Baqer Store (باقر ستور) — Iraq

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered by structured data. The description adds useful behavior context beyond that: the data is public, scoped to a single product, and includes a prebuilt WhatsApp order link. It does not say what happens with an invalid or expired slug, which is the main remaining 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, front-loaded with the payload summary, then the calling instruction. The field enumeration is long but each item earns its place by telling the agent what is available without an output schema. Minor redundancy between the name, title and opening phrase.

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 does the important work of listing returned fields so the agent can judge whether this call answers a user's question. For a single-parameter read tool with full annotation coverage, it is nearly complete; only error/failure behavior for a bad identifier is unaddressed.

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 single 'product' parameter is already documented as accepting a URL or slug. The description's 'Pass the product URL or slug from search_products' adds the provenance hint (where to get the value) but no new format or constraint detail. Baseline 3 is appropriate when the schema carries the 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 opens with a specific verb and resource ('Full public details of one Baqer Store product') and enumerates exactly which fields come back, so an agent knows what it gets. It implicitly separates itself from search_products by referring to it as the source of the identifier, but never states outright that it is the detail-fetch step rather than a discovery 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?

It gives a concrete prerequisite workflow: pass the URL or slug obtained from search_products, which tells the agent this is a follow-up call after discovery. It stops short of stating when not to use it (e.g. that it cannot search or list), 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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds value the annotations don't: it discloses the store/region scope and that each result carries a product count — important since there is no output schema. It does not mention ordering or whether zero-product brands are included.

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 tightly packed sentences with no filler; the resource and its return content are front-loaded before the tool-chaining hints.

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 usefully hints at the return payload (brands with product counts) and provides the integration path to sibling tools. Only minor gaps remain, such as result ordering and handling of brands with no 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 coverage is 100% and the single parameter already has an example, so the schema does the heavy lifting. The description still adds linkage meaning — that the category value must be a slug sourced from list_categories — which the schema alone does not convey.

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 resource (brands sold at Baqer Store in Iraq) and what comes back (product counts), plus an optional category scope. It is clearly separable from list_categories (which supplies the slug) and search_products (where the brand value is consumed).

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 routes the agent both upstream (category slug comes from list_categories) and downstream (feed the brand into search_products as "brand"). It never explicitly says 'use this to discover valid brand values before searching,' but the cross-references make the intended workflow inferable.

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. The description adds real value beyond that by describing the shape of the payload (fields returned), which compensates for the absence of an output schema, though it says nothing about ordering or size of the result set.

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 tight sentences: the first front-loads what you get, the second routes the agent to the correct follow-up tools. No filler and nothing repeated from the title or annotations.

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-argument, read-only listing tool with no output schema, the description covers the returned fields and cross-tool relationships well. Minor gaps remain around result ordering and whether the category list is flat or hierarchical in structure, but nothing an agent needs in order to call it.

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 no parameter semantics to explain and the baseline is 4. The mention of 'slug' refers to output values consumed by search_products rather than an input here, which is helpful context but not parameter documentation.

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 the resource precisely (all product categories of Baqer Store in Iraq) and enumerates exactly what each entry carries — slug, Arabic name, parent category, in-stock product count, page URL. That level of specificity makes it immediately distinguishable from list_brands and get_product.

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 gives concrete downstream usage — 'Use a slug as "category" in search_products' — and handles a likely confusion case by pointing at search_vip_numbers for VIP mobile numbers. It stops short of stating when to prefer this over list_brands, but the context is clear enough to act on.

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 true and destructiveHint/openWorldHint false, so the safety profile is covered. The description adds genuinely non-obvious behavior: the tool only constructs a message link, no order is placed, and the customer must manually send the message — exactly the misconception an agent would otherwise have.

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 carrying distinct information, with the core purpose and the 'no order created' caveat front-loaded. Slightly dense parenthetical packing of the input modes, 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?

With no output schema, the description carries the burden of explaining the return value and does so: a WhatsApp link plus the page URL for the customer to order on the site. For a 3-parameter, zero-required-parameter tool this is nearly complete; only the role of 'quantity' in the message 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 67%, so the schema already documents product ('URL or slug') and vip_number ('11 digits starting with 07'). The description adds a concrete VIP example (07855557555) and restates the product forms, but 'quantity' is never mentioned in either the schema or the description, leaving its effect on the generated message unexplained.

