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

No annotations are present, so the description carries the full disclosure burden. It states the tool is a read operation returning normalized product-detail data, lists the returned fields, and discloses the not-found error condition. While it does not cover rate limits or other potential failure modes, for a simple single-SKU lookup this is adequate transparency.

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 cover purpose, output content, parameter derivation, and error behavior with zero redundancy. The core action is front-loaded, making the description easy to parse quickly.

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 tool with no output schema and no annotations, the description is complete: it explains what the tool returns, where the input comes from, and what happens on failure. Nothing essential for invoking it correctly or interpreting its results 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?

The schema already documents product_id fully (100% coverage), but the description goes far beyond it: it gives a concrete SKU example (JI0397), explains two distinct ways to derive the value (search result field or URL segment), and states the error behavior for invalid IDs. This materially improves an agent's ability to supply the correct value.

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 uses a specific verb ('Get') and resource ('Adidas product'), and immediately clarifies it returns detail for a single SKU. The enumerated return fields (name, brand, category, pricing, images, size variants) make it distinct from search/list siblings without needing to open the 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?

The description clearly states the prerequisite: you need an Adidas SKU, and it tells the agent exactly where to obtain it (from a search result's products[].id field or a product page URL). It also discloses the not-found error behavior for unknown IDs. It does not explicitly name alternative tools, but the context is unambiguous enough for an agent to decide when to use this tool.

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 covers important edge-case behavior: keyword search is best-effort, empty keyword returns an empty list, page beyond range or unknown category returns a not-found error, and pagination is real. It also explains how to derive category slugs from URLs and response fields, which is highly transparent.

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 structured logically: purpose first, then required arguments, return contents, behavioral caveats, and category derivation. Every sentence provides useful information with no redundancy, and it remains readable despite its density.

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?

This is a complete description for a search/browse tool with no annotations and no output schema. It covers both usage modes, required parameter constraints, return summaries, facets, sort options, pagination, error behavior, and category slug derivation. Nothing essential for invoking the tool correctly 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?

The input schema already documents all four parameters clearly (100% coverage). The description adds meaningful extra semantics: explains how to construct category values from Adidas URLs or response breadcrumbs/filters, clarifies the one-of requirement, and describes empty-search and page-boundary behavior. This goes beyond the schema but does not redefine each parameter in full detail.

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: 'Searches Adidas.com product listings by keyword, or browses a category listing by taxonomy slug.' It clearly distinguishes the two modes (keyword vs. category browse) and separates this tool from siblings like adidas_product (single product) and adidas_suggest (autocomplete).

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 usage context: exactly one of query or category is required, plus real pagination and sort options. It also warns about best-effort keyword match and not-found error cases. However, it does not explicitly name sibling alternatives or state when not to use this tool, so it falls just short of a 5.

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 delivers: it discloses the error behavior ('An unknown store_id returns a not-found error'), states the data is 'normalized,' and lists the exact response content — the key uncertainties for a single-id GET. It could go further (rate limits, coordinate format, meaning of 'status'), but the not-found disclosure is genuine value beyond the name and schema.

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, each earning its place: instant action, return payload, parameter provenance, and error behavior. The most important information (what it does and what it returns) is front-loaded, with zero filler or repetition of schema content.

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 tool (1 required param, no output schema, no annotations), the description is nearly complete: the field enumeration substitutes for the missing output schema, the id-source hint covers the workflow, and the error case is handled. Minor gaps like coordinate format and phone formatting are the only omissions, and they don't block correct 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 coverage is 100%, so the baseline is 3. The description adds real value beyond the schema by clarifying that store_id is numeric (the schema only says 'string', which could lead an agent to pass a slug or name) and by pinning the exact source field (stores[].id). This extra precision 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 opens with a specific verb+resource ('Get an Adidas store') and precisely enumerates the returned payload (name, status, phone, address, coordinates, hours, in-store services). It is clearly distinct from siblings: the reference to an 'adidas-stores response' differentiates this detail-by-id tool from the plural listing tool, and 'retail store' separates it from adidas_product/adidas_search.

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 context is implied through the store_id provenance: 'taken from an adidas-stores response's stores[].id field' tells the agent this tool is meant to be called after adidas_stores, with an id obtained from that listing. However, there is no explicit statement of when to choose this over alternatives, and no exclusions or fallback guidance — the routing 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.

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

With no annotations, the description carries the full behavioral burden, and it delivers: it discloses the upstream source, the ignored radius, the ~20 store cap, distance ordering, and the empty-list instead of error behavior. These are exactly the kinds of quirks an agent needs to set correct expectations.

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 the main purpose, and every sentence earns its place: scope, return fields, required params, upstream behavior, and edge-case behavior. There is no fluff or repetition, making it dense but highly readable.

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 there is no output schema, the description enumerates the returned fields (name, address, phone, coordinates, distance, hours, feature flags) and covers ordering, result limits, and empty-list behavior. Parameters are fully documented in the schema, so nothing an agent needs to invoke this correctly 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 confirms lat/lng are required and notes the upstream returns ~20 stores, which gives pagination context for the page parameter, but it adds no additional semantic detail beyond what the schema already documents.

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 'Find nearby Adidas stores' and specifies it returns physical retail stores nearest to a coordinate, which is a clear verb+resource+scope. It is implicitly distinct from the sibling adidas_store (singular) but does not explicitly name or contrast it, so it falls 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?

The description makes the intended context obvious: call this when you need Adidas physical stores near a coordinate, with lat/lng required. It does not explicitly mention alternatives or exclusions, but the coordinate-based usage and store-finder framing provide clear context without ambiguity.

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. It discloses that Adidas has no separate term-autocomplete index, that suggestions are matching products rather than phrases, and that relevance is best-effort without guarantees for obscure queries. It does not detail pagination or exact result count, but the key behavioral quirks are documented impressively.

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 sentences, each informative: what it does, product-based results, absence of autocomplete index, and best-effort caveat. Front-loaded and no 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 a single parameter, no output schema, and no annotations, the description covers return shape, operational behavior, and expectations. Could mention count limits or formatting variations, but it is complete for practical 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 coverage is 100% and the only parameter, query, is described as 'Partial search query'. The description adds the meaning that the query feeds the search-as-you-type preview, but it doesn't provide examples or length/format constraints beyond the schema. Baseline 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 clearly states it returns Adidas search suggestions for a partial query, as a search-as-you-type preview, and distinguishes the actual return type (matching products with id, title, url, image, price) versus completed search phrases. The specific verb 'Get' plus resource and behavior makes it clear among many suggest siblings.

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 to use the tool (for partial queries / as-you-type preview) and distinguishes it from a hypothetical completed-phrase autocomplete. It could explicitly mention an alternative like adidas_search, but the description conveys the context well.

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 behavioral nuances: keyword fallback to resolved city name, city_id precedence, and credential-free public data sourcing. It stops short of describing pagination or result format, but for a search tool this is notably transparent.

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 sentences, each packed with distinct information. Front-loaded verb and resource, no fluff, and the fallback/precedence rules are stated compactly without 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?

Given the tool's simplicity (3 optional params, no output schema), the description covers the main invocation patterns and parameter interactions. It could mention result structure or limits, but the core selection criteria are well addressed.

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 already covers all three parameters with descriptions, but the description adds meaningful behavioral semantics: how keyword omission triggers city-name search, and the city_id > city precedence rule. This goes beyond simple parameter mapping.

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: 'Search Agoda activities' and clarifies the result type as 'tours, attractions, experiences'. This clearly distinguishes the tool from the sibling agoda_activity_detail (which retrieves a single activity) and other Agoda search 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?

Provides clear usage context: can search by keyword and/or city, fallback to city name when keyword is omitted, and city_id precedence over city. However, it does not explicitly name alternative tools or state when not to use this tool, so it misses the top tier for explicit exclusions.

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. It discloses that the data is credential-free and from Agoda's own content source, which is helpful. However, it does not detail potential limitations such as stale data, partial responses, or error behavior for invalid IDs, leaving some behavioral 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?

Three short sentences, each adding value: purpose, return fields, and data source/credential status. No fluff, though 'Get Agoda activity detail' and 'Returns full activity detail from Agoda' are slightly redundant, so not a perfect 5.

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 single-parameter tool with no output schema, the description is adequate: it lists return fields and notes the public nature of the data. However, it omits details about response structure, image URL formats, or reliance on a prior search (only in schema), leaving moderate gaps.

