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

Beyond the readOnlyHint and openWorldHint annotations, the description reveals important behavioral details: Tock returns the full open-date/time set by default, passing a date only focuses the summary, and no booking side effect occurs. The external reservation redirect adds practical context.

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 carry distinct, high-value information: what the tool returns, how the date parameter behaves, and the non-booking caveat. There is no filler or repetition of schema details.

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 availability tool with no output schema, the description adequately explains the return contents, the date behavior, and the reservation limitation. The party_size parameter is already fully described in the schema, so nothing critical 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 the baseline is 3. The description adds extra meaning for the date parameter by explaining how it affects the output ('focus the summary') while noting the full set is still returned. This goes beyond the schema's simple 'center the calendar on' wording.

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-object pair ('Get a venue's bookable calendar') and enumerates the returned content: experiences, prices, party sizes, cancellation policy, and open dates/times. This clearly distinguishes it from sibling tools like tock_get_restaurant or tock_list_reservations.

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 explains when the optional date parameter is useful ('pass a date to focus the summary') and explicitly warns that this MCP does not book, directing the agent to exploretock.com for reservations. It does not explicitly compare against sibling tools, but the usage 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?

The annotations only declare read-only and open-world behavior; the description adds the non-obvious operational facts: a signed-in bridge tab is required and the identity is synthesized from reservation records, so an account with zero reservations will not yield a profile. That is exactly the kind of auth/dependency disclosure the annotations cannot carry.

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: identity and fields first, then the two preconditions. No filler, no restatement of the tool name, and nothing to trim.

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 low-complexity read tool with no output schema, the description covers what is returned, what is required to call it, and the data dependency behind the result. An agent has everything needed to decide to call it and to interpret failure conditions.

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 'view' enum is documented in detail in the schema itself, including what compact strips and why no projection exists. The description never mentions the parameter, so it adds nothing beyond the schema, making the baseline 3 correct.

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 (get the signed-in user's Tock account identity) and enumerates the returned fields (name, email). None of the sibling tools (reservations, availability, restaurants, healthcheck) overlap with this scope, so an agent can select it unambiguously.

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 preconditions for use: an authenticated browser tab on exploretock.com via the ContextMint Bridge extension, plus at least one existing reservation. No when-not guidance or named alternatives, but no sibling offers profile data, so the missing exclusion is low-cost.

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 carry readOnlyHint=true and openWorldHint=true, covering the safe, read-only nature. The description adds the response field list but discloses no additional behavioral traits such as authentication, rate limits, or error behavior. With annotations present, this meets the baseline without contradiction.

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 with no filler. The core action and return contents are front-loaded, followed by the crucial slug-source guidance. Every sentence 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 simple get-by-identifier tool with a read-only annotation, the description is complete: it names the input, the source of the input, and the expected response fields. No output schema exists, so enumerating the return value in prose fills that gap adequately.

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 value beyond the schema by telling the agent where the slug comes from (tock_search_restaurants or exploretock.com URLs), which complements the schema's example. This extra provenance guidance justifies a 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 states a specific action and resource: 'Get details for a Tock venue by slug' and enumerates the returned content (name, cuisine, price band, location, description, bookable experiences). It also implicitly distinguishes itself from siblings by indicating the slug comes from tock_search_restaurants, clarifying its role in the workflow.

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 description gives clear usage context: the slug is obtained from tock_search_restaurants or an exploretock.com URL, so an agent knows this tool is the follow-up lookup after a search. It does not explicitly state when not to use it or name alternatives, but the guidance is sufficient for typical selection.

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 and openWorldHint, so the safety profile is covered. The description adds genuinely useful context beyond them: no auth required, that it touches your signed-in browser tab, elapsed round-trip timing, and the four failure classes the hint discriminates between.

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 mechanism, then the returned diagnostics, then the usage trigger. Slightly dense in the first sentence's long list of diagnostic fields, but every clause carries information and nothing is wasted.

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, and the description fully enumerates the return shape (bridge role, port, version, link state, elapsed time, hint), so an agent knows exactly what it gets back. Combined with the trigger guidance and auth note, nothing needed to call it correctly is absent.

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 no parameter semantics to clarify and the description does not invent any. Nothing here is missing or misleading on the parameter axis.

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: it round-trips a small public URL (/robots.txt) through ContextMint Bridge and returns diagnostics. It also enumerates what the diagnostics contain, so an agent can distinguish it immediately from the tock_* data tools in the sibling list.

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 when to call it: 'Call this when a real tool fails and you want to know which hop broke.' That is a clear trigger condition, though it does not name a specific alternative diagnostic tool to prefer and leaves the 'when not to call' case implicit.

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 convey readOnlyHint=true and openWorldHint=true. The description adds a non-obvious behavioral default ('only metros with bookable venues are returned'), which is useful. However, it does not disclose other behavioral traits such as pagination behavior or what 'bookable' means, so it stays at a baseline acceptable level.

