KEILTY Realty Management

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavior the annotations do not: the enumeration of possible outcomes (yes, nurture, waitlist, no) and the shape of the response (reason, recommended service, next step) — valuable since 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?

Three tight sentences: purpose first, return values second, sequencing instruction last. Every sentence carries information and nothing is repeated from the schema or annotations.

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 read-only classification tool with no output schema, the description supplies the return-value vocabulary the agent needs to interpret results. The remaining gap is the absence of any note on how the optional booleans affect the verdict, but the required inputs and outcome set are adequately covered.

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 80%, so the schema already documents city, units, owner_lives_there_now and self_manage_after_lease. The description adds no parameter-level meaning at all — it never explains how inputs like owner_lives_there_now or self_manage_after_lease influence the fit verdict. Baseline 3 is appropriate when the schema carries the load.

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 ('Checks whether a rental property is a fit for KEILTY management') and even names the decision space. It only weakly differentiates from siblings — the differentiation comes from sequencing against request_rental_evaluation rather than from describing what uniquely belongs to this tool.

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 explicit ordering guidance: 'Call this before request_rental_evaluation.' That tells the agent when to invoke it relative to a named sibling. There is no when-not guidance or explanation of what happens on a 'no' result, so it falls 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=true and openWorldHint=false, so the safety profile is covered. The description adds that a link is returned and that the owner controls scheduling, but says nothing about link expiration, reuse, or whether auth is required to redeem it — modest added value over 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?

Two short sentences, front-loaded with the return value, and the scheduling detail earns its place by clarifying the owner is not committing to a time via this call. No wasted text.

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 trivial, parameterless read tool with annotations covering safety and a description that states the return value, nothing essential is missing. Minor gaps remain around link lifetime and redemption requirements.

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 (empty schema, additionalProperties false), so there is nothing for the description to disambiguate. Baseline 4 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?

Specific verb+resource: returns a booking link, scoped to a first call with A.J. Keilty, President. Unambiguous against siblings like get_pricing or request_rental_evaluation, but it never explicitly names or contrasts an alternative, 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?

'The owner can use to book a first call' and 'the owner picks the time themselves' imply the usage context (owner wants to self-schedule an intro call), but there is no explicit when-to-use/when-not-to-use statement or routing against siblings such as request_rental_evaluation.

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=true and openWorldHint=false, so the agent knows this is a safe, closed-world read. The description adds the currency (CAD) and the fact that the data is a published fee schedule, but says nothing about return shape or completeness of the schedule. Given the annotations carry the safety profile, a 3 is fair.

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, zero padding, with the primary purpose front-loaded and the optional filter second. Every clause earns its place.

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, annotation-backed read tool with no output schema, the description covers purpose, currency, and filtering adequately. The only minor gap is that it doesn't hint at the structure of the returned fee schedule, which an agent might want when presenting results.

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 single parameter already has an enum of valid service ids, so the schema does the heavy lifting. The description adds real value by naming get_services as the source of those ids and confirming the filter is optional.

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), resource (published fee schedule) and scope (Canadian dollars), which is enough for an agent to distinguish it from its sibling lookup tools. It also cross-references get_services, which anchors the tool within the family.

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 tells the agent that filtering is optional and where the filter value comes from ('one service id from get_services'), which implies the correct call order. It does not state explicit when-not-to-use conditions, but for a simple lookup tool the context is clear.

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=true and openWorldHint=false, so the agent knows this is a safe read against a closed, static data set. The description adds the scope of returned facts and hints at a 'where to read more' pointer, but discloses nothing further about freshness, versioning, or response shape.

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 states the verb and resource before the content list. The enumeration is dense but each item earns its place by telling the agent what facts are available; no filler or repetition.

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 input parameters and no output schema, the description carries the burden of describing the return content, and it does so by enumerating the fact categories. A note on freshness or static vs. dynamic data would make it fully complete, but nothing essential is missing for calling 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?