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 concrete verb and artifact ('Builds a WhatsApp link with a ready order message'), names the recipient (Baqer Store's sales team) and the two input modes (product URL/slug or VIP number). This is clearly distinguishable from read-oriented siblings like get_product and search_products, which fetch data rather than generate a customer-facing link.

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 gives a direct operational instruction ('Give the link to the customer') and pre-empts the most likely misuse by stating 'No order is created: the customer opens the link and sends the message.' It does not explicitly name an alternative tool or state when-not to use it, so it stops short of a full routing rule.

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, non-destructive, closed-world behavior, and the description adds material context beyond that: a hard result cap of 20, in-stock-first ordering, the exact returned fields, and IQD currency. It does not mention pagination offsets (none exist) or rate limits, but nothing important about the behavior is hidden.

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

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

Three tight sentences, each with a distinct job: what to search on, what comes back, and where to go next. Capability and scope are front-loaded and no sentence 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?

For an 8-parameter search tool with no output schema, the description supplies the missing return contract (fields, ordering, cap) and the sibling routing. Everything an agent needs to call it correctly and interpret the result is present.

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

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

With 75% schema description coverage, the schema already documents query, brand, category, in_stock_only, and price bounds. The description adds bilingual query examples and confirms IQD units, but leaves the sort enum and limit semantics unmentioned, so it largely restates structured data. 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?

States a specific verb (search) against a named resource (the live Baqer Store product catalog) and enumerates the searchable dimensions: Arabic/English text, category, brand, and IQD price range. It also distinguishes itself from get_product and search_vip_numbers, so an agent can select it without opening sibling schemas.

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 routes to alternatives: 'Use get_product for full details and order_link to order' and 'For VIP phone numbers use search_vip_numbers.' It gives clear when-to-use context but omits the discovery siblings list_brands and list_categories, which the schema references for valid brand/category values.

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 and closed-world, so the safety profile is covered. The description adds genuine value by disclosing that only available-now numbers come back and that results include price, tier, page URL and payment rules (transfer + delivery fee, down payment). It says nothing about result ordering, pagination or how limit interacts with the result set beyond the schema's max of 20.

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 dense sentence that front-loads the resource and scope before listing filters; the parentheticals earn their place by decoding enums and Arabic terms. It is somewhat run-on and would read faster split into a purpose sentence and a filter sentence.

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 10-parameter optional-filter search with no output schema, the description covers purpose, filter semantics and the shape of returned data (price, tier, URL, payment rules) plus the availability constraint. Only ordering/pagination behavior is left implicit.

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?

With only 50% schema description coverage, the description compensates well: it decodes the pattern enum (triple/quad/penta/hexa = digit repeated 3/4/5/6+ times, mirror = ABBA ending, birth_year = ends with a year), clarifies that tier is Baqer's classification rather than the operator's, and gives examples for ending and prefix. Sort, limit and operator semantics remain unexplained, keeping it below 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?

States a specific verb (search) and resource (special/VIP mobile numbers for sale at Baqer Store, Iraq) and names the two covered operators (Zain, Asiacell), which clearly separates it from search_products and get_product.

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: the filtering dimensions an agent can combine (operator, ending, contains, prefix, pattern, tier, price in IQD) and the constraint that only currently available numbers are returned. It does not explicitly say when to prefer this over the sibling search_products, so it stops short of full alternative routing.

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 establish that this is a safe, read-only, idempotent, non-destructive, closed-world lookup. The description adds useful scope by listing the store-policy domains covered, but it does not disclose freshness, source, or output-shape behavior beyond that scope.

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 identifies the store and then lists the covered policy areas. The list is dense but purposeful, with no obvious filler, though it could be slightly easier to scan if the topics were separated more clearly.

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 informational tool with no output schema, the description gives enough topical coverage for an agent to know what questions it can answer. It does not need to explain arguments or return structure because neither is relevant here.

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 input parameters, so there is no parameter semantics for the description to clarify. The baseline 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 identifies the resource as Baqer Store purchasing information and enumerates the covered topics: delivery, payment, returns, warranty, contact, and VIP-number rules. This is specific enough to distinguish it from product-search and ordering siblings, though it does not explicitly name those 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?

The content strongly implies the tool is for store-policy questions such as delivery fees, payments, returns, and contact details. However, it does not explicitly say when to use this versus search_products, get_product, or order_link, so the routing guidance remains inferred.

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