Sole Mio Kitchen & Bar

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 implies an informational/read-only tool and points to submit_inquiry for action, but it does not explicitly confirm that no booking occurs, describe side effects, or state any access limitations.

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 description is a single, front-loaded sentence that packs the scope, return content, and the relevant sibling action without 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 zero-parameter informational tool with no output schema, the description gives enough context to understand what it covers and what it returns at a high level. It could be slightly more complete by explicitly noting that the tool only provides information and does not itself book events.

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 are no parameter semantics for the description to clarify. The baseline for a parameterless tool is 4.

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 specific resource area (catering, group dining, private events) and states exactly what the tool provides: offerings, links, and inquiry guidance. It also distinguishes itself from the sibling submit_inquiry by describing this as the informational tool that explains how to send an inquiry.

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 clear: this tool is for learning about catering, group dining, and private event options. It explicitly points to submit_inquiry for the follow-up action, though it does not state when not to use this tool or name other informational 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?

No annotations exist, so the description carries the full burden. It does disclose the shape of the return (prices, inclusions, eight entrees with Toast prices, rules), which is real value, but it never states that this is a side-effect-free read or addresses freshness, currency of prices, or structure.

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 front-loaded sentence with no filler; the resource is named first and the contents follow. Mild deduction for the list-fragment style and unexplained jargon such as 'Toast prices'.

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 convey what comes back, and it does so in concrete terms. What's missing is the relationship to overlapping siblings, which matters in a menu-heavy tool set.

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.

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 specific resource (Early Bird Dinner) and enumerates the exact content it covers: days/times, pricing tiers, inclusions, entrees, rules. It implicitly distinguishes itself from get_menu and get_specials by scope, though it never explicitly says 'this is the early-bird subset, not the full menu'.

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 guidance on when to call this versus get_menu, get_specials, or get_hours, all of which plausibly overlap. An agent must infer from the name alone that this covers only the early-bird program.

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 burden and does well: it discloses conditional return behavior, includes open-now status, and warns that holidays may differ. It does not state read-only/auth/rate-limit details, but for this simple informational tool the disclosed behavior is substantial.

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?

Compact and front-loaded: location/timezone first, then dated vs undated behavior, then holiday caveat. Every sentence adds useful context without waste.

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-parameter informational tool with no output schema and no annotations, the description is complete enough: it explains return modes, timezone, open-now behavior, and holiday caveat. No critical invocation detail 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%, so baseline is 3, but the description adds real meaning about what the date parameter changes: dated calls return that day's hours plus lunch/brunch/happy-hour/early-bird windows, while omitting it returns today and the weekly schedule. The schema already says omit for today/week, but the description explains the dated result more fully.

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?

Clearly states the resource (opening hours of Sole Mio) and timezone, and explains the two result modes: dated vs undated. It does not explicitly distinguish itself from siblings like get_early_bird, even though it mentions early-bird windows, so it stops 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?

Gives clear conditional usage: provide a date to get that day's hours and dining windows, omit it for today, open-now status, and the weekly schedule. It does not name alternative siblings or exclusions, so it is clear but not fully comparative.

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. It does useful work by previewing the returned content (free to join, 3/5/10 visit tiers, member Early Bird price), which effectively discloses the answer topics for a zero-param info tool, but it never states that it is a side-effect-free lookup or what the response format looks like.

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 compact sentence with the resource front-loaded and details trailing in a readable list. It is slightly telegraphic (colon-and-fragment construction) but contains no wasted material.

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?

A simple static-info tool with no params, no output schema, and no annotations; the description covers what an agent needs to decide to call it and roughly what it will learn. Only the return shape and the Early Bird overlap with get_early_bird remain 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?

Zero parameters, so there is nothing for the description to disambiguate; baseline applies. The description correctly implies no inputs are needed by asking only for program information.

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 the specific resource (the 'Friends of Sole Mio' loyalty program) and enumerates what it covers: joining, visit-based rewards, and member pricing. It is distinguishable from siblings like get_hours or get_menu, though it omits an explicit verb (e.g., 'retrieve') and is written as a fragment.