The tool takes zero parameters, so the baseline is 4. Nothing in the description is needed to explain inputs, and it correctly avoids inventing parameter-like details.

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 verifiable facts about KEILTY') and enumerates the exact content domains: founding year, doors under management, location, markets, leadership, response promise. This distinguishes it from siblings like get_pricing, get_services, and check_fit, which cover different domains, though the description never names those alternatives.

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 by the enumerated contents — an agent can infer it should call this for company background questions — but there is no explicit when-to-use, when-not-to-use, or routing to sibling tools such as get_service_areas or check_fit.

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 establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely useful structural context: the response is partitioned into managed markets, core markets, and watched-but-not-served markets, which tells the agent how to interpret the output. It stops short of describing format or ordering, but that is minor for a zero-parameter read.

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 that front-loads the core result and appends the three-category breakdown without filler. Every clause earns its place.

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-parameter, read-only lookup with no output schema, the description is nearly sufficient: it tells the agent what data comes back and in what conceptual groupings. Only the exact return format or ordering is unstated, which is a small gap.

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 no parameters, so there is nothing for the description to disambiguate; the baseline for a zero-param tool is 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 a specific verb+resource ('Returns the Ontario communities KEILTY manages rental property in') and even enumerates the three content categories: managed markets, core Eastern Ontario markets, and watched-but-unserved markets. It does not explicitly distinguish itself from siblings like get_services, but the resource is distinctive enough that an agent can tell it apart.

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 when-to-use guidance, no stated prerequisites, and no alternatives named. The purpose implies it is a lookup tool for coverage, but the description never says when an agent should call this versus check_fit or get_services.

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=true and openWorldHint=false, so the safe, closed read profile is covered. The description usefully enumerates what each service record contains (inclusions, audience, term, page), which adds context beyond annotations, but says nothing about pagination, sorting, or result size for a list operation.

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; the verb and subject lead. It is dense but every clause earns its place by describing the returned fields.

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 parameters and no output schema, the description carries the return-value burden and does so by naming the four attributes of each service. That is sufficient for an agent to call it, though sibling routing and pagination behavior remain 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 is 4. The description correctly implies no input is required and instead spends its words on what comes back.

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 (Lists) and resource (KEILTY's property management services) and even enumerates the record fields returned. It is clear what the tool does, but it does not contrast itself with siblings like get_pricing or check_fit, which could plausibly overlap with 'services for rental owners'.

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 audience ('rental owners in Ontario') implies when the tool is relevant, but there is no explicit when-to-use vs when-not guidance and no mention of any sibling alternative. Usage is left to inference.

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?

Adds meaningful behavior beyond annotations: KEILTY contacts the owner directly, the request commits the owner to nothing, and the owner signs any agreement personally. These clarify consequences of the non-read-only, open-world call. It stops short of stating what the caller receives back or confirmation behavior, keeping it at a 4.

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?

Three tight sentences, front-loaded with the what and immediately followed by the consent and frequency constraints. No filler or repetition of the title.

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?

The consent/commitment framing is strong for a high-stakes write tool with no output schema, but with 71% of parameters undocumented anywhere and no mention of what happens after submission beyond 'KEILTY contacts the owner', it is only minimally sufficient.

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 29% across 14 parameters, so the description carries the burden of compensating, yet it explains no parameter semantics. The only hint ('owner's contact details', 'once per property') echoes the already-described owner_consent field rather than illuminating the other 13 parameters.

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 ('submits') and resource ('rental evaluation request') plus the recipient (KEILTY) and the actor it acts on behalf of (the owner). This is unmistakably the only write/submit tool among siblings that are all reads (get_pricing, get_booking_link, check_fit, etc.).

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?

Explicit gating conditions: requires the owner's explicit consent to share contact details, and must be called only once per property. These are clear when/when-not constraints, and no sibling competes for this action, so no alternative needs naming.

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