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 parameter is fully described in the schema as a numeric activity id from a prior search. The tool description does not add any additional parameter semantics, so the baseline score 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 clearly states the action ('Get') and the resource ('Agoda activity detail'), and enumerates the specific content returned (title, description, duration, categories, images). It distinguishes itself from sibling search tools like agoda_activities_search by focusing on detail retrieval for a single activity.

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 provides no explicit guidance on when to use this tool versus alternatives. It does not mention that an activity_id from a prior search is required or point to the search tool. The need for a prior search is only implied via the schema's parameter description, not the tool description itself.

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?

Despite having no annotations, the description discloses key behavioral traits: 'Credential-free public data' and 'from Agoda's own flight content service'. This tells the agent no authentication is required and identifies the data source. It also mentions 'real-content amenities', implying live data. It does not detail error behaviors or rate limits, but the provided context is meaningful.

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 three sentences, each contributing essential information: what the tool does, what it returns, and how to obtain the input. It is front-loaded with the verb 'Get' and contains no redundant language.

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 simplicity (one nested parameter, no output schema) and absence of annotations, the description covers the essential aspects: purpose, return content, input source, and auth requirements. It does not outline the return structure or pagination, but for a straightforward amenities lookup, it is sufficiently 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 coverage is 100% with only a generic 'body' parameter described as 'One or more flight segments to fetch amenities for.' The description adds value by instructing to 'copy the segments straight from a flight search response's own segment fields,' which clarifies the source and format of the input. However, it still does not specify the exact nested structure or how multiple segments are represented, so it only modestly supplements 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's function: 'Get Agoda flight segment amenities' and enumerates the returned content (aircraft type, seat layout, meals, entertainment, wifi). This distinguishes it from sibling tools like agoda_flights_search, which searches for flights rather than fetching amenities for existing segments.

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 provides practical usage context: 'Copy the segments straight from a flight search response's own segment fields.' This implies the tool is used after a flight search and tells the agent exactly where to obtain the input. It does not explicitly name alternatives or exclusion cases, but the guidance is clear and actionable.

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 of disclosure. It adds useful context: 'Credential-free public data from Agoda's own flight search' and mentions 'bookable' itineraries. However, it does not disclose rate limits, pagination behavior, or error/empty-result handling, which are important for a search endpoint.

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 three sentences with no redundancy. It front-loads the core function, then provides output details, a prerequisite, and auth context—each 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?

The description covers core usage: what it searches, expected inputs (IATA codes, date), output fields, and auth requirements. It omits pagination details, result limits, and round-trip handling, but for a one-way search tool with a self-explanatory schema, it is fairly 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%, so the baseline is 3. The description adds value by emphasizing that origin/destination are IATA codes and instructing to resolve free-text names first, which clarifies parameter usage beyond the schema descriptions. It doesn't detail every parameter, but the schema already does.

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's function: 'Search Agoda one-way flights' and lists specific output fields (per-segment flight number, airline, times, layovers, aircraft type, price). It distinguishes from sibling tools like agoda_flights_search_locations by explicitly focusing on one-way itineraries and referencing IATA codes.

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 provides a clear prerequisite: 'Resolve free-text city/airport names to codes first via the flight destination search endpoint,' which directs the agent to a specific sibling tool. It also implies the tool is for direct IATA-code queries, but does not explicitly discuss alternatives like round-trip searches or other flight providers.

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. It discloses that the tool uses 'Credential-free public data', which communicates a safe, read-only operation, and describes the output behavior ('each city's direct and nearby airports'). However, it does not mention limitations like rate limits, ambiguity handling, or error conditions, which would have made it even more transparent.

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 three sentences, each earning its place: the first states the main action, the second elaborates on the input and output, and the third notes the access requirement. No filler or repetition, and it is front-loaded with the primary purpose.

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 one-parameter tool with no output schema or annotations, the description covers the essential aspects: input format, output type, purpose, and data source. It lacks details on error cases or result formatting, but these are not critical for such a straightforward lookup tool, making 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?

The schema already describes 'keyword' as 'Free-text city or airport name' (100% coverage). The description adds context by explaining that this keyword is resolved into IATA codes, but it does not provide new parameter-level meaning beyond the schema. Therefore, 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 clearly states the tool's function: 'Search Agoda flight destinations/airports' and explains it 'Resolves a free-text city or airport name into IATA airport codes for flight search'. This distinguishes it from sibling tools like agoda_flights_search, which searches actual flights, and provides specific output details (IATA codes, direct and nearby airports).

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 implies when to use this tool by stating it resolves locations 'for flight search', signaling it is a prerequisite lookup step before performing a flight search. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to determine appropriate use.

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 fully carries the transparency burden. It discloses the credential-free/public nature, the city_id precedence rule, the pre-filter limit semantics, the data source relationship to hotel search, and the promise of 'full listing detail' for each result. This goes well beyond the schema.

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, each earning its place: the core purpose, the filtering/data-source behavior, and the input selection semantics. It is front-loaded and free of filler, being appropriately dense for a tool with no annotations and a non-trivial filtering mechanism.

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?

Despite lacking an output schema, the description provides a thorough mental model: what is returned, how results are filtered, how inputs interact, and what authentication is required. Combined with the fully documented schema parameters, the tool is well-specified for an agent to invoke 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% and the schema descriptions already document the precedence rule, the free-text resolution, the 1-indexed page, and the limit semantics. The description paraphrases these without adding new parameter-specific 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 uses a specific verb ('Search') plus a clear resource ('Agoda Homes & Apartments by city'). It distinguishes from sibling agoda_hotels_search by explicitly stating results are 'filtered to non-hotel accommodation types' and drawn from the same city search as hotel search.

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: it is the apartment/homes-focused counterpart to hotel search and explains the two input modes (city_id vs free-text city). It implies when to use this tool (when you need non-hotel listings) but does not explicitly name the alternative tool or state exclusion conditions.

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 transparency burden. It discloses that the data is 'Credential-free public data from Agoda's own hotel content source,' which is valuable context about authentication and source. It also enumerates the exact content returned, giving the agent a clear picture of the operation's behavior and scope, though it doesn't describe error cases or edge behaviors.

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 lists the main return fields in a structured, parenthetical format. It is somewhat long due to the detailed field list, but every element provides useful information and the structure is clean, meriting a 4 rather than 5.

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?

Despite lacking an output schema, the description compensates by explicitly listing the fields to be returned, including policy statements. It also clarifies the data source and credential-free nature. It doesn't cover failure modes or when property_id might be invalid, but for a simple detail endpoint with one parameter, this is sufficiently 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?

The schema covers the single parameter fully with a description explaining property_id is a numeric ID from a prior search or URL. The tool description itself does not add further parameter semantics, so the baseline of 3 applies given 100% schema coverage.

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's function with a specific verb and resource: 'Get Agoda hotel detail.' It enumerates the exact types of data returned (identity, address, rating, photo, room count, chain, descriptions, policies), which distinguishes it from sibling tools like agoda_activity_detail or agoda_homes_search. The title matches the scope 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?

The description implies usage context by stating it returns hotel detail and the schema notes the property_id comes from a prior search call, but it does not explicitly mention alternatives or when to prefer this tool over agoda_hotels_search or other detail tools. There is no direct exclusion of activities or homes, leaving guidance implicit rather than explicit.

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 states that this is 'credential-free public data' from Agoda's own hotel search, indicating no authentication is needed and clarifying the data source. It also discloses the return contents (matching property ids and direct links). It omits details like pagination behavior or rate limits, but for a search tool, the key safety and access traits are well covered.

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 three sentences, front-loaded with the core action and resource, then efficient elaboration on inputs and data source. Every sentence earns its place with no filler or redundancy.

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 has four parameters, no output schema, and no annotations, the description is reasonably complete. It covers purpose, return shape, parameter flexibility, and authentication requirements. It could add more detail about the structure of the returned result set (e.g., pagination metadata), but for a search tool this is a solid level of contextual completeness.

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 all four parameters thoroughly. The description adds marginal semantic value by restating the precedence rule for city_id over city and noting that at least one is required. This is helpful but largely redundant with the schema descriptions, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches Agoda hotels by city and specifies the exact output: matching property ids and direct listing-page links. It distinguishes itself from sibling tools like agoda_hotel_detail (single hotel details) and agoda_homes_search (different property type) by focusing on hotel search scoped to a city.

