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 discloses that the tool 'Lists all' reviews and returns a comprehensive set of fields per review, indicating a read-only behavior (GET) without side effects. It does not hide the requirement for contributorId or the pagination mechanism. While it doesn't state 'read-only' explicitly, the description's phrasing and the GET method imply it, and no behavioral surprises are hidden.

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 two sentences plus a use-case list, with no fluff. It front-loads the core action ('Lists all...') immediately, then provides targeting details and return fields, and ends with concrete use cases. Every sentence adds information relevant to invocation; there is no repetition or 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?

Given the tool's moderate complexity (5 params), lack of annotations, and no output schema, the description is remarkably complete. It states what the tool returns (rating, text, date, place details, photos, owner responses), mentions targeting and pagination, and provides clear application scenarios. An agent has sufficient context to call this tool correctly and interpret the response.

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 by linking 'language/country targeting' to the hl and gl parameters, and 'nextPageToken pagination' to the nextPageToken parameter, and clarifies the primary 'by contributorId' scope. It enriches the schema without being redundant, so a 4 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?

The description clearly states a specific verb ('Lists') and a specific resource ('all Google Maps reviews authored by a specific Local Guide / contributor by contributorId'). It also lists the returned fields (rating, text, date, place name, etc.), making the tool's function unambiguous. It distinguishes from siblings like getMapReviews by emphasizing the contributor-scoped nature, which is not evident in other tool names.

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 explicit use cases ('reviewer reputation checks, detecting fake/bot review patterns, local-guide activity analysis, and building review-author profiles for trust scoring'), which clearly indicate when to use this tool. It does not explicitly name alternative tools or exclusion criteria, but the use cases are specific enough to guide an agent. This is better than the MID example but not as strong as naming a sibling.

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 provided, the description carries the full burden of behavioral disclosure. It explicitly mentions pagination via nextPageToken, filtering via categoryId (listing values like 'all, latest, menu, by owner, videos, street view'), and the return fields (image URL, thumbnail, upload date, uploader, photoId). This gives the agent a clear picture of what happens when called, though it does not cover rate limits, authentication, or error behavior.

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 compact and front-loaded: the title 'Get Place Photos' immediately states the action, followed by a single paragraph that packs all essential details without redundancy. Each sentence contributes new information—pagination, filtering, return fields, and use cases. 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?

Given the tool's complexity (5 parameters, no output schema, no annotations), the description covers the key aspects: purpose, parameters, pagination, filtering, and return data. It could be improved by mentioning edge cases (e.g., handling of no results, or interaction between dataId and placeId) but the core information an agent needs to call it correctly is present.

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. The description adds meaningful semantics beyond the schema: it explains how dataId/placeId identify the place, what categoryId filters (with explicit values), and how nextPageToken drives pagination. It also clarifies the shape of the return object, which is not in the schema. This goes beyond simply restating parameter names.

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 clear verb-resource pairing: 'Fetches the photo gallery of a Google Maps place'. It specifies the two identifying parameters (dataId/placeId) and distinguishes itself from sibling tools (reviews, details, posts, search) by focusing solely on photos. The purpose is unambiguous and not a tautology.

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 concrete use cases ('restaurant-menu extraction, venue/ambience visual audits, building rich place detail pages, and sourcing up-to-date imagery for POI listings'), which clearly contextualize when to use this tool. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5 but is well above vague 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?

No annotations are provided, so the description carries the full burden. 'Fetches' implies a safe read operation, and the 17-field return list discloses what the agent gets. But it does not mention rate limits, auth requirements, error conditions, or pagination behavior — gaps for a no-annotation tool, though acceptable for a straightforward GET.

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 plus a use-case list, with the purpose front-loaded and the return payload enumerated compactly. The use-case list is slightly redundant with the resource description but earns its place as routing signal. No filler or repetition.

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?

Moderate complexity (3 params, 1 required) with no output schema, so the description rightly compensates by enumerating the full return fields. The placeId source is covered by the schema. Missing only edge details like limits or error handling, which are minor for a details-fetch tool.

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 already documents all three parameters. The description adds only minimal meaning via 'optional domain/language localization,' which loosely maps to hl and domain. The schema itself already notes language-code and Google-domain constraints with allowed values, so the description adds little beyond 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?

The description states a specific verb (Fetches) and resource (full Google Maps place data by placeId), then enumerates the return fields explicitly. It clearly distinguishes itself from the sibling tools (search, reviews, photos, posts) by being the single place-details endpoint.

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 clear use cases (local SEO audits, POI enrichment, lead generation, competitor mapping, location-aware agents) and the 'by placeId' phrasing implies it should follow a search that yields an ID. However, it does not explicitly name alternatives or state when not to use it, leaving sibling differentiation to 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?