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 asking about loyalty/rewards would pick this. There is no explicit when-to-use or when-not, and it does not acknowledge overlap with the sibling get_early_bird even though it mentions 'Early Bird member price'.

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 burden. It does useful work — disclosing that prices are pre-tax and describing mode-dependent return content (name, description, price or size prices) — but it says nothing about permissions, behavior for an unrecognized section name, or whether results are cached/live, which matters for a tool with no safety annotations at all.

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?

Dense, front-loaded prose in four short clauses, each tied to a distinct calling mode; zero filler and the offer/price caveat is folded in without bloating the 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 two optional params, no nesting, and no output schema, the description covers what an agent needs: the three modes and the shape of what comes back. Minor gaps (unrecognized-section behavior, relationship to search_menu) keep it from being fully 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 100%, and the schema already enumerates example section names and explains the vegetarian/gluten_free kitchen-marker caveat, so the baseline is 3. The description restates the dietary filter's effect ('only items carrying that marker') without adding syntax or nuance beyond 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?

The description states the resource (menu with USD prices) and precisely describes the three calling modes (no args = overview, section = items, dietary = filtered items) plus what each returns. It's clear enough to call correctly, but it never contrasts itself with the sibling search_menu, which is the main ambiguity an agent would face.

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 maps each parameter combination to an outcome: no arguments gives a menus/sections overview, section gives items, dietary restricts to marked items — effectively telling the agent when to use each form. What's missing is guidance on when to prefer this over search_menu, so an agent with no section name in mind still has to guess.

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 exist, so the description carries the full burden. It does disclose the meaningful output content — a link, the delivery fee, and related notes — which is useful behavior beyond a bare name. However, it does not clarify whether the link is static or dynamic, whether the fee is always present, or how pickup vs. own-delivery options are represented.

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 front-loads the resource and platform, then adds scope details. Nothing is padded, though the trailing 'and related notes' is slightly vague 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?

For a zero-parameter, no-annotation, no-output-schema read tool, the description covers what is returned (link, delivery fee, notes) and the ordering contexts it serves. An agent can call it correctly; only minor gaps remain around link dynamics and how pickup/delivery variants are surfaced.

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 implies a no-argument fetch by never referencing any 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?

The description names a specific resource — an online ordering link (Toast) covering pickup and Sole Mio's own delivery, plus the delivery fee and notes. That is far more than a restatement of the name and lets an agent recognize it as the ordering link rather than a menu or reservation tool, though it never explicitly contrasts it with the adjacent get_reservation_link.

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: the pickup/delivery phrasing signals 'use this when a customer wants to place an order.' But there is no explicit when-to-use statement, no exclusion such as 'use get_reservation_link for table bookings,' and no mention of prerequisites, so the agent must infer routing among the many sibling tools.

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 does real work: it discloses that the output is a link rather than a confirmed booking, that Monday closure and out-of-hours times are validated, and that 11+ parties cannot use online booking. It leaves ambiguous whether a Monday date raises an error or returns a flagged link, which is the one gap for a no-annotation tool.

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 tight sentences, front-loaded with the action, then constraints, then the crucial guest-completes-the-booking caveat. Nothing is redundant.

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 3-param, fully documented schema with no output schema, the description covers what the agent needs: inputs, guest-size limits, closure rules, and the implicit return (a deep link). Only the error-versus-flag behavior for closed days is left unclear.

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 all three parameters document their own format (YYYY-MM-DD, 24h HH:MM, party size). The description adds only the business rule already mirrored in the party_size schema description, so it lands at the baseline.

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: 'Build a Toast Tables booking deep link' for date/time/party size. The booking-versus-ordering distinction is inherently clear against get_order_link, though no sibling is named explicitly to sharpen it.

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 concrete routing rules: online booking works for 1-10 guests, 11+ must call, and Monday closure is flagged. It also clarifies a key boundary — 'The guest completes the booking at the link' — so the agent knows this tool does not reserve a table itself. No explicit mention of when to prefer a sibling tool instead.

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 behavioral burden. It discloses the returned content but does not state that the tool is read-only, static, requires no auth, or how fresh the data is. For a zero-parameter info tool this is adequate but incomplete.