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 provides clear context on how to use the tool: callers can supply either a numeric city id or a free-text city name, with city_id taking precedence. It does not explicitly name alternative tools or exclusions (e.g., 'use agoda_hotel_detail for a specific property'), so it falls short of a 5, but the intended use case is unambiguous.

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 must cover behavioral traits. It states the return is a 'normalized public host profile' and lists fields, but does not explicitly mention that the operation is read-only, idempotent, or any potential errors. Adequate but not comprehensive.

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, concise sentence that front-loads the purpose and key returned fields. Every word adds value with no redundancy.

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 absence of an output schema, the description adequately lists the returned fields. However, it could mention error handling (e.g., invalid ID) or clarify that only public data is returned, but overall it is fairly complete for a simple profile retrieval 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 only parameter 'id' is described in the schema as 'Host id (numeric)'. The description adds no additional meaning beyond what the schema already provides, meeting the baseline for 100% schema coverage.

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 verb 'Get' and the resource 'Airbnb host profile'. It lists specific returned fields, distinguishing it from sibling tools like airbnb_host_listings and airbnb_host_reviews which retrieve different data.

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 implies this tool is for retrieving a host's public profile, but it does not explicitly state when to use it over alternatives or provide prerequisites. No when-not-to-use guidance is given.

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 discloses pagination behavior (first page from profile, deeper pages from portfolio) but lacks details on read-only nature, authorization, rate limits, or error conditions.

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 purpose. Every sentence adds value without redundancy.

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 low complexity (2 parameters, no output schema), the description covers core functionality well. Minor omissions: no mention of return format, error handling, or data limits.

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 parameters. The description adds no additional meaning beyond what the schema 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 uses a specific verb ('Get') and resource ('Airbnb host listings'), clearly distinguishing it from sibling tools like airbnb_room or airbnb_host. It also mentions pagination, providing strong clarity.

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 implies usage for obtaining a host's listings, but does not explicitly state when to use this tool over alternatives (e.g., airbnb_room for individual listings) 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 must carry the full burden. While it mentions pagination and output fields, it omits behavioral details such as sorting order, rate limits, or whether reviews are in reverse chronological order, which are critical for an API 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?

The description is two sentences, front-loads the core purpose, and every sentence adds value without redundancy.

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 should compensate by detailing return structure. It only mentions reviewer name and location, missing essential fields like rating, date, and text. Pagination details (page size, total results) are absent, leaving significant gaps for agent use.

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 parameters adequately. The description adds no semantic value beyond confirming pagination context; baseline 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 clearly states the verb 'Get' and resource 'host reviews', explicitly mentions output includes reviewer name and location, and distinguishes from similar sibling tools like airbnb_room_reviews by specifying 'host'.

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 implies usage context (when you need host reviews) but does not provide explicit guidance on when to use this tool vs. alternatives like airbnb_room_reviews, nor does it mention prerequisites or exclusions.

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 present, so the description carries the full burden. It only states it returns 'normalized public room details', but doesn't disclose behavior like error handling, rate limits, or whether the id must be a specific format. The description is minimal for 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 concise, using one sentence to convey the core purpose. It front-loads the verb and resource. While it could be slightly expanded, there is no wasted content.

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 tool with one parameter and no output schema, the description covers the basics. However, with many sibling tools, some context about when to use this over similar tools (e.g., airbnb_search, airbnb_room_calendar) would improve completeness.

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 does not add any meaning beyond the schema's 'Room id' for the 'id' parameter. It is adequate but does not enhance understanding.

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 gets an Airbnb room and returns normalized public details. It uses a specific verb and resource, and while it doesn't explicitly differentiate from siblings like airbnb_room_calendar or airbnb_room_reviews, the function is distinct enough for an agent to infer.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or cases where other tools (e.g., airbnb_search) would be more appropriate. Agents are left to infer usage from the name alone.

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 bears full burden. It states the tool returns 'public calendar month hints parsed from Airbnb room bootstrap data', indicating a read-only operation. However, it does not disclose potential side effects, authentication needs, or rate limits, which is acceptable for a simple retrieval tool 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?

The description is two sentences, with the first sentence stating the primary purpose and the second adding detail. It is front-loaded, concise, and contains 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 tool with one parameter and no output schema, the description is adequate but lacks details on the return format or what 'calendar month hints' entail. More context on the output structure would improve completeness.

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 input schema covers the single parameter 'id' with description 'Room id', achieving 100% coverage. The description adds no additional meaning beyond this, so a baseline score 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 clearly states the tool gets the Airbnb room calendar and returns 'public calendar month hints'. The verb 'Get' and resource 'Airbnb room calendar' are specific, and it distinguishes itself from sibling tools like airbnb_room (room details) and airbnb_room_reviews (reviews).

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 implies usage when needing calendar data, but does not explicitly state when to use this tool versus alternatives like airbnb_room. No exclusion or prerequisite information is provided, relying on the tool's name and context for differentiation.

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?

Without annotations, the description only says 'Returns normalized Airbnb public review snippets.' It does not disclose pagination behavior, rate limits, or what 'normalized' entails. Minimal 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?

Two sentences front-load the action and provide direct purpose. No extraneous 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?

Given no output schema, the description lacks detail about the structure of reviews (e.g., rating, text, date). The term 'normalized' hints but is incomplete. Adequate but not comprehensive.

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 describes parameters (id, page). The description does not add meaning beyond what the schema provides, 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?

The description clearly states 'Get Airbnb room reviews' with a specific verb and resource, and distinguishes itself from sibling tools like 'airbnb_room' and 'airbnb_room_calendar' by focusing on reviews.

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?

No guidance on when to use this tool versus alternatives like 'tripadvisor_reviews' or 'googleplay_reviews'. It does not mention prerequisites or context.

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?

Lacks annotations, so description must carry burden. Mentions 'normalized' and 'public web search results', but doesn't explain what normalization means, pagination, or authentication needs.

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?

Very concise, two sentences, no waste. Front-loaded with purpose. Could be expanded but efficient.

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?

Despite 11 parameters and no output schema, description is brief. Doesn't explain bounded map search or results structure. Incomplete for a complex 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 description adds no additional parameter meaning beyond the schema descriptions. Baseline score 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?

Clearly states verb 'Search' and resource 'Airbnb stays', and distinguishes from siblings like 'airbnb_room' by indicating it returns normalized search results.

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?

Implies use for searching stays, but no explicit guidance on when to use vs. alternatives like 'airbnb_room' or when not to use.

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 burden of behavioral disclosure. It does reasonably convey read-only behavior ('List') and output normalization ('Returns normalized products'), and it discloses the fixed server-side storefront URL as a quirk. However, it does not mention pagination behavior, rate limits, authentication, or output shape details.

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 sentences, each earning its place: purpose, scope/normalization, and the critical handle/fixed-URL detail. Information is front-loaded and there is no redundant 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?

The tool is moderately complex: no output schema exists and no annotations are present, so the description should give more context about return structure and pagination. While it explains the core behavior and handle semantics, it leaves gaps such as how an agent discovers valid handles and what fields a 'normalized product' contains.

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 all three parameters. The description adds meaningful semantics for the required `handle` parameter by explaining it is the collection's URL slug, going beyond the schema's generic 'Collection handle'.

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 clear verb and resource: 'List Allbirds collection products' and clarifies that it returns normalized products from one specific collection. This distinguishes it from broader tools like allbirds_products by narrowing scope to a single collection, though it does not explicitly name sibling alternatives.

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 implies usage by explaining that `handle` is the collection's URL slug, which tells an agent where to source the value from. However, it does not explicitly state when to choose this tool over allbirds_collections or allbirds_products, nor does it mention that collection handles can be discovered via another endpoint.

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 adds useful behavior: results are normalized, the storefront URL is fixed server-side, and valid empty pages return 200 with an empty array. It still doesn't describe failure modes, rate limits, or return-shape details, but the disclosed edge case is valuable.

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 sentences, with the action front-loaded and no filler. The URL/normalization note and empty-page edge case each earn their 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 optional-pagination list tool, the description covers source, normalization, and an edge-case response. It doesn't enumerate the fields inside each collection, but that is not necessary to select or invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents both page and limit with defaults and max at 100% coverage, so the description doesn't need to repeat them. It adds the note that the storefront URL is fixed server-side, which clarifies why no source/URL parameter is offered.

