Huntay AzerTürk

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

Annotations already flag a non-read-only, open-world, non-idempotent operation; the description adds the concrete side effect (Cal.com sends the calendar invitation, Meet link created) and the 30-minute duration and host. It stops short of saying what happens on a duplicate or conflicting slot, which matters given idempotentHint=false.

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 filler, with the core action and its external channel front-loaded and the safety precondition placed last as the gating rule. Every clause carries independent 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 6-parameter mutation tool with no output schema, it covers the actors, the external side effect, and the confirmation gate. The remaining gap is return/error behavior (e.g. what identifier comes back, how a taken slot fails), which the description leaves 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?

Schema coverage is 100%, so every parameter including start, name, email, notes, language and timeZone is already documented in the schema. The description only reiterates that start comes from get_availability and that name/email identify the attendee, adding little beyond structured fields, 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 a specific verb and resource (books a 30-minute intro video call), names the host and channel (Google Meet / Huntay AzerTürk), and anchors the slot to get_availability. An agent can distinguish this from read-only siblings like get_availability or list_services immediately.

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 ties invocation to a precondition: the slot must come from get_availability and the user must have confirmed both slot and details. That sequencing plus the 'call only after' exclusion is exactly the when/when-not guidance an agent needs before a side-effecting booking.

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 and closed-world, so the safety profile is covered. The description adds real value beyond them by clarifying that the result is the *full text* (not a snippet) and by showing the id shape with prefixes ('service:', 'case-study:') that hint at document types.

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 with zero filler, front-loading the return value and then the lookup key. 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 read tool with rich annotations and no output schema, the description covers what it returns and what input it needs. Only error/not-found behavior for an unknown id is left unstated, a minor gap given the simplicity.

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 baseline is 3; the description exceeds it by illustrating the id format with two concrete prefixed examples, which is meaning the schema's 'Document id returned by search' does not convey. It still omits what happens on a malformed or unknown id.

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+resource ('Returns the full text of a document') and the lookup key ('by its id'), which clearly distinguishes it from `search`, which only returns references. It does not explicitly name `search` as the sibling it complements, keeping it just 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?

'from search' and the schema note 'Document id returned by search' make the intended workflow (search first, then fetch) clear without spelling out an alternative. There are no explicit exclusions or failure conditions, but for a one-step lookup the context is sufficient.

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 and closed-world, so the safety profile is covered. The description adds real value beyond them: results are read live from the calendar, slots are 30-minute Google Meet calls, and availability is bounded to Monday–Friday 10:00–18:00 Istanbul time — all material to interpreting 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?

Two sentences, zero filler. The output content and business constraints come first, the usage trigger second — properly 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?

There is no output schema, yet the description conveys the essentials of what comes back (open slots for a defined meeting type, in a defined window) and the timezone/hours frame needed to act on it. It stops short of describing the response shape (slot granularity, date grouping) and any rate limits, which is the remaining 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?

Schema description coverage is 100%, so the schema already documents days, from, language and timeZone including defaults and bounds. The description only reinforces the Istanbul timezone default and adds no per-parameter meaning (no format hints, no guidance on combining from + days), 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?

A concrete verb ("Returns") plus a precisely scoped resource ("open slots" for a 30-minute intro video call on Google Meet), with the data source named (his live booking calendar). The distinction from the sibling book_intro_call is implicit but obvious from semantics: this reads slots, that one books 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?

"Use when the user wants to schedule a call" gives a triggering context, but it does not name book_intro_call as the follow-up action or state when not to use this tool. An agent could plausibly read "wants to schedule" as an instruction to book directly, so the routing guidance is implied rather than explicit.

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 and determinism profile is fully covered by structured data. The description adds that the payload is a fixed personal profile rather than a live lookup, which is mildly useful, but says nothing about auth, caching, or the fact that the language parameter changes the response language.

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 waste: the first front-loads what is returned with a concrete content list, the second gives the invocation trigger. Nothing is repeated from the title 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?

