Straws Soda

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

No annotations are provided, so the description carries the full burden and it adds almost nothing behavioral beyond the field list. It does not say whether the data is live, cached, or how freshness of 'right now' is determined, nor anything about the read-only nature or failure modes.

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?

It is a single short sentence with no padding, which is good, but it is a noun fragment rather than a front-loaded statement of purpose. It is under-specified rather than genuinely concise.

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 usefully enumerates the fields returned, which is the main thing an agent needs. However, for a zero-param tool with no annotations, it still omits when to use it and any behavioral context, leaving gaps that the structured fields cannot fill.

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 per the rubric the baseline is 4; there is nothing for the description to clarify. Schema coverage is trivially 100% because the object is empty.

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 is a bare list of returned data fields ('Public address, phone, email, weekly hours...') with no verb or resource statement, so it never says what the tool does. A reader must infer 'fetch the location/contact details' from the name alone, and nothing distinguishes it from siblings like list_menu or understand_site.

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 prerequisites, and no mention of alternatives such as understand_site or match_intent. The agent is left to guess when this tool is the right call.

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 it does disclose useful traits: the data source is the 'live catalog', prices are integer cents (unit convention), and it explicitly disclaims any ordering side effect. It omits what else a caller might need — availability/stock behavior, pagination, or auth requirements — so it is adequate but not rich.

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 short, front-loaded fragments with zero filler: scope first, then the unit convention, then the negative guarantee. Every clause earns its place and nothing is repeated from the 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 two-optional-parameter read tool, the description covers purpose, data source, price unit, and the absence of side effects, which is most of what an agent needs. Since no output schema exists, the item shape and pagination behavior are left unspecified, which is the only meaningful 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 enum for 'kind' (drinks/merch/both, default drinks) and the 'query' name filter are already documented in the schema. The description adds no parameter-level detail beyond echoing the drinks/merch split, so the 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?

The description states a concrete verb and resource: it returns a public drink menu from the live catalog or shipped merch, with the catalog scope made explicit. Siblings (get_location, match_intent, recommend_path, understand_site) are unrelated domains, so no sibling disambiguation is needed, which caps this at 4 rather than 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?

Usage is only implied: an agent infers it should call this when it needs menu contents. The closing clause 'Does not place an order' functions as a partial when-not (this is not an ordering tool), but there is no explicit statement of when to prefer it or any prerequisites.

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?

No annotations are provided, so the description carries the full behavioral burden. It says nothing about whether classification is deterministic, whether the returned URL is guaranteed to exist, auth requirements, or failure behavior. Only the intended output shape is hinted.

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 with the core action front-loaded and zero filler. The scope-limit sentence is tersely worded and slightly ambiguous, which keeps it from a perfect score.

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 must explain what comes back, and 'return the next public URL' is only vaguely specified — the agent cannot tell what the URL represents or whether other fields are returned. Adequate for a small 2-param tool but under-specified on the return contract.

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 both 'message' and 'pageUrl' (including the notable 'Not fetched' caveat). The description adds no syntax or format detail beyond what the schema provides, so the 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+resource: classify a visitor message and return the next URL. This distinguishes it from lookup-style siblings like get_location and list_menu. It stops short of naming an alternative, so it is clear but not fully differentiated.

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 second sentence supplies negative scope ('Order lookup, punch balances, and hiring are not guest-order conversions'), which is a form of when-not guidance. However it never names a sibling as the alternative and the phrasing is cryptic, leaving actual usage conditions 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?

No annotations are provided, so the description carries the full behavioral burden. It does not disclose read-only nature, auth requirements, side effects, or return format; 'Return' implies a read but not explicitly.

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 core action and followed by the alternative. No wasted words.

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 lookup with one enum parameter and no output schema, the description covers purpose and alternative routing. Missing explicit read-only/return details, but low complexity makes it nearly complete.

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 0%, so the enum values are the only parameter documentation. The description mentions 'known goal' and routing to match_intent for unclear goals, adding some semantic context but not explaining the enum values or format.

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 (Return), resource (canonical public URL), and scope (known goal). Names the sibling match_intent for unclear goals, differentiating this tool from that alternative.

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 directs the agent to match_intent when the goal is unclear, defining when this tool applies (known goals) versus the alternative. No ambiguity about 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?

No annotations are provided, so the description carries the full disclosure burden. It usefully signals a boundary ('what this server will not do'), which tells the agent this is an informational tool and hints at capability limits, but it says nothing about the return shape, whether it is safe/read-only, or whether it must be re-called per session.

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 with no filler: the scope comes first and the imperative 'Call this first' is placed at the end for emphasis. 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 zero-parameter orientation tool with no output schema, the description covers the key question of what the tool exposes plus an invocation ordering. It is nearly complete, only missing any hint of the output form or post-call next step.

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 schema takes zero parameters, so the baseline of 4 applies. Nothing in the description contradicts the empty input object, and there is no parameter meaning to add.

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 concrete scope: what the business is, where the shop is, and what the server won't do — an orientation/overview tool. That is more specific than 'understand_site' alone, but it never clarifies how it differs from the sibling get_location, which also covers shop location, leaving overlap unresolved.

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?

'Call this first' gives an explicit ordering cue, telling the agent to invoke this before the other siblings. It does not state when not to use it, nor name list_menu/recommend_path as the follow-ups, so the guidance is clear but not complete.

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