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 first sentence, 'List Allbirds collections,' gives a specific verb and resource, and 'collections' clearly separates it from product-level siblings like allbirds_products/allbirds_collection_products. It doesn't explicitly name a sibling or scope boundary, so it stops short of the strongest differentiation.

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 explicit when-to-use or alternative guidance. The first sentence implies the tool is for fetching the Allbirds collection list, but it doesn't say when to choose this over allbirds_collection_products or allbirds_pages.

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 usefully discloses that the storefront URL is fixed server-side and that output is normalized. It does not cover error handling, rate limits, or output structure specifics, which is a moderate gap for an unannotated 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?

Two short sentences with no filler. The first sentence front-loads the action and resource, the second adds return normalization and the fixed-URL constraint. Every sentence contributes meaningful 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?

This is a simple one-parameter tool with no output schema or annotations. The description identifies the required input, the resource type, and a key server-side behavior, which is sufficient for correct invocation. It loses one point for not referencing the sibling allbirds_pages tool to complete the contextual map.

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%, with 'handle' documented as 'Page handle'. The description merely repeats the term without adding format details, examples, or guidance on where to find valid handles. Baseline 3 applies because the schema already covers the single parameter adequately.

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?

Description states a specific action ('Get') and resource ('Allbirds static page'), and clarifies it returns detail for a single page handle. This implicitly differentiates it from sibling list tools like allbirds_pages, though it does not name that sibling explicitly. Minor grammar issue ('a Allbirds') does not undermine clarity.

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 implies usage context: call when you have a specific Allbirds page handle and need normalized static page detail. However, it does not mention alternatives, list tools, or exclusions, leaving the when-not-to-use case unaddressed.

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 present, so the description carries full burden. It discloses that the storefront URL is fixed server-side and outputs normalized static pages, but provides no detail about pagination behavior, rate limits, freshness, or response shape. For a list tool, the lack of behavioral context beyond 'normalized' is a notable gap.

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, compact and front-loaded with the primary action. The URL detail is useful but positioned after the main statement; no redundant 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 simple two-optional-param list endpoint with no output schema, the description is mostly adequate. However, without annotations or mention of what 'normalized' means, return shape, or pagination semantics, it is not fully complete for an agent deciding how to paginate or interpret results.

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 both optional parameters (page, limit) are described in the schema. The description adds no extra semantic detail beyond the schema, 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 'List' and resource 'Allbirds static pages', mentions normalized output from allbirds.com. It lacks explicit comparison to sibling tools like allbirds_page or allbirds_sitemaps, but the scope is reasonably clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when-to-use versus alternatives, but the description conveys it is for listing static pages; the fixed server-side URL and normalized output contextualize usage. It does not name alternatives such as allbirds_page or allbirds_sitemaps, so usage guidance is implied rather than explicit.

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 usefully explains that the storefront URL is fixed server-side and that the handle is the URL slug, and it states the return is normalized product detail. However, it does not mention whether the operation is read-only, what happens for invalid handles, or any error/response 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 only two sentences, front-loads the core action and output, and adds the parameter clarification without any wasted words. Every sentence contributes useful 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 low-complexity, single-parameter tool, the description is largely complete: it identifies the resource, the input semantics, and the return type. It does not describe error cases or explicitly confirm read-only behavior, but given the simplicity of the tool, this is a minor gap rather than a serious omission.

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 parameter is already documented, but the description adds meaningful context beyond the schema by clarifying that 'handle' is the product's URL slug and that the base URL is fixed server-side. This helps the agent understand exactly what value to supply.

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 that the tool fetches a single Allbirds product by handle and returns normalized product detail, which is a specific verb+resource combination. It differentiates from plural-oriented siblings like allbirds_products through the explicit 'one ... product handle' phrasing, though it does not name any sibling directly.

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 implies when to use the tool: when you have a single Allbirds product handle and want normalized details. However, it does not explicitly state when not to use it or mention alternatives like allbirds_products or allbirds_product_recommendations, so the usage guidance is present but mostly 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?

With no annotations, the description carries the full burden, and it does add meaningful behavior: returns normalized products, resolves the handle to a Shopify product ID server-side, and uses a fixed storefront URL. These details go beyond a simple 'list recommendations' statement and help the agent understand internal resolution and why there is no storefront parameter. It stops short of disclosing error behavior or output 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?

Three sentences, no filler. The first sentence states the core action, the second defines the object and output, and the third clarifies internal behavior. Each sentence earns its place and the most important information is front-loaded.

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 lack of output schema and annotations, the description covers the essential context: what the tool returns (normalized recommended products), what input it needs (a handle), and how that handle is processed. It does not describe the returned recommendation fields, but for a simple recommendations tool with well-documented parameters, this is reasonably 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%, so the baseline is 3. The description adds extra meaning to the handle parameter by clarifying that it is a route handle resolved to a Shopify product ID before fetching, which is not in the schema. Limit and intent are already well described in the schema, so no additional burden on the description.

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 Allbirds product recommendations.' It further clarifies that it operates on a single product handle, which distinguishes it from sibling tools like allbirds_product (single product details) and allbirds_products (list all products). The mention of normalized recommended products makes the purpose concrete.

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 implies when to use the tool: when the agent needs product recommendations for a single Allbirds product handle. However, it never explicitly names alternatives or states when not to use it, such as pointing to allbirds_product for product details. The usage context is clear but no exclusionary guidance is provided.

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, and it delivers: it states output is normalized, the storefront URL is fixed server-side, and — most valuably — that valid empty result pages return 200 with an empty products array, which prevents an agent from misinterpreting an empty response as an error. It doesn't cover pagination metadata or rate limits, but for a simple catalog list this is solid 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?

Three sentences, all essential and non-redundant. The purpose is front-loaded in the first sentence, the data source context comes second, and the behavioral caveat closes. No filler, no repetition of schema content.

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?

This is a simple paginated list tool with two optional, fully-documented parameters; the description covers purpose, source, normalization, the fixed-URL constraint, and the key pagination edge case. The main gap is that with no output schema, 'normalized products' leaves the return shape unspecified — an agent doesn't know what fields a product object contains until it makes a call.

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% — page (1-based, defaults to 1) and limit (defaults to 50, up to 250) are both fully documented in the schema, so the description needs to add little. It does add one meaningful piece: the empty-array-on-valid-page behavior clarifies how the page parameter's results should be interpreted. This matches the baseline 3 for fully-schema-covered parameters.

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?

'List Allbirds products' is a specific verb+resource that clearly states the operation. The added detail — 'public product catalog' with a fixed server-side URL — helps distinguish it from collection-scoped or store-scoped siblings like allbirds_collection_products and allbirds_store. However, it never explicitly names a sibling alternative, so the differentiation is implicit rather than explicit.

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 implies when this tool is useful (browsing the entire Allbirds product catalog) and the fixed-server-side-URL note hints that no storefront selection is needed, but it gives no explicit when-to-use guidance or exclusions versus the many related allbirds_* siblings. The empty-page-returns-200 behavior adds useful interpretation context, but nothing tells an agent to prefer this over allbirds_collection_products for a collection-scoped query.

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 behavioral burden. It discloses that the endpoint is credential-free and the URL is fixed server-side, which is useful operational context. It does not disclose pagination, default response shape, or whether 'types' restrict output or merely prioritize, but for a search-suggest read tool this is a moderate coverage.

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: one sentence states the purpose and return categories, a second gives the source URL and endpoint characteristic. It front-loads the core function and adds the important credential-free and fixed-URL notes with minimal 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 small read-only suggest tool, the description plus full schema coverage is reasonably complete. It could further explain response shape or type restrictions, but with no output schema and no annotations, the description still covers the call context (endpoint, auth-free nature, result categories). The missing pieces are minor for an agent choosing and invoking this 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 description coverage is 100%, so the schema documents q, limit, and types. The description adds that results are grouped by type (products, collections, query suggestions) but does not clarify details like the meaning of the types comma-separated values beyond the schema's allowed values. Baseline 3 is appropriate because the schema does the heavy lifting and the description adds only the return-category context.

