Zenith Workspaces

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

Adds substantial context beyond the annotations: it does not hold or book the room, rooms are bookable 24/7, and availability can change until the booking is completed. It also discloses the response contents (busy times, free windows, slot verdict, price estimate, booking link, photos), which the annotations do not cover.

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 and trigger are front-loaded, then inputs, then returns, then behavioral caveats — a sensible order with no filler sentences. It is dense and slightly long, and the room-name enumeration plus photo-field mention repeat schema/output detail that could be trimmed.

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 (busy times, free windows, slot verdict, price, booking link, images). For a 4-parameter read tool it covers inputs, output shape, timezone, and freshness caveats with nothing an agent needs left 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 already 100%, yet the description still adds meaning: "any_office" is explained as checking all six private offices, start times are specified as 24-hour US Eastern, and start is described as paired with duration_hours to test a single slot. The space list largely duplicates the schema enum values, which keeps it from a 5.

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 ("Checks whether a Zenith Workspaces room is free on a given date") and names the backing system (Zenith's live booking calendar). It is clearly distinguishable from siblings like list_spaces (catalog) and get_booking_link (booking action) because it states it only tests availability.

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 an explicit trigger: "Use when someone asks if a private office or the conference room is available at Zenith on a day or at a time." The read-only clause implicitly routes booking intent elsewhere, but no sibling is named as the alternative, so it stops short of full when-not guidance.

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description still adds real value: booking, account creation and payment happen off-tool, availability is not verified, and nothing is reserved. It also names return fields (image_url, images) despite no output schema, though it doesn't describe the price-estimate format or failure behavior for unknown spaces.

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?

Front-loaded with what is returned, then usage, then caveats, then return fields — a logical order with no filler. The trailing sentence about photos is slightly tacked on but earns its place given there is no output schema.

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, closed-world, three-parameter link generator with no output schema, the description covers trigger, exclusions, off-tool handoff, and returned fields. Nothing an agent needs in order to call 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 67% and the description compensates usefully by explaining that date and duration are optional prefill values and that duration is what unlocks the price estimate — meaning the schema does not state. The 'space' parameter still relies entirely on the schema's name list, so it isn't fully additive.

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 Zenith's booking page for a Zenith Workspaces room') and immediately scopes what the URL can contain (date, duration, price estimate). It is clearly distinguishable from siblings, which only check availability, list spaces, or fetch 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?

Gives an explicit trigger ('Use when someone wants to book a Zenith room') and explicit exclusions with the alternative named: 'this tool does not check availability (use check_availability) or reserve anything.' An agent cannot confuse this routing decision.

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 cover the safety profile (read-only, idempotent, non-destructive, closed-world), so the description's job is narrower. It adds useful behavior the annotations cannot: quote-only items return contact details rather than a price, and the optional keyword filter shapes results. It doesn't mention response shape or whether calls are cached, but that is minor given the 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?

Front-loaded with the core purpose followed by the content inventory and then the filter semantics and the quote-only caveat. It is a single dense, slightly run-on sentence, but every clause carries information an agent would otherwise have to guess.

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 lookup tool with no output schema, the description covers what content is available, how to filter, and the one pricing exception. It could be slightly more complete by describing the response form (structured fields vs. FAQ text), but nothing essential for correct invocation 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% for the single optional `topic` param, which would be a baseline 3, but the description goes beyond the schema's bare 'Optional topic or keyword' by listing accepted topic values and allowing free-form keywords. That is real added semantic value because no enum exists in 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?

States a specific verb and resource ('Returns general information about Zenith Workspaces') and then enumerates the exact content returned: address, phone, email, access hours, parking, directions, and FAQ topics. This clearly distinguishes it from siblings like list_spaces or check_availability, which deal with inventory rather than static 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?

The topic filter values (pricing, booking, mail, access, amenities, or any keyword) give concrete guidance on how to scope a call, and the note that monthly offices are quote-only tells the agent not to expect a price there. It stops short of naming when to prefer a sibling tool instead, so routing is only implied.

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 goes further by specifying the returned fields (name, type, capacity, hourly/daily price, booking link, image_url, images), 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?

Two sentences, front-loaded with the what and scoped with the when/not-for. The enumerated room names and returned fields are dense but each item adds signal for an agent deciding whether to call 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?

With no input parameters and no output schema, the description carries the return-shape burden itself and does so fully: record fields, pricing granularity, booking link, and images. The address and inventory size also let an agent answer a user's location question without a second call.

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 is 4. The description correctly conveys that no inputs are needed by framing the call as an unfiltered inventory listing.

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 specific verb and resource ("Lists the rooms at Zenith Workspaces") and immediately scopes what counts as a room: six named private offices plus one conference room. It also states what the tool is not for (monthly offices/suites), so an agent can distinguish it from listing all inventory.

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 an explicit trigger ("Use when someone asks what rooms or offices Zenith has") and an explicit exclusion (monthly offices or suites, quote only). It does not name or route to the sibling tools (check_availability, get_booking_link, get_info), so the alternatives criterion is only partially met.

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