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 with no wasted words. The first sentence states the resource and output fields, while the second provides the key downstream relationship and default filtering behavior. Everything present 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 read-only list tool with no output schema, the description tells the agent what the tool returns, the default behavior, and how to proceed with the result. Parameter details are covered fully by the schema, so nothing essential 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 description coverage is 100%, so all four parameters (limit, query, country, include_empty) are already documented in the schema. The description adds no additional parameter-level meaning, 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?

The description opens with a specific verb and resource ('List Tock cities/metros') and enumerates the returned fields (name, slug, business count, country/state). It also differentiates from the sibling tool by pointing to tock_search_restaurants as the downstream consumer of a metro slug.

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 clearly guides the agent to use the returned metro slug with tock_search_restaurants, establishing the tool's role in the workflow. It does not explicitly state when not to use it, but the context is clear enough for an agent to select it appropriately.

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 cover the safety profile (readOnlyHint=true, openWorldHint=true), so the bar is lower, and the description adds the genuinely useful operational precondition that a browser tab signed in to exploretock.com is required. It also discloses the shape of what comes back (venue, date/time, party size, experience), though it says nothing about pagination behavior or empty-list handling.

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 first front-loads the resource, scope, and return fields; the second carries the prerequisite. 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 low-complexity, read-only list tool with no output schema and a fully documented input schema, the description covers purpose, filterable statuses, and the authentication environment an agent must satisfy before calling. Nothing required 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 description coverage is 100%, so limit, offset, and status are already fully documented in the schema, and the enum values named in the description mirror rather than extend the schema. The description contributes no additional format, default, or interaction semantics, 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 ('List the signed-in user's Tock reservations') and enumerates the returned fields (venue, date/time, party size, experience), which no sibling provides. An agent can distinguish it from tock_get_availability, tock_verify_reservation, and the restaurant-lookup siblings 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?

Usage is implied by the reservation scope, and the description does state a hard precondition (a signed-in exploretock.com tab via the ContextMint Bridge extension). However, it never says when to prefer this over siblings like tock_verify_reservation or tock_get_profile, and gives no explicit 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?

The annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds useful behavior beyond that: it specifies the returned venue fields (cuisine, price band, neighborhood, Tock slug) and the negative constraint that bookable slots are not included. It does not discuss pagination edge cases, but the schema covers limit.

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 with no wasted words; the main action is front-loaded, the required input and optional behavior are stated next, and the important negative constraint about bookable slots is placed last. Every sentence contributes useful routing or behavioral 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 search/list tool with one required parameter and clear annotations, the description is complete: it tells the caller where to get the metro value, what inputs are optional, what fields are returned, what the output is NOT, and how to chain the result into related sibling tools. No output schema exists, but the return shape is described sufficiently.

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 handles parameter meaning well. The description still adds value by explaining that the metro slug comes from tock_list_metros, giving an example value, and characterizing query as an optional text filter. This is slightly more than the schema alone provides.

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 opens with a specific verb and resource: 'List / search restaurants in a Tock metro.' It also draws clear contrast with siblings by noting it returns Tock slugs to use with tock_get_restaurant/tock_get_availability and explicitly excludes bookable slots, so an agent can distinguish it from availability or reservation tools.

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 description explicitly says to pass a metro slug from tock_list_metros, making the dependency on a sibling concrete. It also tells the agent what to do with the returned slugs and warns that bookable slots are not included, which positively routes the agent to the correct alternative for availability.

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 cover readOnly/openWorld, but the description adds real behavioral context: the verdict enum, the caveat that a not_found within minutes of booking is inconclusive rather than proof, and the hard prerequisite of a signed-in browser tab via the ContextMint Bridge. The auth requirement would be undiscoverable otherwise, so the description carries its own weight.

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 but front-loaded: the core action and verdict semantics come first, followed by the usage mandate, then the reporting rule and the prerequisite. No sentence is 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?

With no output schema, the description still supplies the return contract by naming all three verdicts, states the auth prerequisite, and gives downstream reporting instructions for the inconclusive case. Nothing an agent needs to call and correctly interpret this tool 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 description coverage is 100%, so all four parameters (date, venue, partySize, bookedMinutesAgo) are documented in the schema itself, which already notes that bookedMinutesAgo drives the lag caveat. The description repeats that lag concept but adds no syntax or matching detail 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?

States a specific verb and resource — verifying a Tock reservation by re-querying the account's own reservation lists — and explicitly enumerates the three verdict outcomes. This is clearly distinct from the tock_list_reservations sibling, which merely lists reservations without returning a verdict.

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 when to use it ('after ANY booking attempt') and why (a success screen or screenshot is not proof), and it also gives handling guidance for the not_found case ('report as attempted, unverified'). That is usable when/when-not guidance that pins down behavior well beyond the obvious.

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