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 action (get search suggestions), the data source (Allbirds), and the return types (products, collections, query suggestions). It distinguishes itself from other Allbirds tools by targeting the predictive search/suggest endpoint rather than product listing or store endpoints, though it doesn't explicitly name the sibling it is not.

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 says it calls Allbirds's credential-free predictive search Ajax endpoint, which implies it is for autocomplete-style suggestions, and the fixed storefront URL signals no auth/location setup. However, it does not state when to prefer this over allbirds_search, allbirds_products, or other suggest siblings, nor does it give exclusion conditions.

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 transparency burden. It discloses what the tool returns (child sitemap URLs with inferred types), the source (/sitemap.xml index), and a key behavioral constraint (storefront URL fixed server-side). This is solid for a zero-parameter read-only listing tool, though it does not mention rate limits or output shape.

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 sentences with no filler. The main action is front-loaded, and each subsequent sentence adds necessary detail about output and server-side behavior. 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 no-parameter, no-output-schema tool, the description covers the essentials: what it lists, where it fetches from, and that no configuration is needed. It could specify the exact return format structure (e.g., array of {url, type}) but that is a minor gap for a simple sitemap index listing.

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?

There are zero parameters, so the baseline is 4. The description adds value by explaining that no parameter is needed because the storefront URL is fixed server-side, which preemptively answers why the input schema is empty and reassures the agent that no URL argument is expected.

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 starts with a clear verb and resource: 'List Allbirds sitemaps.' It specifies that the output is child sitemap URLs from the /sitemap.xml index with inferred sitemap types, which precisely distinguishes it from the sibling allbirds_sitemap_urls and other per-brand sitemap 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 usage context is implied: an agent uses this when it needs an overview of Allbirds's sitemap structure. However, there is no explicit guidance about when to prefer this over the sibling allbirds_sitemap_urls or which tool to choose for a given task, leaving some inference to the agent.

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. It usefully discloses that results are capped, that entries come from child sitemaps, and that the storefront URL is fixed server-side. However, it does not describe return structure, pagination behavior, or what happens when no type is supplied.

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 sentences, each carrying distinct useful information: what is listed, where entries come from, and an important fixed-server-side constraint. It is front-loaded and contains no 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?

This is a simple tool with fully documented optional parameters, but there is no output schema and no annotations. The description explains the result is a capped set of URL entries but not the output shape, and it does not clarify the relationship to allbirds_sitemaps or allbirds_store, leaving some contextual gaps.

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 the type allowed values and the limit default/maximum. The description adds only minor framing like 'matching the requested type' and 'capped', which does not meaningfully go beyond the structured parameter definitions.

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 uses a specific verb and resource: 'List Allbirds sitemap URLs' and clarifies that results come from Allbirds child sitemaps filtered by type. It is clearly a URL-listing tool, but it never explicitly distinguishes itself from the sibling allbirds_sitemaps tool, so it misses full sibling differentiation.

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 about when to use this tool versus alternatives such as allbirds_sitemaps, allbirds_products, or allbirds_store. The description tells what the tool does but not which situations call for it or when a sibling would be more 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 provided, the description carries the full burden of behavioral disclosure. It reveals the data source (credential-free storefront JSON), the fixed server-side URL, and a detailed fallback chain if the vanity domain blocks `/products.json`, including falling back to a discovered `*.myshopify.com` domain or embedded page data. It does not detail the exact fields within the returned metadata, but it is substantially transparent about how the tool operates.

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 sentences, each carrying essential information: purpose, data source, relationship to the generic Shopify family, parameter restriction, and fallback behavior. It is front-loaded with the primary purpose and contains 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?

The tool is a simple zero-parameter, brand-pinned endpoint, and the description covers its purpose, data source, credential-free nature, and fallback resolution. The only gap is that the exact contents of 'store metadata' are not enumerated, but since there is no output schema and the term is reasonably informative, this is a minor shortfall for invocation purposes.

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 input schema is empty and there are zero parameters, so the baseline is 4. The description adds meaningful parameter-related context by explicitly stating that no `url` parameter is accepted because the URL is fixed server-side, preventing an agent from attempting to pass one. This goes beyond the schema and earns a 5.

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 and resource ('Get Allbirds store metadata') and then identifies the exact brand URL and the fact that this is a brand-pinned wrapper around the generic Shopify store family. This differentiates it from both the generic shopify_store and the many other allbirds_* sibling tools (e.g., allbirds_products, allbirds_collections, allbirds_sitemaps), leaving no ambiguity about what the tool does.

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 states that this is a brand-pinned wrapper with the storefront URL fixed server-side and that no `url` parameter is accepted, effectively indicating when to use this tool (Allbirds) versus the parametric generic Shopify store family. It does not explicitly name alternative tools or give an explicit when-not-to-use statement, so it falls slightly short of a 5.

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 reveals that data is parsed from a stable server-rendered page and that no separate JSON endpoint exists. This adds meaningful context about the data source and reliability, though it does not describe error handling or output 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?

The description is extremely concise, two sentences, with no redundant or extraneous information. It front-loads the core purpose and then gives the key parameter source and technical context.

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?

The tool has no output schema and no annotations, so the agent must rely on the description to understand return details. While the description says it returns 'one Amazon.jobs posting', it does not enumerate fields or outline error behavior, leaving some ambiguity for a simple one-parameter 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 already provides a description for the id parameter, but the tool description adds that it is the field returned by search, giving the agent a clear origin and expected value. This adds value beyond the schema's minimal 'Numeric Amazon job id'.

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 returns one specific Amazon.jobs posting by numeric job id, using the specific verb 'Returns' and identifying the resource. It distinguishes itself from the sibling search tool by emphasizing 'single posting' and by noting the id comes from search.

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 implies a workflow by saying the id is 'the `id` field returned by search', which clarifies when to use this tool. However, it does not explicitly name the search sibling tool or state when not to use this tool, leaving some room for ambiguity.

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 the credential-free nature (no auth required), the fact that results include full descriptions and qualifications, and the exact sort semantics (relevant vs recent). It also clarifies that category works standalone. This is substantial behavioral information, though it doesn't cover pagination limits or error 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?

The description is concise at roughly 100 words, front-loaded with the tool's purpose, and each sentence provides essential information: purpose, output content, sort options, and the q/category requirement. There is no redundancy 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 has 6 parameters, no annotations, and no output schema, the description covers the critical aspects: data source, auth-free access, result contents, sort values, and the q/category constraint. It doesn't describe pagination controls (though page/limit are in the schema) or return envelope details, but the provided information is sufficient for an agent to make informed calls.

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 already documents all 6 parameters with descriptions (100% coverage), so the baseline is 3. The description adds value by enumerating the valid sort values (`relevant` default and `recent`) and explaining that category can be used without a text query, which is not clear from the schema alone. This additional context 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 clearly states the tool searches Amazon's public careers site (amazon.jobs) via a credential-free JSON API, distinguishing it from other search tools like amazon_search (product search) and amazon_jobs_job (likely job detail). The verb 'searches' and explicit resource make the purpose unambiguous.

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 provides clear context for when to use this tool: to search Amazon's public careers site. It also includes important usage constraints like the need to provide either q or category, and explains that category can work with no text query. However, it doesn't explicitly name alternative tools or when not to use this tool, so it falls short of a perfect score.

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 must carry the full burden. It lists returned data but lacks details on error handling, rate limits, authentication, or any side effects. It does not contradict annotations.

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 that succinctly convey purpose and returned content. Every word is necessary, no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but the description lists key return data (pricing, availability, etc.). However, lacks structure details. Adequate for a simple retrieval 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 describes parameters adequately. The description adds no extra meaning beyond listing output content, thus baseline 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 clearly states 'Retrieve Amazon product details' with a specific verb and resource, and includes the scope (by ASIN on amazon.com). It distinguishes from siblings like amazon_search by focusing on a single product detail retrieval.

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 provides clear context for when to use (to get details for a specific ASIN), but does not explicitly state when not to use or mention alternatives. However, among siblings, the distinction is 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?

With no annotations, the description must disclose behavior; it only mentions returning normalized result cards but fails to explain pagination, sorting, or any side effects or 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 concise (two sentences) and front-loaded with the action, but it could include more context without being excessively long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description does not explain what 'normalized Amazon search result cards' entails, nor does it cover sorting or page behavior, leaving gaps for a search 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 description coverage is 100%, so the description adds no additional meaning beyond what the schema already provides for parameters, meeting the baseline of 3.

