Svijet Beba — katalog dječje opreme

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered structurally. The description adds the id-provenance rule and names the fields returned, but since an output schema exists that content is largely restated rather than new behavioral context. No contradiction 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?

Two dense, front-loaded sentences: purpose first, then return contents, then the connector note. Nothing looped or padded, though the enumeration of return fields partially duplicates the output schema and the trailing connector sentence is the weakest link.

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 an output schema covering return values, full annotation coverage, and a single required parameter, the description only has to establish purpose and id provenance, which it does. The residual gap is the missing disambiguation against the very similar 'get_product_details' sibling, which is a real but modest omission for a one-parameter lookup.

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 is a single parameter with 100% schema description coverage; the schema already documents it as a numeric product id from the search tool, including a regex pattern the description omits. The description's 'id returned by the search tool' phrasing mirrors the schema rather than extending it, 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?

The description states a specific verb and resource ('Fetch full details for a single Svijet Beba product by its id') and even enumerates the returned content, so the agent knows exactly what it does. It does not, however, differentiate itself from the sibling 'get_product_details', which reads as a near-equivalent, leaving ambiguity about which one to pick.

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 supplies one real usage constraint — the id must come from the 'search' tool — which is helpful routing information. But it never says when to prefer this over 'get_product_details' or 'search_products', and the only differentiator offered ('generic entry point for ChatGPT/OpenAI connectors') is audience framing rather than a use condition.

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description's only added behavioral content is that each brand is returned with a product count; it says nothing about ordering, completeness, or caching. Against a rich annotation set, that is a modest but real contribution.

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?

A single front-loaded sentence with no filler. The parenthetical examples of brand names are the one embellishment and they earn their place by confirming the expected taxonomy.

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 an output schema present, no parameters, and annotations covering the safety profile, the definition is nearly complete for a trivial list endpoint. The remaining shortfall is that it gives no hint about ordering or result volume, and it is written in Croatian while the surrounding tool ecosystem (sibling names) is English.

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

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

The tool takes zero parameters, so the baseline is 4 and there is nothing for the description to compensate for. The schema explicitly sets additionalProperties=false, so no hidden input 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 states a specific verb+resource: it returns all brands, and it even lists example values (Bugaboo, Cybex, Maxi-Cosi) plus the fact that each entry carries a product count. That is clear enough that an agent knows what comes back, though it never contrasts itself with nearby siblings like get_categories or get_sizes, which also enumerate taxonomy values.

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 when-to-use or when-not-to-use guidance, and no alternative is named. The agent must infer that this is the lookup for brand identifiers before calling search_products, which is the obvious downstream use but is never 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds the meaningful extra that each entry carries a product count, but says nothing about ordering, caching, or filtering.

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?

A single front-loaded sentence with no filler, appropriate for a zero-argument lister. It is efficient, though it is also short enough that it could have afforded one routing clause.

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 parameters, an output schema present, and rich read-only annotations, the description only needs to convey scope and it does. The one gap is that it never positions itself relative to the many sibling lookup tools.

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

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. The description correctly implies the call is unconditional.

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 names a specific resource (categories) and states the payload includes a count of available products, so the agent knows exactly what this returns. It does not, however, distinguish itself from sibling listers such as get_brands or get_sizes beyond the resource noun.

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 statement of when to call this versus get_brands, get_sizes, get_specs, or the search tools. Usage is only inferable from the resource name, and no prerequisites or exclusions 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, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds one genuinely useful behavioral fact not in the annotations – results are ordered by discount size – but says nothing about result limits (the schema's hard cap of 50), pagination, or what happens on an unknown category.

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?

A single short, front-loaded sentence with no filler; the core scope and ordering are delivered immediately. Its brevity is also its weakness, but as a structure/concision measure it is efficient rather than rambling.

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?

An output schema exists, so return-value shape needn't be explained, and the tool is simple (2 optional params). Still, the description omits routing guidance versus similar siblings and gives no hint about the result cap or filtering behavior, leaving real gaps for an agent choosing among ten sibling tools.

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 only 50%: 'category' is documented as an optional SEO slug, but 'max_results' has no description and no default. The tool description adds nothing about either parameter, so it fails to compensate for the undocumented half.

