Goldsberry Orthodontics

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured fields. The description only adds that the data is "public" practice information, with no mention of auth requirements, caching, or freshness. Adds modest value on top of rich 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 resource and its contents, followed by the use case. No filler or restated title 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?

With no output schema, the description carries the return-value burden and does so by listing the returned fields. Combined with annotations covering safety and a parameterless schema, the only real gap is the unresolved boundary with get_practice_info.

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 field list in the description accurately mirrors what the caller gets rather than misrepresenting 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?

States a specific resource (Goldsberry Orthodontics business overview) and enumerates exactly what it returns: doctor, phone, email, hours, website, booking links. It is a clear read of a single resource, though it never distinguishes itself from the near-identical sibling get_practice_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?

"Use for general questions about the practice" gives a context, but it is generic and does not exclude or route against get_practice_info, get_consultation_info, or get_locations, which cover adjacent territory. An agent facing a general practice question has no stated rule for choosing this tool over its 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?

The annotations already declare readOnlyHint=true, destructiveHint=false, and closed-world scope, so the safety profile is covered. The description adds that this is a rules/information tool rather than an action, but gives no sense of return format or freshness of the content it serves.

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 dense sentence enumerating four content areas with no filler. It is adequately front-loaded, though the list structure reads more like a table of contents than a prioritized lead.

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 is the agent's only signal of what comes back, and it does enumerate the content (rules, required fields, confirmation rules, collection restrictions). The main omission is any explicit tie-in to when this should be fetched relative to submit_consultation.

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. Baseline 4 applies; no parameter-level gaps exist.

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 states a specific content domain: consultation mechanics, required fields, confirmation rules, and prohibited data. It is distinguishable from generic info siblings like get_business_info and get_services, though it never names those siblings or explicitly contrasts itself with them.

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?

Referencing 'required fields for submit_consultation' strongly implies this is a prerequisite read before submitting, but the description never states when to call it, whether it must precede submit_consultation, or that it is informational-only. Usage is inferred rather than stated.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description contributes beyond that by specifying exactly what data comes back (address, hours, phone, service area), which matters because 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 sentence, front-loaded with the resource and scoped instance, then the returned fields. No filler or redundancy.

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 and no parameters, the description carries the burden of describing the return payload and does so by enumerating the fields. It is nearly complete; only a note on whether the response can cover multiple offices would add value.

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 is nothing for the description to clarify about argument semantics, and schema coverage is 100%.

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 (office location details) and the specific instance (Sugarhouse / Salt Lake City office), then enumerates the returned fields (address, hours, phone, service area). This clearly separates it from siblings like get_business_info, get_practice_info, and get_services.

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 content listing implies when to reach for this tool (when you need address, hours, phone, or service area), but there is no explicit when-to-use/when-not statement and no sibling is named as an alternative. Usage is inferable rather than stated.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds the useful 'legacy alias' status, but says nothing about return format, caching, or whether the legacy surface may diverge from the replacements.

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, zero waste, with the identity of the tool and the routing advice both front-loaded. 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?

No output schema and no parameters, so the description only needed to convey identity and routing, which it does. It could have said more about what 'legacy' implies (deprecation risk, parity with replacements), which is the one remaining gap for an agent deciding whether to rely on 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly avoids inventing parameter 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 resource scope (public contact, location, hours) and explicitly labels itself a legacy alias, which distinguishes it from the sibling tools. It is clear enough to select correctly, though 'legacy alias' leaves the exact scope of returned data somewhat fuzzy.

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 preferred alternatives: get_business_info, get_locations, and get_services. It gives no condition mapping each sibling to a use case, and does not say when this legacy tool is still the right call, so it stops short of a full when/when-not statement.

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, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context of its own — no indication that the result is a static catalog, whether it reflects current offerings, or anything about the return shape — so it contributes nothing beyond the structured fields.