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 it searches Amazon products and returns normalized search result cards for amazon.com, differentiating it from sibling tools like amazon_product and amazon_suggest.

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?

No guidance on when to use this tool versus alternatives (e.g., amazon_suggest for suggestions or amazon_product for details), no exclusions or contextual prerequisites provided.

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 full burden. It states it returns suggestions from a public API, but does not disclose rate limits, caching, or the exact return format. It provides basic transparency but lacks detail.

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 only two sentences, front-loaded with the primary action, and contains no superfluous information. Every word serves a purpose.

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 tool with one required parameter and no output schema, the description is mostly complete. It specifies the source and scope. However, it could mention the return format (e.g., array of strings) for full completeness.

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 parameter description 'Suggestion prefix' already clarifies semantics. The tool description adds no new parameter-level information, matching the baseline score.

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 verb 'Retrieve' and the resource 'Amazon search suggestions', specifying it returns typeahead keyword suggestions. It distinguishes from sibling suggest tools by naming 'amazon.com' and the typeahead nature.

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?

No guidance is provided on when to use this tool versus alternatives like `amazon_search` or other suggest tools. The description only explains what the tool does, without context on when it 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 states the tool returns upcoming broadcasts, is paginated, and credential-free, but lacks details on rate limits, data freshness, error handling, or what happens when no upcoming episodes exist.

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, front-loads the core purpose, and includes only essential information without redundancy. Every sentence adds value.

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 no output schema, the description lists the return fields and mentions pagination and ordering. It also identifies the data source (AniList). However, it does not specify the format of time fields (e.g., UTC offset) or countdown units, leaving minor gaps.

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 description does not need to add more, but it does not provide additional context beyond what the schema already offers (page defaults, per_page max). The description's mention of pagination and ordering is tool-level, not parameter-level.

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 identifies the tool as providing an upcoming anime airing schedule with specific return fields (episode number, air time, countdown, normalized title) and ordering (soonest first). It distinguishes itself from sibling anime tools like anime_search or anime_rankings by focusing on the schedule aspect.

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 mentions it is credential-free, implying easy access, but does not provide explicit guidance on when to use this tool versus alternatives like anime_search for finding specific anime or anime_rankings for popularity. There is no mention of when not to use it.

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 must fully cover behavioral traits. It states the tool returns a normalized character profile (read operation) and that it's credential-free public data, indicating no authentication or destructive actions. This is sufficient for a simple lookup 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?

The description is two sentences with no wasted words. The first sentence states the purpose and output fields, the second adds credential information. Every sentence adds value.

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 a single parameter, no output schema, and a clear list of return fields, the description is fairly complete. It lacks details on error handling or rate limits, but for a simple get-by-ID tool, it adequately informs the agent.

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 input schema has one parameter 'id' with description 'AniList character id' and 100% schema coverage. The description adds that it's an AniList ID and that the tool gets a character, but does not provide additional format details or constraints 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 'Get an anime/manga character' and lists the specific fields returned (names, image, description, etc.). It distinguishes itself from sibling tools like 'anime_character_search' which is for searching, while this tool retrieves a specific character by ID.

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 specifies the required input ('by AniList id') and notes that it's credential-free public data. It implies usage when you have an AniList ID, but does not explicitly mention when not to use it or suggest alternatives like search for query-by-name.

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 discloses pagination, returned fields (name, native name, image, favourites), and credential-free access. It doesn't mention rate limits or other constraints, but the provided information is sufficient.

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: the first states the core purpose, the second adds details on results and pagination. No wasted words, well-structured.

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 no output schema, the description explains the return format (summaries with specific fields) and pagination. The tool is simple and the description covers all necessary context for an agent to use 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?

All three parameters (page, query, per_page) are already described in the input schema with 100% coverage. The description adds 'paginated' and 'by name' but does not provide additional parameter-level meaning 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 searches anime & manga characters by name, returning paginated summaries. It distinguishes from siblings like anime_search (which searches titles) and anime_character (likely single character details).

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 implies use for character name searches but does not explicitly state when not to use or provide alternatives. No guidance on excluding other search scenarios.

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. It states the tool is read-only and publicly accessible, but lacks details on pagination behavior, rate limits, or output format. This is adequate but not thorough.

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 extremely concise (two sentences), front-loading the action ('Rank anime') and including essential context. Every sentence adds value without redundancy.

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 simplicity and no output schema, the description covers key aspects: purpose, data source, and filterability. It could mention pagination or default sort order, but overall it is sufficiently complete for a ranking 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 input schema has 100% description coverage, so the schema already documents all parameters. The description only reiterates filter categories without adding new meaning, meeting the baseline for a well-documented 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 verb 'Rank' and the resource 'anime', specifying it returns a filterable, sorted ranking. It distinguishes from siblings like anime_search (general search) and manga_rankings (manga-specific) by focusing on anime rankings.

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 mentions it is 'credential-free public AniList data', indicating no authentication needed. It lists filter options (season, year, format, genre, status) but does not explicitly state when not to use this tool versus alternatives like anime_search.

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, description adds context: 'Credential-free public anime data' discloses no auth needed, and 'Returns normalized entries' hints at structure. Does not cover pagination or rate limits, but adequate for a read-only search.

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 action ('Search anime'), then details. No redundant words. Well-structured and efficient.

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 4 parameters, no output schema, and no annotations, the description explains the return format (titles, scores, etc.) and data source. Missing mention of pagination behavior, but overall adequate for a search 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 covers 100% of parameters with descriptions. The description adds no parameter-level info beyond what's in the schema, so baseline 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 clearly states 'Search anime' and 'Searches anime by free-text query', specifying the verb and resource. It distinguishes from sibling tools like anime_character_search or anime_rankings by indicating general anime search with normalized entries.

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?

No guidance on when to use this tool vs alternatives. Does not mention when not to use or provide exclusions. Siblings are listed but not addressed in description.

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 description notes the tool uses public AniList data and optionally scrapes MAL without credentials, but lacks details on rate limits, error handling, or data freshness.

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 cover the main purpose and extra parameter behavior, though the list of fields could be more structured.

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-item retrieval, the description lists all returned fields, but could mention error scenarios or data format details.

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 description adds value beyond the schema for the 'mal' parameter (adds one fetch, omitted if no MAL id).

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 'Get an anime' and lists all returned fields, distinguishing it from sibling tools like anime_title_characters or anime_title_recommendations.

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 implies usage when you have an AniList id and want detailed info, but does not explicitly mention when to use this tool vs alternatives like anime_search or anime_rankings.

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 discloses the output fields and pagination behavior, which is basic. It does not mention rate limits, authentication needs, or any side effects. However, for a simple read-only API, this is adequate.

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 long, front-loaded with purpose and core output. Every sentence adds value: the first specifies action and result, the second clarifies it's public and free. No redundancy or fluff.

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 simplicity (3 parameters, no output schema, no nested objects), the description is complete. It states the return type (cast with specific fields) and pagination. There is no missing information for an agent to use this tool effectively.

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 input schema has 100% description coverage for its three parameters. The description adds no additional meaning beyond what the schema already provides (id, page, per_page defaults and limits). Baseline score of 3 applies as the schema does the heavy lifting.

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 lists an anime's characters with specific output fields (character name, native name, billed role, image, favourites) and pagination. It distinguishes from sibling tools like anime_character (single character) or anime_character_search (search across characters) by making 'anime's characters' the focus.

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 implicitly tells when to use it (when you need characters for a specific anime) but does not explicitly mention when not to use it or recommend alternatives like anime_character or anime_character_search. The 'Credential-free public AniList data' line hints that no auth is required but stops short of full 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 bears full responsibility for behavioral disclosure. It states the tool is read-only ('List'), returns paginated results with ratings and media entries, and is 'credential-free public AniList data', which communicates that no authentication is needed. However, it does not mention error handling, rate limits, or default sorting, but these are minor omissions for a simple read 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?

The description is two concise sentences. The first sentence states the core purpose, and the second adds key details (returns, rating, media entry, pagination, credential-free). Every sentence adds value; no fluff.

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 3 parameters, no output schema, and no nested objects, the description sufficiently covers the tool's behavior: it lists recommendations with ratings and media entries, is paginated, and uses public data. It omits some details like error responses or output format, but for a straightforward list tool, it is reasonably 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?

