Shortlist Pass Local Businesses

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

With no annotations, the description carries the disclosure burden. It usefully notes that hours are returned for fixed locations only and that mobile businesses have no fixed address, which is real behavioral context. However, it says nothing about errors for invalid subdomains, rate limits, or whether this is a read-only public endpoint — gaps that a mutation-free lookup tool of this simplicity can tolerate at a 3.

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 dense but front-loaded paragraph that leads with the operation and then lists outputs; every clause earns its place, including the mobile-business caveat. It is slightly list-heavy but not padded.

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, so the description correctly compensates by enumerating the returned fields (including conditional ones like hours and order page URL) and covers the mobile-business edge case. An agent has everything needed to call and interpret 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?

Schema coverage is 100% and the single parameter already documents the subdomain with a concrete example ("nitos" for nitos.shortlistpass.com). The description adds no format or constraint detail beyond what the schema provides, so the baseline of 3 is appropriate.

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 (get) and resource (public profile of one business), then enumerates exactly what is returned: name, type, description, town, phone, website, page URL, hours, ordering status, order page URL. It also explicitly contrasts with the sibling get_upcoming_events for mobile businesses, so an agent can distinguish it without opening schemas.

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 a clear usage context (fetch one business's public profile by subdomain) and a routing rule for mobile/food-truck businesses pointing to get_upcoming_events. It does not state when to prefer search_businesses or what happens on an unknown subdomain, so it stops short of full when/when-not coverage.

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?

With no annotations, the description carries the behavioral burden and does it well: it declares what the return contains (active items only, sold-out flag, image URL), that prices are USD, that the order URL appears conditionally, and that ordering is out of scope. It doesn't cover auth or rate-limit behavior, but the read-only nature is unmistakable.

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 dense sentences, zero filler, front-loaded with what the tool returns; the ordering boundary is placed last where it belongs. Every clause adds 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?

No output schema exists, so the description must describe returns — and it does thoroughly (fields, currency, conditional order URL). Combined with full schema coverage on the only parameter, 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?

Single parameter with 100% schema description coverage, including an example value ("nitos"). The description adds no meaning beyond the schema — it never says what a subdomain is or how to obtain one — so the schema is doing all the work.

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 ("The current public menu of one business") and enumerates the returned fields, so an agent knows exactly what this yields. It doesn't name siblings like get_business to draw an explicit boundary, but the menu-vs-business resource split is clear.

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 a clear condition and next step: when ordering is open, include the order page URL and send the customer to that link. It also states a hard exclusion ("this tool cannot place orders"), which prevents misuse. No named alternative tool is offered, so it stops short of full when/when-not routing.

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?

With no annotations, the description carries the full burden and does well: it discloses data-shape guarantees (ISO timestamps with local offset), capacity semantics (null = no cap), exclusions (cancelled and test events never included), and recurrence behavior. It omits auth requirements, pagination, and result limits, keeping it short of 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?

Front-loaded with the resource and scope, and each subsequent sentence adds distinct value (returned fields, capacity semantics, exclusions, ordering pointer). The return-field enumeration is long but justified since 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?

No output schema exists, and the description compensates thoroughly by enumerating returned fields and their edge-case semantics. Combined with a trivial one-parameter input schema, an agent has everything needed to call and interpret the result.

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?

Only one parameter (subdomain) with 100% schema description coverage, so the schema already fully documents it. The description adds nothing about the parameter, which is the correct baseline when structured data does the work.

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 (upcoming published events and stops for a business) with clear scope, and even clarifies the food-truck framing. It does not explicitly differentiate from siblings, but get_business/get_menu/search_businesses cover wholly different domains, so confusion is unlikely rather than impossible.

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 implied rather than stated — the description tells the agent to route customers to order_url for a stop, but never says when to call this tool versus alternatives, or any prerequisites. No when/when-not guidance and no named alternatives.

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?

With no annotations, the description carries the full burden and does disclose real behavior: a hard cap of 25 matches, the subdomain field in each result, and the guarantee that demo/test pages are never returned. It does not mention auth requirements, rate limits, or pagination behavior beyond the cap.

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 sentences, no filler, with the core purpose front-loaded and filter details and return behavior following in priority order.

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, so the description must cover return values, and it does (up to 25 matches, each with a subdomain). Combined with the documented filter semantics, an agent has everything needed to call this tool 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?

Schema coverage is 100%, so the schema baseline is 3, but the description adds genuine meaning: it explains that the free-text query is matched against name, headline and type, and gives richer category examples (food_truck, restaurant, bakery) than the schema's single example.

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 (find local businesses on Shortlist Pass) with concrete domain examples (food trucks, restaurants, HOAs). It also distinguishes itself from siblings by explaining that the returned subdomain feeds get_business, get_menu and get_upcoming_events.

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?

Explains the three filter modes and how they combine ('and/or'), and routes the agent to the sibling tools that consume the result. It lacks an explicit when-not-to-use or an alternative search tool, but the context is otherwise clear.

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