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 resource ('Proizvodi na akciji' – products on sale) plus a defining behavior (sorted by discount amount), which is far more than a restatement of 'get_deals'. It does not, however, distinguish itself from the closest sibling, search_products, which an agent might reasonably pick for the same intent.

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 when-to-use, when-not-to-use, or alternative guidance. With sibling tools like search, search_products, and fetch available, the agent gets no signal about why it should choose get_deals over a general product 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered by structured data. The description adds no behavioral context beyond that — no not-found/error behavior, no note on which identifier takes precedence when both are supplied, and no hint about result 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?

A single front-loaded sentence with the lookup keys stated immediately; there is no filler and nothing extraneous to remove.

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?

An output schema exists so return values need not be described, and annotations carry the safety profile. However, for a lookup tool with an anyOf/optional-parameter design, the description omits practical details such as fallback behavior when one key is absent — it is adequate but thin.

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 50% (gtin documented as 'EAN ili interni kod', id undocumented). The description clarifies that either key may be used and expands gtin to EAN/GTIN, which is slightly more than the schema's annotation, so it lands at the baseline for partial 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 names a specific verb-and-resource pair (fetch details of a single product) and states the two accepted lookup keys, ID or EAN/GTIN. It is clearly distinguishable from the plural sibling search_products, though it never names that sibling explicitly.

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 only implied: 'one product by ID or EAN/GTIN' suggests a direct-identifier lookup rather than a search, but there is no explicit statement of when to use this over search_products or fetch, and no prerequisites or exclusions 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, idempotentHint, destructiveHint=false and closed-world scope, so the safety profile is covered. The description adds only content scope and says nothing about pagination behavior despite the max_items cap, so it meets but does not exceed the lower bar set by 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 compact sentences with the core action front-loaded and the content enumeration second. No wasted wording, though it is fairly terse given the tool's ecosystem.

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?

An output schema exists, so return-value description is unnecessary, and both parameters are fully documented in the schema. The remaining gap is routing context against sibling FAQ/spec/product tools, which keeps it just short of 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 description coverage is 100%, so both parameters (product id and max_items with default 20/max 50) are already fully documented in the schema. The description adds no parameter meaning beyond that, which is the correct 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?

States a specific verb and resource ('Dohvati pitanja i odgovore za proizvod') and clarifies the content type as FAQ with expert answers on age, safety, compatibility and setup. An agent can distinguish it from get_specs or get_product_details by content scope, though no sibling is named explicitly.

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 only implied: the content categories (age, safety, compatibility, setup) suggest when this FAQ retrieval is relevant, but there is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives like get_specs or get_product_details.

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

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds useful scope context by naming the categories of information returned (delivery, contact, location, payment), which is behavior beyond the annotations, though it says nothing about caching, freshness or authorization 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?

A single short sentence with the resource front-loaded and the content categories in a compact parenthetical. No filler, 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?

An output schema exists, so the description need not describe return values, and the zero-parameter signature needs no parameter documentation. What remains is the scope of the tool's content, which the parenthetical covers well; only the absence of any sibling routing guidance keeps it from being fully 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 tool takes zero parameters and the schema is explicitly empty, so there is nothing for the description to disambiguate. The baseline of 4 for a no-parameter tool 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 states the resource (webshop info) and enumerates the content it covers — delivery, contact, location, payment — which is more specific than the bare tool name. It does not, however, reference any sibling tool or explain how it differs from the product-oriented tools (get_product_details, search_products), leaving differentiation to the name alone.

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 only implied: an agent can infer this is the tool for shop-level metadata such as shipping or payment terms, but there is no explicit when-to-use statement, no prerequisites, and no mention of alternatives. With ten siblings present, that omission is a real but modest gap.

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 readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is fully covered. The description adds genuine semantic context by defining available/available_sizes as orderability and in_stock/in_stock_sizes as the 'Y' stock flag, but it says nothing about behavior for an invalid ID, empty variant sets, or caching.

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?

It is a single compact sentence that front-loads the action and then defines the key field semantics with no filler. The density and unglossed field names (available_sizes, in_stock_sizes) make it slightly cryptic, but nothing is wasted.

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

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

An output schema exists, so return structure need not be explained, and annotations cover safety. What remains missing is enough context for a shop API agent: that this returns size/variant options for one product and how that differs from get_product_details. For a one-parameter read tool this is minimally adequate.