The input schema covers all 3 parameters with descriptions (100% coverage). The tool description does not add meaning beyond the schema; it simply restates that the 'id' is the anime ID. For high schema coverage, baseline is 3, and no extra value is provided.

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 lists anime recommendations, specifying the verb 'list' and the resource 'anime's recommendations'. It differentiates from sibling tools like anime_title, anime_title_characters, and anime_title_staff by focusing solely on recommendations, and includes details about returned data (rating, normalized media entry, pagination).

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 provides no guidance on when to use this tool versus alternatives. It does not mention when not to use it, nor does it compare it to other anime tools like anime_search or anime_title. The phrase 'Credential-free public AniList data' implies it's a public API, but this is not a clear usage guideline.

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?

Discloses that data is 'credential-free public AniList data' and paginated, indicating read-only behavior. However, no annotations are provided, so the description partially compensates but lacks details on rate limits or error 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 concise sentences, front-loaded with the action and resource, followed by details. No redundant 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 no output schema, the description adequately explains response contents (name, role, occupations, image) and pagination. Lacks total count info but sufficient for a simple listing 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%; the description adds no extra meaning beyond the schema's parameter descriptions. It implies pagination control via page and per_page but does not enrich semantics.

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 verb 'List' and resource 'anime's staff', and specifies return fields (name, production role, occupations, image). It implicitly distinguishes from siblings like anime_character, but does not explicitly differentiate from anime_character_search.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not mention when to choose this over anime_character or anime_title_characters.

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 discloses return fields (narrator, duration, audio preview) and the conditional cross-link to the ebook edition. It also notes 'from Apple Books' public catalog page' and 'normalized', implying read-only behavior. It lacks error-condition details but adds meaningful 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 two sentences, front-loaded with the main verb, and each sentence adds value. No filler or redundancy.

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?

Without an output schema, the description adequately itemizes expected return data and the conditional cross-link. It could mention how to obtain the ID or link to search, but for an ID-based detail tool it is sufficiently 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%, so the parameters id, lang, and country are already fully documented. The description adds no parameter-specific semantics, leaving it at the baseline of 3.

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?

Description uses specific verb 'Retrieve' and resource 'Apple Books audiobook details', clearly distinguishing from siblings like apple_books_audiobook_search or apple_books_book. The mention of 'normalized audiobook metadata' adds further specificity.

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 clearly implies use when audiobook metadata is needed, but does not explicitly name alternatives or state when not to use. This is a clear context without exclusions, appropriate for a simple retrieval tool.

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. It usefully discloses the pagination mechanism (catalog page for first page, Apple review API for deeper pages, up to 20 per page), but does not describe the return shape, error behavior, or any rate-limiting considerations.

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, front-loaded with the primary action, and every sentence adds value. There is no redundancy 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?

The tool is a focused reviews retrieval endpoint with a well-documented schema. The description covers the core behavior and pagination nuances; what's missing (return fields, sorting) is not explicitly required given the simplicity and existing schema coverage.

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 by explaining that page >1 or larger limits route through Apple's review API and that the max is 20 per page, which helps the agent understand parameter interactions.

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 uses a specific verb ('Retrieve') and clear resource ('Apple Books audiobook customer reviews'), stating it returns a page of reviews. It distinctly focuses on audiobook reviews, separating it from related siblings like apple_books_book_reviews or apple_books_audiobook_search.

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?

Clear context is provided: this tool is for retrieving audiobook reviews, with pagination details explaining how pages beyond the first are fetched. However, it does not explicitly mention when to prefer this over alternatives like apple_books_audiobook_similar or apple_books_book_reviews.

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 must carry the behavioral transparency burden. It adds that results are 'normalized' and sourced from a public API, implying read-only behavior, but it does not disclose response structure, pagination defaults, or potential errors, leaving significant ambiguity.

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 core action, and every word contributes (search action, scope, and data source).

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?

The tool has no output schema and no annotations, yet the description only promises 'normalized Apple Books audiobooks' without specifying the return format, pagination behavior, or result fields. For a search tool with five parameters, this is a moderate 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?

The input schema has 100% parameter description coverage, so the baseline is 3. The description adds no parameter-specific details beyond repeating the search concept, so it does not elevate 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 uses a specific verb and resource ("Search Apple Books audiobooks") and adds context about returning normalized data from Apple's public iTunes Search API, which distinguishes it from generic apple_books_search and other apple_books 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?

It clearly states the tool is for searching audiobooks, which tells when to use it, but it doesn't explicitly mention alternatives or exclusions (e.g., use apple_books_search for books in general).

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. It discloses that the tool reads from Apple Books' public catalog page (implying no auth), returns series metadata and the full ordered list of audiobooks, and highlights the domain distinction. It does not cover pagination or error behavior, but for a read-only retrieval this is adequate.

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 three sentences, front-loaded with the primary action. The first and second sentences overlap slightly (both mention retrieving the series and its list), but the third sentence adds a valuable distinction. Efficient overall, with minimal fluff.

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 absence of an output schema and annotations, the description adequately explains what the tool does, where the data comes from, and how this resource differs from a book-series. It lacks return-format specifics, but for a straightforward retrieval tool the essentials are covered.

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% — all params (id, lang, country) already have descriptive definitions. The description does not add param-specific meaning beyond what the schema provides, so the baseline score 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 uses a specific verb+resource ('Retrieve an Apple Books audiobook series and its full audiobook list') and clearly states the output (series metadata and ordered audiobook list). It also distinguishes from the sibling apple_books_series tool by explicitly noting that an audiobook-series is distinct from a book-series, even for the same conceptual series.

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 implies when to use this tool versus alternatives by clarifying that an audiobook-series is a distinct catalog resource from a book-series. This helps an agent choose between apple_books_audiobook_series and apple_books_series, though it does not explicitly name the alternative or provide exclusions.

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 burden. It uses read-only language ('Retrieve', 'Returns') and specifies the data source (Apple Books catalog page), clearly indicating a non-destructive operation. It does not mention edge cases like empty results or pagination, but overall it communicates the core 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 consists of two concise sentences, front-loaded with the main action. Every word serves a purpose, with no fluff 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?

For a simple retrieval tool with three well-documented parameters and no output schema, the description adequately states purpose and return concept. It could clarify that the result is a list, but 'related audiobooks' implies a collection. Overall, it is complete enough for this tool's complexity.

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 input schema already provides 100% coverage with clear descriptions for id, lang, and country. The description adds no parameter-specific details beyond the schema, so it meets the baseline but does not exceed it.

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 retrieves 'Customers Also Bought' audiobooks, with the verb 'Retrieve' and specific resource. It distinguishes from sibling tools like apple_books_audiobook_search (search) and apple_books_book_similar (books) by focusing on related audiobooks.

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 description and name: use this to get related audiobooks for a given audiobook. However, it does not explicitly mention when to avoid it or how it compares to related tools like apple_books_audiobook or apple_books_audiobook_series.

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 of behavioral disclosure. It states that data is pulled from Apple Books' public catalog page, suggesting a read-only operation with no special access. It also reveals what is returned (author metadata, full ebook/audiobook bibliography) and includes a caveat ('where available') about audiobook inclusion, which adds context beyond the tool name.

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, efficient sentence that front-loads the primary action ('Retrieve an Apple Books author's bibliography') before elaborating on return contents. Every word earns its place, with no redundancy or filler. This is a model of concise, structured tool description.

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 simplicity, no output schema, and no annotations, the description adequately covers what the tool does and what it returns. It gives enough detail for an agent to select it for author bibliography needs. However, it could be more explicit about the exact structure or fields in the returned bibliography (e.g., titles, formats, metadata), but the high-level overview is sufficient for basic selection.

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 input schema provides full descriptions for all three parameters: id (Apple Books numeric author ID), lang (result language tag), and country (two-letter storefront country code). Since schema coverage is 100%, the description does not need to add parameter details, and it does not. The baseline of 3 is appropriate because the schema does the heavy lifting, but the description adds no extra semantic nuance.

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's function: 'Retrieve an Apple Books author's bibliography.' It specifies the resource (author) and the action (retrieve bibliography), and further details that it returns author metadata and full ebook/audiobook bibliography. This distinguishes it from sibling tools like apple_books_book or apple_books_search, which focus on individual books or search results, not author-centric bibliographies.