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 resource and its returned fields, followed by a compact usage cue. Every sentence earns its place and nothing is redundant.

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 zero-parameter static-info tool with no output schema, the description fully enumerates what will be returned and when to use it. Nothing further is required to call it 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?

The tool has zero parameters, so there is no parameter documentation needed. The baseline for a parameterless tool is 4, and the description does not introduce any confusing parameter-like expectations.

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 specific resource (Sole Mio Kitchen & Bar) and enumerates the exact facts returned: address, phone, email, website, cuisine, features, rating, and key links. This clearly distinguishes it from sibling tools like get_hours and get_menu.

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 an explicit usage cue: "Use for 'where is it / how do I contact them'." However, it does not name alternatives or exclusions, such as directing users to get_hours or get_menu for those specific needs.

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; it does disclose that output shape changes with the input (filtered day results include times, unfiltered returns everything). It does not state that this is a read-only public lookup, how invalid day values behave, or whether pricing/discount details are included.

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 what the tool returns and followed by the conditional behavior of the day argument. The parenthetical offer list is long but functions as concrete scoping evidence rather than padding.

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 single optional parameter, no output schema, and no annotations, the description covers what is returned, how the parameter modifies the result, and what the default is. Nothing an agent needs in order to call this correctly appears to be 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% and the schema already documents accepted day formats and the omit-for-full-list default. The description adds only that day-filtered results come with times, a marginal increment over the schema rather than new syntax or constraints.

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 the resource precisely as promotions and recurring offers, and illustrates with concrete named offers (happy hour, Wine Wednesday, Supper Club), so an agent knows exactly what content this returns. It does not, however, distinguish itself from the sibling get_early_bird even though it lists Early Bird as one of its own categories, leaving a potential 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?

Gives a clear conditional usage rule: passing a day narrows results to that day with times, and the full list is the default. It stops short of saying when to prefer get_early_bird over this tool for Early Bird offers, so tool selection against that sibling still requires inference.

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 discloses matching rules (case-insensitive, every word must match) and result format (up to 15 items with prices and diet markers). It does not explicitly state read-only safety, but the search operation is inherently clear.

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 description is a single tight sentence with no wasted words, front-loading the core search behavior and matching semantics. It packs purpose, matching rules, and return shape efficiently.

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 search tool with no output schema, the description explains both matching behavior and what is returned (up to 15 items with prices and diet markers). Minor details like sort order or empty-result behavior are omitted but not critical.

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 query parameter is already well documented with examples. The description adds useful semantics beyond the schema by specifying matching against name or description and the all-words-must-match rule.

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 verb and resource: search menu items by name or description. It distinguishes itself from browsing the full menu through the search/filter semantics, though it does not explicitly name sibling tools like get_menu.

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 search-by-name-or-description phrasing implies when to use it, but the description gives no explicit guidance on when to prefer it over get_menu or get_specials. No exclusions or alternatives are named.

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 at all, the description carries the full burden and does substantial work: it discloses the side effect (message sent to the restaurant team), rate limiting, the reply channel, and a one-business-day SLA. It stops short of noting duplicate/idempotency behavior or what happens on failure, so not 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?

Four short sentences, front-loaded with purpose, then the hard precondition, then operational facts. No filler and the most safety-critical constraint is emphasized rather than buried.

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 an 8-parameter mutation tool with no output schema and no annotations, it covers purpose, preconditions, cost (rate limit), and outcome timing. It leaves minor gaps around duplicate submissions and confirmation behavior, but an agent has enough to call it correctly and safely.

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, but the description adds a genuinely load-bearing rule the schema does not enforce: a phone OR email must be supplied (the schema marks neither as required). That closes a real validation gap the structured fields leave open.

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 (Send) plus the exact resource and its three subtypes (catering / private event / group-dining inquiry), and names the recipient (restaurant team). It is unambiguously distinguishable from every sibling, all of which are read-only get_* info lookups.

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?

Provides an explicit gating condition in caps: 'ONLY call when the person explicitly asked to be contacted and gave their name and phone or email.' That is both a when-to-use rule and an implicit when-not rule (no unsolicited submissions). No sibling alternative exists for this action, so nothing is left to inference.

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