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 the single 'id' parameter documented as 'Picture ID proizvoda', so the schema carries the parameter burden. The description adds no further syntax, range, or example for the ID, which is acceptable at full coverage but not value-adding.

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 says 'Dohvati varijante' (fetch variants) and explains what the availability fields mean, which is a specific resource. However, it never clarifies that these are product size/variant options tied to the 'Picture ID proizvoda' argument, and it does not distinguish itself from siblings like get_product_details or get_specs that could plausibly also return variant 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?

There is no statement of when to call this versus get_product_details or any other sibling, and no preconditions. The only directive, 'Provjeri availability_text svake varijante' (check each variant's availability_text), tells the agent how to read the result, not when to choose 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, idempotentHint and destructiveHint=false, so safety is covered without the description. The description does add one useful behavioral expectation: that the specification set differs by product category (car seats vs strollers vs toys), which prepares the agent for heterogeneous output. It says nothing about error behavior for invalid IDs or whether missing specs are returned empty.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no padding: the core action first, then the category-dependent caveat. Efficient and front-loaded, though the parenthetical field list is somewhat long for the value it adds.

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 only one required parameter, full schema description coverage, an output schema, and annotations covering the safety profile, nearly everything an agent needs is present. The only shortfall is absent guidance on how this differs from related spec/detail tools.

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 single parameter is documented in the schema, giving a baseline of 3. The schema's own wording ('Picture ID proizvoda') is ambiguous, and the description only indirectly clarifies that the identifier refers to a product by referring to 'proizvoda', so no real meaning is added beyond the schema.

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

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

States a specific verb and resource ('Dohvati tehničke specifikacije proizvoda') and enumerates the returned fields (Brand, Težina djeteta, Dob, Visina, Standard, Dimenzije). However it never distinguishes itself from close siblings like get_product_details or get_sizes, which an agent could easily confuse with it.

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 statement of when to choose this tool over get_product_details, get_sizes, or get_categories. The only context given is that spec content varies by category, which describes output shape rather than tool selection.

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

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

Annotations already declare read-only, idempotent and non-destructive behavior. The description adds useful context beyond annotations by describing the return fields (id, title, url, snippet) and the follow-up workflow to 'fetch'.

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 compact sentences front-loaded with the action and scope. The final connector note is brief and helps routing without padding.

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 two-parameter read tool with an output schema and safety annotations, the description is nearly complete. The main missing element is routing guidance against the sibling 'search_products'.

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

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

Schema description coverage is 100% and documents both parameters, so the baseline is 3. The description adds that the free-text query accepts Croatian or English, a constraint not stated in the schema, though it adds no extra detail for max_results.

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 ('Search') and resource ('Svijet Beba product catalog'), including product types and query languages. It distinguishes itself from 'fetch' by routing full-detail requests there, but never addresses the sibling '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?

Provides clear context by calling itself a generic entry point and tells the agent to pass returned IDs to 'fetch' for details. It lacks explicit when-not conditions or a comparison to the similar sibling 'search_products'.

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, non-destructiveHint and closed-world scope, so the safety profile is covered. The description adds nothing beyond what the schema already lists (the filter facets) — no ranking, pagination, result-cap, or empty-result 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?

A single short sentence with the key facets front-loaded and zero filler. It is efficient, though arguably too terse to carry the routing information the tool needs.

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?

Output schema and annotations are rich, so return values and safety need no explanation. But the schema's anyOf constraint (at least one of query or brand required) is not surfaced in the description, and the sibling overlap with 'search' is unaddressed — meaningful gaps for a 6-parameter 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 each parameter is already documented with type, bounds and Croatian explanations; baseline 3 applies. The description merely restates the facet list and adds no syntax, unit, or interaction detail (e.g. how min/max_price combine).

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 (search) and resource (products) plus the filter dimensions (keyword, brand, price, availability), so the agent knows exactly what the tool returns. However, it never distinguishes itself from the sibling 'search' tool, leaving a real ambiguity about which search entry point to pick.

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 when-to-use guidance, no exclusions, and no mention of the sibling 'search' tool. The agent must infer from the name alone that this is product-scoped while 'search' is generic.

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