Booyah Index

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it's a safe read operation. The description adds useful context about the geographic scope (14 cities) and the provenance of the slug, which goes beyond the annotations without contradicting them.

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 sentence that front-loads the action (Get the full structured record), includes necessary constraints (14 cities, slug source), and contains no extraneous information. It is well-structured and concise.

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

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

For a simple one-parameter getter with no output schema, the description sufficiently covers purpose, scope, and input source. The phrase 'full structured record' gives a sense of the return value, and the annotations cover safety. It lacks explicit error behavior but that is not critical for this simple 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 documents the slug parameter with an example at 100% coverage. The description adds semantic value by calling it a 'Booyah Index slug' and specifying it should come from search_places results, giving the agent guidance on how to obtain 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 clearly states 'Get the full structured record for one place' with a specific verb and resource, and scopes it to 'any of the 14 Southeast Asian cities.' This distinguishes it from sibling tools like get_product and search_places by specifying exactly what it retrieves and the input method.

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 'by its Booyah Index slug (from search_places results),' which implies a workflow of searching first and then retrieving a specific record. It provides clear context on when to use this tool but does not explicitly exclude alternatives or name them, so it lacks explicit when-not guidance.

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

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

The annotations already declare read-only, idempotent, and non-destructive. The description adds valuable clarity by stating 'never creates a checkout or order', which addresses a common misuse and reassures the agent about side effects. This goes beyond the generic annotation.

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 resource, and every sentence adds value. It efficiently communicates the tool's purpose, input scope, output fields, and side-effect safety.

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 an output schema, the description compensates by listing key return fields (price, availability, validity, seller store, URL). It covers the essential context for a simple get tool, though it omits any mention of the language parameter's purpose.

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 id parameter well with examples, and the description adds 'stable' and 'from search_products', providing marginal value. However, the language parameter is left entirely undocumented in both schema and description, leaving ambiguity about its effect on the response.

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 full public record for one product, specifying the resource (product) and the action (get). It also differentiates from sibling tools like search_products (which finds products) and get_place/get_store (which target other resources).

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 explains how to identify a product via a stable id or slug, and explicitly references search_products as the source of slugs, providing clear usage context. It doesn't list exclusions or alternatives, but the context is sufficient 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: it returns a "capped list" and only "published products," and states the store is "verified" — details not available in annotations or schema. This goes beyond the baseline.

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 core action and key parameters. No redundant phrasing; every clause adds useful information (id types, product list cap, usage recommendation).

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

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

There is no output schema, so the description carries the burden of conveying the return shape. It mentions the store and a capped list of published products, which is adequate for a getter tool. It also covers the key distinctions and workflow context. It does not elaborate on default limit or language behavior, but those are available in the schema, so a 4 is appropriate.

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 67% (2 of 3 parameters documented). The description partially reinforces the id parameter by mentioning "stable id or slug" and the limit by saying a "capped list" of products, but it does not clarify the language parameter or add information beyond the schema. It adds slight value but does not fully compensate for the coverage gap.

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: "Get one verified Booyah store by stable id ("store_1") or slug, with a capped list of its published products." It clearly distinguishes from sibling tools by scope (store vs place/product) and by noting it returns published products, which differentiates it from search_products.

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

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

The description explicitly provides usage guidance: "Use after search_products to see everything a seller offers." This gives a clear when-to-use context and implies a workflow, which is sufficient for a getter tool and fulfills the guideline criteria.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context beyond annotations by specifying that it returns every city and its place count, and it explicitly ties to the `city` filter in search_places, which helps the agent understand the scope and purpose.

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, each earning its place. The first states exactly what the tool returns; the second gives a clear usage directive. 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 zero-parameter, read-only list tool with strong annotations, the description is complete: it states the data returned, the scope ('every city'), and the use case relative to search_places. No output schema exists, but the return concept (city + place count) is sufficient for an agent to invoke and interpret the result.

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

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

The tool has zero parameters, so the baseline is 4. The description appropriately references the `city` filter parameter of a sibling tool, adding cross-tool context without inventing parameters that do not exist.

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 'List' and clearly states the resource: every city covered by the Booyah Index with its place count. It also differentiates from siblings like search_places by framing itself as the lookup for city coverage, not a search tool.

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

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

Explicitly says 'Call this first if unsure which city name to pass as the `city` filter in search_places', providing a clear when-to-use instruction and naming the alternative tool. It also explains the benefit: avoids guessing spelling or coverage.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds valuable context by specifying the return format (structured records with known-for, rating, review count, canonical URL) and the geographic scope (14 cities). This goes beyond the annotations, though it does not cover pagination or sorting 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 a single, information-dense paragraph with no fluff. It front-loads the core purpose, then adds city lists, categories, examples, and return format efficiently. Every sentence contributes meaningful details.

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

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

The tool has 4 parameters and no output schema, but the description covers purpose, scope, examples, and return format. It does not mention pagination or sorting, but for a search tool with good annotations, this is a minor gap. Overall, the description is complete enough for an agent to 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?

Schema coverage is 100%, so each parameter has a description. The description adds extra value by enumerating all 14 supported cities (schema only lists 8 examples), giving category examples, and providing query examples that clarify parameter usage. This elevates it above 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 clearly states the tool searches the Booyah Index for Southeast Asian local businesses, listing 14 cities and categories. It uses a specific verb-resource combination ('Search the Booyah Index') and distinguishes from siblings like search_products or get_place by focusing on places/businesses.

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 context on when to use the tool (searching for local businesses/places) and provides example queries to illustrate usage. However, it does not explicitly state when not to use it or name alternatives like search_products, though sibling names imply these distinctions.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description reinforces with 'Read-only discovery' and 'Never creates orders or payments.' It adds valuable behavioral context beyond annotations by listing the exact return fields (titles, prices in minor units, availability, seller store, place context, canonical URL) and the scope of 'verified Booyah stores.'

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: purpose, return details, and safety note. It is front-loaded with the main verb and resource, avoids redundancy, and is highly scannable.

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 10 parameters and no output schema, the description reasonably lists return fields and scopes the search to published products from verified Booyah stores. It does not mention pagination or response list structure, but the limit parameter and return-field list cover the essential context 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 all 10 parameters already have descriptions. The description's mention of 'integer prices in minor units' aligns with the price parameter descriptions but does not add new information beyond the schema. It provides no additional guidance on parameter interactions or formats.

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 published products, vouchers, experiences, memberships and digital goods sold by verified Booyah stores.' It explicitly differentiates from a sibling tool ('distinct from search_places, which finds physical businesses'), making its purpose unmistakable.

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 provides a clear alternative ('distinct from search_places') and a firm exclusion ('Never creates orders or payments'), telling users when to use this tool for discovery and not for transactions. This explicit when/when-not guidance is exemplary.

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