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 tight sentence with a clear lead-in ('Treatments offered:') and no filler. It is appropriately sized for a no-argument lookup, though the phrasing reads more like payload data than an action statement.

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 tool this is minimally adequate: an agent can call it without further information. However, it omits any framing that this is a retrieval operation returning the service catalog, and gives no clue how it differs from the other info-retrieval siblings.

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. The baseline of 4 applies; the description neither helps nor hurts on this dimension.

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 enumerates the treatments offered, which lets an agent infer this returns the practice's service list, but it never states an explicit verb or scope ('returns the list of services offered'). It also does not distinguish itself from close siblings like get_practice_info or get_business_info, leaving the agent to guess which tool surfaces this content.

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 mention of alternatives among the six sibling tools, and no exclusions. The agent must infer that this is the tool for treatment/service questions purely from the name and the list of items.

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?

Beyond the annotations (which only say non-read-only, non-destructive, closed-world), the description discloses the key gate that nothing is sent unless confirmed=true, that dry_run returns a preview without sending, and that requests are routed through a third party (Found For AI) before reaching the office. These are non-obvious behavioral traits an agent could not infer from structured fields.

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 identity and legacy-alias framing are front-loaded, followed by the confirmation gate and dry_run preview, then the routing context. Five sentences, all relevant, though the routing/office-scheduling sentence is the least essential for correct invocation.

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 7-parameter mutation with full schema coverage but no output schema, the description covers the send gate, preview mode, and downstream routing. It stops short of describing what a successful response or a dry_run preview actually returns, which is the remaining gap given there is no output schema.

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 parameter, including the confirmed gate and dry_run, is already documented in the schema. The description reinforces the confirmed and dry_run semantics but adds no syntax, format, or constraints beyond what the schema already provides, 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?

The description states a specific action (emails a consultation request through the Cloudflare Email pipeline) and explicitly frames itself as a legacy alias of the sibling submit_consultation. An agent can immediately tell what it does and how it relates to the sibling tool without opening any 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?

It gives concrete usage conditions: only proceeds when confirmed=true, re-confirm with the visitor and retry otherwise, and set dry_run=true to validate without sending. The one gap is that it never tells the agent whether to prefer submit_consultation over this legacy alias when both are available.

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 substantial context beyond the annotations: the sending path (Cloudflare Email binding), the hard gate on `confirmed`, the non-sending preview mode, the prohibition on clinical/PII collection, and the third-party routing chain (Found For AI → Goldsberry Orthodontics → visitor follow-up). That reveals real side effects and downstream handling. The description does not say what a successful send returns, which is the remaining gap.

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 confirmation gate and the 'nothing is sent unless confirmed' rule lead the text, so the most important constraint appears first. Five sentences, each carrying usable information. The routing paragraph is slightly long for a detail the agent cannot act on, but it is not 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?

Covers the safety gate, the dry-run path, data-collection restrictions, and the downstream recipient chain, which is most of what an agent needs in order to call a side-effecting tool correctly. With no output schema, it should ideally state what a successful send or preview returns, and it should resolve the overlap with 'request_consultation'.

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 `confirmed`, `dry_run`, `note`, and `preferred_contact_method` are already documented in the schema. The description reinforces the confirmation gate and preview semantics but adds no syntax or format detail beyond the structured fields; 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?

Names a concrete verb and resource and explains the delivery mechanism: "Emails a non-clinical consultation request through the Cloudflare Email binding after the visitor explicitly confirms." That is far more specific than the title. It never mentions the sibling 'request_consultation', however, so an agent cannot tell from the text which of the two overlapping-sounding consultation tools to pick.

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 preconditions and fallback behavior: if `confirmed` is not true nothing is sent, so re-confirm with the visitor and retry; use `dry_run: true` to validate and preview. It also states scope exclusions (no date of birth, insurance, or clinical information). It stops short of telling the agent when this tool is preferred over the sibling 'request_consultation'.

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