With no output schema, the description carries the return-value burden itself and does so by enumerating the profile sections. There are no required parameters and no destructive behavior to warn about, so an agent has everything needed to call this 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?

There is a single optional parameter with 100% schema description coverage and an enum ("en"/"tr"), so the schema already documents it completely. The description never mentions the language switch, adding no meaning beyond the schema. Per the high-coverage rule, 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 a specific verb (Returns) and resource (the professional profile of a named person) and enumerates the contents: background, role, experience highlights, languages, contact links. None of the siblings (get_service, list_services, fetch, search, get_availability, book_intro_call) overlap with this static-profile resource, so the agent can route correctly 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?

Explicit trigger condition: "Use when the user asks about Huntay AzerTürk himself." That resolves the main ambiguity an agent would have with a name-based resource. There are no when-not conditions or named alternatives, but none are needed given the sibling set is unrelated to this tool's domain.

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, closed-world and non-destructive, so safety is covered. The description adds real value by disclosing the response composition, including that pricing mechanics are surfaced through the FAQ — important context 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 tight clauses: what is returned first, then how to obtain the slug. There is no filler, and the actionable dependency is front-loaded at the end where it belongs.

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 enumeration of returned sections is what makes this definition sufficient. The only gap is the absence of any note that the language parameter switches the response locale, which matters for content-returning 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?

Schema coverage is 100% and both parameters are fully described with enums, so the schema does the heavy lifting. The description reinforces the slug source but says nothing about the 'language' parameter's effect on the returned content, adding no meaning beyond the schema. 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 a specific verb and resource ('Returns full details of one of ... services') and enumerates the sections returned (audience, deliverables, use cases, technologies, FAQ, pricing). This is clearly distinguishable from sibling list_services, which only lists.

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 the slug from list_services' gives an explicit prerequisite and routes the agent to the sibling that produces the required identifier. It stops short of stating when not to use it (e.g., list_services for browsing all services), so it is clear context rather than a full when/when-not matrix.

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 that this is a read-only, idempotent, non-destructive, closed-world operation. The description adds useful behavior beyond annotations: services are ranked by fit when need is given, and each ranked result includes the matching item from its service page.

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, front-loaded with what is listed and then the conditional need behavior. Every sentence contributes useful selection or behavior 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 simple list tool with full schema coverage and clear annotations, the description supplies what structured fields do not: the ranking behavior, inclusion of matching page items, and links. No output schema exists, but the description adequately frames the return contents.

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 adds meaning by explaining that need is the user's problem or project in their own words and that it changes the result ordering. The language parameter is left to the schema, which is acceptable given its clear enum.

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: lists Huntay AzerTürk's consulting and development services, with links. It also specifies the conditional ranking behavior when a need is supplied, which is meaningful differentiation from the singular get_service sibling.

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 says to use it when the user asks which services exist or fit their project. It lacks explicit when-not-to-use guidance or named alternatives such as get_service, but the intended 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 readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds real value beyond that: it lists exactly which fields come back (id, title, url) and that this returns document summaries, not full text. It omits any mention of result limits, ranking, or pagination behavior, which keeps it from 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, zero filler. The content scope is front-loaded and the follow-up action (fetch by id) closes the sentence, so the agent gets purpose and next step in one pass.

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 read tool with no output schema, the description supplies the two things structured fields can't: the corpus being searched and the shape of the results. Nothing needed 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?

There is a single parameter at 100% schema coverage, and the schema already gives a worked example ("cloud cost reduction", "RAG") plus length bounds. The description only restates "by keyword," adding essentially nothing about query matching, so the baseline 3 holds.

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 (searches) plus a precisely enumerated resource scope: services, case studies, FAQ, work experience and articles on a named site. It also states the return shape (id, title, url), which no sibling tool offers, so an agent can distinguish it from `fetch` and `list_services` without opening a 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 explicitly routes the second step: "pass an id to fetch for the full text," which tells the agent this is the discovery step and `fetch` is the retrieval step. It stops short of stating when NOT to use search (e.g., when a known id or URL is already in hand), so it falls just short of the top mark.

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