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 implies usage when you need an author's bibliography from Apple Books, but it provides no explicit guidance on when to use this tool over alternatives such as goodreads_author_books or apple_books_search. No exclusions or alternative tool references are given, so the usage context is implied rather than explicitly stated.

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 burden of disclosing behavior. It adds value by specifying the source ('public catalog page') and the normalized fields returned (ISBN, page count, publisher, audience, rating histogram, series linkage). However, it does not explicitly state that this is a read-only operation, nor does it mention rate limits, authentication, or error behavior, leaving some gaps 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?

The description is highly concise: two sentences that front-load the action and resource, followed by a list of key metadata fields. Every word contributes to understanding, with no redundant or filler content.

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 retrieval tool, the description is complete: it states the purpose, the source, and the kind of data returned. The schema documents the parameters, and the description enumerates key output fields even in the absence of an output schema. It does not detail response structure or how to obtain the ID, but that is not essential for basic use.

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 input schema covers all three parameters (id, lang, country) with descriptions, achieving 100% coverage. The tool description does not add any additional meaning to these parameters beyond what the schema already provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves Apple Books book details, using the specific verb 'Retrieve' and resource 'Apple Books book details'. It distinguishes from sibling tools like apple_books_audiobook, apple_books_book_reviews, and apple_books_book_similar by focusing on the book's metadata, making the purpose unambiguous.

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 implies the tool is for retrieving book metadata from a public catalog page, which provides context for when to use it. However, it does not explicitly mention when not to use it or name alternatives (e.g., 'for reviews, use apple_books_book_reviews'), so guidance is implied rather than explicit.

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 burden of behavioral disclosure. It transparently explains the data source (catalog page vs API) and the pagination limit, which are key behavioral traits. However, it does not disclose error conditions, rate limits, or the exact structure of returned reviews, leaving some 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 two sentences with no waste. It front-loads the purpose in the first sentence and provides critical pagination details in the second. The structure is efficient and easy to parse.

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?

The description adequately covers pagination behavior and data sources for a moderately complex tool, but it omits information about the content of the reviews (e.g., rating, text, author, date). Since there is no output schema, describing the return structure would improve completeness. Still, the core functionality is well-covered.

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 already documents all five parameters (100% coverage), but the description adds value by clarifying the interplay between 'page' and 'limit' and the two different data sources. This contextual information goes beyond the schema's individual field descriptions, helping the agent understand how to paginate effectively.

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: 'Retrieve Apple Books customer reviews.' It clearly states the tool returns a page of a book's customer reviews, distinguishing it from sibling tools like audiobook reviews or book details. The purpose is unambiguous and precisely scoped.

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 provides useful usage context about pagination (first page vs deeper pages, limit up to 20), but it does not explicitly mention when to use this tool versus alternatives like apple_books_audiobook_reviews or goodreads_book_reviews. The use case is implied rather than explicitly contrasted, so guidance is partial.

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 present, so the description carries the full burden. It discloses that the tool returns related books from the Apple Books catalog page, which is useful, but it omits behavioral details such as pagination, result limits, ordering, or how lang and country affect results. This is acceptable for a simple read-only lookup 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?

The description is two concise sentences with the key verb and resource front-loaded. There is no filler or redundancy, and each sentence contributes either the primary purpose or the source context.

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 retrieval tool with full schema coverage, the description adequately conveys what is returned and from where. It lacks explicit mention of the output shape or list behavior, and since no output schema exists to offload that, this is a minor but not critical 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?

The input schema already provides descriptions for all three parameters (100% coverage), including the numeric book ID, language tag, and two-letter storefront country code. The description adds no parameter-specific meaning beyond the schema, so it meets but does not exceed 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?

The description uses a specific verb, 'Retrieve,' and identifies the resource as 'Customers Also Bought' books from the Apple Books catalog page. This clearly distinguishes it from sibling tools like apple_books_book (detail lookup), apple_books_book_reviews, and apple_books_audiobook_similar.

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 implies the usage context through the 'Customers Also Bought' phrasing, but it does not explicitly state when to choose this tool over alternatives or when not to use it. There are no exclusion or alternative mentions, though a user can reasonably infer this is for finding related books from a specific book ID.

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 bears the burden of behavioral disclosure. It mentions the data comes from Apple's public marketing-tools RSS JSON feed, hinting at public data, but does not disclose defaults, pagination, rate limits, or response format. Behavior remains largely opaque.

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 three sentences, front-loaded with the action, and not overly verbose. Minor redundancy ('chart rankings' repeated) is acceptable. It is overall concise and structured effectively.

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 lack of annotations and output schema, the description provides insufficient context. It does not explain default behavior when no parameters are provided, expected result structure, or any limitations. The moderate complexity of four optional parameters warrants more contextual details.

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 all four parameters (genre, limit, country, collection). The description adds no additional parameter semantics beyond what the schema provides, aligning with the baseline of 3.

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 retrieves Apple Books chart rankings, with specific supported collections (`top-free` and `top-paid`). This distinguishes it from other Apple Books tools like `apple_books_book` or `apple_books_search`, making the purpose unambiguous.

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 implies the tool is for chart rankings but does not explicitly say when to use it versus alternatives. There are no named alternatives or when-not-to-use conditions, though the supported collections provide some parameter-level 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?

With no annotations, the description carries the full behavioral disclosure burden. It adds useful context by stating results come from 'Apple's public iTunes Search API' and are 'normalized,' implying a public, read-only source. However, it fails to disclose pagination behavior, rate limits, or the concrete shape of normalized output, which are material for a search 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?

The description is two tight sentences with the primary action front-loaded ('Search Apple Books titles'). Every word earns its place—'public iTunes Search API' and 'normalized' add informational value without redundancy.

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 5-parameter tool with no annotations and no output schema, this description is only high-level. It gestures at return values via 'normalized Apple Books ebooks' but omits pagination semantics for page/limit and the filtering effect of lang/country, leaving noticeable gaps for an agent invoking this 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 description coverage is 100%, so the baseline is 3. The description marginally links 'Search Apple Books titles' to the term parameter, but it does not explain how lang, country, page, or limit interact or add meaning beyond their existing schema descriptions.

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 uses a specific verb ('Search') with a clear resource ('Apple Books titles') and adds scope by specifying 'normalized Apple Books ebooks,' which subtly distinguishes it from the sibling apple_books_audiobook_search. However, it does not explicitly name or contrast sibling alternatives, such as apple_books_book or apple_books_author.

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 provides no guidance on when to use this tool versus its alternatives. It does not mention apple_books_audiobook_search for audiobooks, apple_books_book for specific titles, or any exclusions. Usage is only implied by the generic 'Search' phrase, with no context about when this search is preferred.

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 must carry behavioral disclosure. It states the data source is Apple Books' public catalog page, implying read-only public access, and specifies that it returns metadata and the full ordered list. However, it does not explicitly state that the operation is read-only, has no side effects, or requires no authentication, nor does it mention potential pagination or rate limits. The 'full ordered list' detail adds useful behavior, but gaps remain.

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 only two sentences, front-loaded with the action and resource, and includes essential return information. Every word earns its place; there is no redundancy 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?

For a straightforward retrieval tool with a fully documented schema, the description adequately covers purpose, return type, and data source. It does not explain how optional parameters like lang and country affect results, but the schema already does so. The lack of an output schema is mitigated by the clear statement that series metadata and the full ordered book list are returned.

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 input schema provides 100% parameter coverage: id is described as an Apple Books numeric series ID, lang as a result language tag, and country as a two-letter storefront country code. The description adds no additional meaning beyond restating the purpose, so the baseline of 3 for full schema coverage 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 the tool's action ('Retrieve') and resource ('an Apple Books series and its full book list'), making it distinct from siblings like apple_books_audiobook_series by specifying 'book list' rather than audiobooks. It also notes the return of series metadata and the ordered list, which removes ambiguity.

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 implies when to use this tool (when series data and book lists are needed) and provides context via 'from Apple Books' public catalog page', but it offers no explicit guidance on alternatives or exclusions. It does not mention sibling tools like apple_books_book or apple_books_audiobook_series, leaving the agent to infer usage from purpose alone.

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 some burden. It discloses that the data is 'Parsed from jobs.apple.com's server-rendered job detail page' and shows example ID formats, which is useful behavioral context. However, it does not mention error handling, rate limits, or what happens for invalid IDs.

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?