kalicart-global

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the agent knows this is a safe, read-only operation. The description adds context about the return payload (price, availability, attributes, variants, direct storefront URL) but does not disclose edge-case behavior (e.g., not-found errors, federation latency). This is acceptable given the annotation 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 two sentences, front-loaded with the primary purpose, and every clause earns its place. It avoids unnecessary details and is immediately 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?

For a simple one-parameter, read-only tool with no output schema, the description covers the essential context: what the tool returns, what the ID is, and where to obtain it. It lacks explicit error-handling details, but annotations and the simple contract make this sufficient.

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%: the single parameter p2209_id has a description and example. The tool description adds value by explaining that this ID comes from global_search and is the lookup key, which the schema alone does not explicitly state. This enriches the parameter's 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 action ('Retrieve full product detail') and the specific resource ('KaliCart Global federated index by p2209_id'). It distinguishes itself from sibling tools like global_search (which provides IDs but not full details) and lookup_merchant (which targets merchants rather than 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 provides a clear usage context: 'Obtain p2209_id from global_search results.' This implies a workflow (search first, then fetch details) and differentiates from the search tool. However, it does not explicitly list when not to use this tool or mention alternative tools for product-related queries.

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 indicate read-only, idempotent, and open-world behavior. The description adds context by noting that the index includes only merchants who opted in via ARC, and that returned data is merchant-authoritative. It does not contradict annotations and provides useful behavioral 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 concise and front-loaded, stating the core purpose in the first sentence. It uses 2-3 sentences total, includes a spec link, and avoids 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?

Despite having no output schema, the description lists key returned fields (prices, availability, storefront URLs, category leaves) and explains the overall context. The spec link serves as a fallback. It covers the essential information for a complex federated search tool, though a full output schema would be beneficial.

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 9 parameters with rich descriptions (100% coverage), so the schema does the heavy lifting. The description's mention of q and leaf is redundant and does not add additional meaning beyond what the schema already provides. No param-specific nuance is added.

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 a specific action: 'Search the KaliCart Global federated index' and explains what it returns (offers, prices, availability, storefront URLs, categories). It distinguishes itself from sibling tools like get_product and list_categories by its global, cross-merchant scope.

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 usage instructions for parameters ('Provide q and/or leaf') but does not explicitly state when to use this tool versus alternatives such as get_product or list_merchants. The federated context implies broad search usage, but no exclusions or alternative tool recommendations are 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?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds behavioral details beyond annotations: it specifies that the tool returns canonical category leaves, includes product counts, and is intended for discovery. No contradictions with 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?

The description is two sentences long and front-loaded with the action and resource. The first sentence states what it does; the second provides usage guidance. No wasted words or repetition of schema details.

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

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

For a simple list tool with one optional parameter and good annotations, the description is largely complete. It explains the tool's purpose, output highlights (product counts), and usage context. It lacks explicit mention of return format or behavior when 'parent' is omitted, but these are minor gaps given the schema and tool simplicity.

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% for the sole parameter 'parent', which is described in the schema. The description does not add parameter-specific semantics beyond the schema. Baseline of 3 is appropriate since the schema carries the burden.

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

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

The description clearly states a specific verb and resource: 'List canonical product category leaves used by KaliCart Global with product counts.' It distinguishes itself from sibling tools like get_product, global_search, and list_merchants by focusing on category discovery. The mention of 'leaves' and 'KaliCart Global' adds precise scope.

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 explicit usage context: 'Use to discover available categories before filtering global_search with the leaf parameter.' This gives a clear when-to-use scenario. However, it does not explicitly mention alternatives or when not to use it, though the phrase 'before filtering global_search' implies a specific workflow.

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, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds value by specifying return fields and the federated catalog scope, but doesn't disclose potential rate limits, ordering details (only in schema), or any other behavioral traits beyond what annotations provide.

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, front-loaded sentences with no wasted words. The first sentence states the action and scope, the second gives return fields and a usage hint. Excellent structure.

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 list tool with one well-documented parameter, the description provides essential context: what is listed, what is returned, and when to use it. Since there is no output schema, the explicit mention of return fields adds completeness. It doesn't need to explain more.

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% for the single parameter 'limit', which already documents default, max, ordering, and lack of pagination. The tool description does not add new parameter semantics, 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 the tool's verb ('List') and resource ('WooCommerce merchants participating in the KaliCart Global federated catalog'), and specifies the return fields (domain, storefront URL, product count). While it doesn't explicitly contrast with siblings like lookup_merchant, the usage hint ('Use before global_search') implies a distinct role in discoverability.

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

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

Provides explicit guidance: 'Use before global_search to understand catalog coverage.' This indicates when to invoke it relative to another tool. No exclusions or alternative recommendations are given, but for a simple listing tool this is sufficient 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?

The description discloses that a miss schedules a background probe, a behavioral side effect beyond the readOnlyHint and openWorldHint annotations. It also describes return contents, providing meaningful context without contradicting 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 concise sentences front-load the core action and return value, then add usage context and sibling differentiation. Every sentence 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?

For a simple lookup tool with one well-documented parameter, the description fully covers purpose, returns, side effects, and usage context. No output schema exists, but the description enumerates what is returned, making it 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% for the single parameter 'domain', with a clear example. The description adds no extra parameter semantics beyond the schema, but this is not needed given the schema's completeness, 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 the tool's primary action ('Check whether a merchant domain runs an ARC-compliant catalog'), specifies the return values (bridge_version, discovery URL, consent flags), and explicitly contrasts with global_search, distinguishing it from 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?

Provides explicit usage criteria ('when you already know a merchant domain') and names the alternative tool for product discovery ('use global_search'), giving clear when-to-use and when-not-to-use guidance.

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