent will receive.

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 a single efficient sentence that front-loads the content domains. It is appropriately sized for a zero-parameter informational tool, though it is a noun phrase without an explicit action verb.

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 simple zero-parameter tool whose annotations already cover safety traits, the description is largely complete: it tells the agent what business information will be returned. The only noticeable gap is that it does not clarify the boundary with overlapping siblings like list_service_areas and request_quote.

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?

This tool has zero parameters, so there are no parameter semantics requiring explanation. The baseline for a no-parameter tool 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?

The description clearly identifies the resource as Kay1 Electric Ltd.'s business information and enumerates the specific content domains: contact details, office hours, emergency policy, licensing, service area summary, and estimate requests. It is distinguishable from service-list and quote-request siblings, though it lacks an explicit verb like 'return' or 'get'.

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 listed content implies when an agent should use this tool, e.g., for contact details, hours, or licensing. However, it does not state when to prefer this tool over siblings such as list_service_areas, list_services, get_page, or request_quote, even though service area and estimate topics overlap with those siblings.

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, closed-world behavior, so the bar is lower. The description adds the non-obvious return characteristic — content comes back as Markdown rather than HTML or raw text — 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, no filler: the first states what is returned, the second how to find inputs. The core capability is front-loaded.

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 no output schema, the definition covers return format, input examples, and path discovery. Nothing an agent needs to invoke it 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?

Schema coverage is 100%, so the baseline is 3. The description earns more by supplying multiple example paths, including a localized '/fa/contact-us/' variant, and naming the resources an agent should use to construct valid paths.

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 ('Returns the Markdown version of a kay1electric.ca page') and gives concrete example paths. It is clearly distinguishable from siblings like get_business_info or request_quote because it is scoped to fetching page content as Markdown.

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 routes the agent to list_services, list_service_areas, or llms.txt to discover valid paths, which is the key prerequisite for calling this tool. It does not state exclusions (e.g., what to do for pages not covered by those lists), so it falls just short of a 5.

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, openWorldHint=false and destructiveHint=false, so the safety profile is fully covered. The description adds useful content scope (cities, example neighbourhoods, per-city page URLs), but says nothing about completeness, ordering, or how the optional language argument changes results.

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 compact sentence with the geographic scope and payload front-loaded and no filler. Every clause (cities, neighbourhoods, page URLs) contributes distinct 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 usefully previews the return shape (city names, example neighbourhoods, page URLs). For a zero-required-parameter read-only list tool this is close to sufficient; only result ordering or completeness guarantees are absent.

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 the single 'language' enum (en default, fa) is already fully documented in the schema. The description adds no parameter meaning of its own, which matches the baseline 3 for a well-documented single-parameter tool.

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 (cities in Greater Vancouver served by Kay1 Electric) plus the payload contents (neighbourhoods and page URLs), which is enough to tell it apart from list_services and get_page. It does not explicitly name a sibling, so it falls 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 only implied: an agent can infer it should call this to discover which cities are covered. There is no statement of when to prefer this over get_page or list_services, and no prerequisites or 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, non-destructive, closed-world behavior, so the safety profile is covered. The description adds value beyond that by disclosing the return shape — each service paired with its page URL — which matters since there is no output schema. It doesn't mention the language switch affecting those URLs, which is a small omission.

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 and the return content second, with zero filler. The parenthetical service list is long but earns its place by showing enumerable values an agent can match against.

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-optional-param, read-only listing tool with no output schema, the description covers what the tool returns and enough of the domain to be callable. The only gap is that it doesn't note the response differs by language.

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% and the single optional language enum is fully documented there, including default behavior. The description adds no parameter meaning of its own, so 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?

States the specific resource enumerated (the electrical services offered) and what each entry carries (its page URL), so the agent knows exactly what comes back. It doesn't name or differentiate itself from siblings like list_service_areas or get_page, but the content itself 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?

Usage is only implied: an agent would infer this is the discovery entry point before calling get_page, but the description never says when to prefer it over list_service_areas or get_business_info, and offers no exclusions.

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?

Goes well beyond the annotations by disclosing downstream effects: Kay1 receives it by email, calls back during 7:00 AM–9:30 PM Pacific hours, and the customer gets a confirmation email if one was supplied. It also states the anti-fabrication rule and the emergency escalation path. Missing only duplicate/idempotency behavior (annotations say idempotentHint=false, but the description doesn't explain what a resend does) and what the call itself returns.

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 in the first sentence, followed by outcome, then consent gating, then the emergency exclusion — a sensible order. It is dense but nearly every sentence carries operational weight; the emergency phone number and hours are long but justified safety 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?

For a 10-parameter, 5-required mutation with no output schema, the description covers the crucial gaps: consent, side effects, callback timing, and emergency routing. It does not tell the agent what the tool returns on success or how to handle a repeat submission, which are the remaining holes.

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 baseline would be 3, but the description adds real meaning: the email parameter's side effect (confirmation email), the consent gating behind customer_confirmed, and the 'Do not invent details' constraint that governs the details field. Enum-driven fields (city, service, urgency, preferred_language) are left entirely to the schema, which is acceptable at full coverage.

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?

Opens with a specific verb and resource ('Send a free-estimate request to Kay1 Electric') plus the acting party ('on the customer's behalf'). This is clearly a write/send tool, distinguishable at a glance from read-only siblings like get_business_info, list_services, and list_service_areas.

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 both a positive precondition ('Only call this after showing the customer the details and getting their explicit OK') and an explicit exclusion with a redirect ('Not for emergencies... tell the customer to call (778) 900-1004'). An agent knows when to call it, when not to, and what to do instead.

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