No annotations are provided, so the description carries the full burden. It states it is a 'paginated fetch' and describes the returned data, implying a read-only operation, but it does not explicitly say it has no side effects or mention any prerequisites (e.g., needing one of dataId/placeId). The GET verb in the title helps, but the description itself is not explicit.

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 concise, starting with the core purpose, then listing use cases. It is efficient and easy to parse, though it could be slightly more structured with parameter explanations.

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?

Moderate complexity with four optional parameters and no output schema. The description lists returned fields and mentions pagination, which covers most essentials. However, it lacks an explicit note that either dataId or placeId is required, and does not describe any rate limits or error conditions. Given the sibling context and schema coverage, it is sufficiently complete for basic invocation.

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 covers all four parameters with descriptions, so baseline is 3. The tool description adds context by mentioning 'language targeting' and 'nextPageToken pagination' and that it fetches by dataId or placeId, which helps clarify the parameter usage 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 clearly states the tool fetches Google Maps Posts (timeline-style updates) for a place, distinct from sibling tools for reviews, photos, and place details. It specifies the resource and action precisely.

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 explicit use cases (small-business intelligence, local-marketing monitoring, etc.) and mentions the pagination and targeting options. However, it does not explicitly state when to use this tool over siblings, though the purpose differentiation is fairly obvious.

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 are not provided, so the description must carry the full burden of behavioral disclosure. It mentions 'Paginated fetch', which implies pagination behavior, and lists the exact fields returned (author name, profile link, star rating, etc.). This is valuable transparency. However, it omits details such as rate limits, error handling, the requirement to supply either dataId or placeId (which is only in the schema), and behavior when no results are found. With no annotations, a 3 is fair—it provides some behavioral context but leaves gaps.

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 concise and well-structured. It opens with a one-sentence summary, then a second sentence detailing the fetch parameters and returned data, and a final sentence on use cases. Every sentence adds value, with no redundancy or fluff. The key capabilities are front-loaded, making it easy for an agent to quickly grasp the tool's functionality.

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?

Given that there is no output schema, the description compensates by listing the exact fields returned per review, which is highly useful for an agent. It also covers the input parameters and use cases. However, it does not explicitly state the requirement to set either dataId or placeId, and pagination behavior is only implied by the word 'paginated' without explaining the nextPageToken. These gaps prevent a perfect score, but overall, the description is quite complete for a fetch tool.

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 has 100% coverage, with all six parameters having descriptions. The description adds minimal new meaning beyond the schema: it summarizes that sorting and filtering are possible and mentions language, but these are already in the schema. The description does not clarify parameter constraints further, such as the exact format of dataId or how nextPageToken is used. Since the schema already handles the semantics, a 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?

The description opens with 'Get Map Reviews' and then provides a detailed explanation: 'Paginated fetch of Google Maps reviews for a place by dataId or placeId, with sort...'. This clearly states the verb (fetch), the resource (Google Maps reviews), and the key distinguishing capabilities (pagination, sorting, filtering). It differentiates from sibling tools that handle photos, place details, posts, or search, leaving no ambiguity about the tool's purpose.

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 includes explicit use cases: 'Use for reputation management, sentiment and topic mining, competitor review benchmarking, and feeding review data into summarization or trust-score LLMs.' This provides clear context on when to use the tool. However, it does not explicitly state when not to use it or name alternative tools, relying on the sibling list for that. Since the context is clear but exclusions are absent, a score of 4 is appropriate.

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 discloses pagination via 'start' and the return format, but does not explicitly state that the operation is read-only or mention any rate limits, authentication, or error behavior. While a search is inherently non-destructive, the description could have added more explicit behavioral 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?

The description is front-loaded with a clear one-line summary followed by a concise explanation of parameters, return values, and use cases. It is efficient without irrelevant details, though slightly more verbose than strictly necessary.

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 search tool with 6 parameters (only 1 required), no output schema, and no annotations, the description covers the essential aspects: action, return fields, parameter roles, and when to use it. It lacks explicit handling of edge cases or limitations, but is adequate for an agent 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?

Schema coverage is 100% with detailed descriptions for every parameter. The description adds light context by grouping parameters (e.g., 'optional GPS coordinates' and 'offset-based pagination') and clarifying the purpose of 'll' and 'start', but it does not significantly go beyond the schema. Thus 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 'Get Google Maps Search Results' and 'Runs a Google Maps search by keyword', clearly stating the action and resource. It specifies the output (local pack list with defined fields) and implicitly distinguishes itself from sibling tools (reviews, photos, place details) since it is the search entry point.

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 lists explicit use cases ('local lead generation, competitor density mapping, market expansion research, hyperlocal directories') and mentions downstream tools ('feeding placeIds into the Maps Place, Reviews, or Photos endpoints'), which helps an agent decide when to use this tool. However, it does not explicitly state when NOT to use it or name alternatives directly, leaving a small gap.

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