YallaDeals: UAE price comparison

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so safety is covered. The description adds genuine behavioral context beyond that: the exact breadth of returned data (current price, stock, cheapest shop, 90-day low/high/usual/last change, verdict, specs, alternatives), which is valuable since there is no output 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?

A single dense sentence with the payload list front-loaded and the usage/input guidance trailing. Every clause earns its place, though the enumeration is long enough that it reads more like a feature dump than a crisp summary.

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 must convey return contents, and it does so thoroughly (prices, stock, cheapest shop, 90-day history metrics, verdict, specs, alternatives). An agent knows what it will get and what input forms are valid.

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?

Only one parameter and schema description coverage is 100%, so the schema already documents it fully. The description's 'Accepts the product url or slug... or a product name' restates the schema's 'Product page url, slug, or name' rather than adding format, resolution-order, or ambiguity-handling detail. Baseline 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+resource ('Everything about one product') and enumerates the exact payload: per-shop price/stock, cheapest shop, 90-day history, verdict, specs, alternatives. It is clearly distinguishable from search_products (which feeds it) and from similar_products/price_drops.

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 an explicit when-to-use directive ('Use before recommending a purchase') and names the upstream source of its identifier ('the product url or slug from search_products'). It does not say when to prefer sibling tools like price_drops or similar_products instead, so no exclusion 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?

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false, destructiveHint=false), so the description is free to add return-shape context instead — it discloses that results are grouped, include slugs, and carry product counts. With no output schema present, this prose is the agent's only view of the response, and it delivers the essentials.

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?

One sentence, front-loaded with the resource and followed immediately by the returned fields. No filler, no restatement of the title or name.

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 listing tool with no output schema, the description covers what comes back (grouping, slugs, counts) and why the slugs matter. Only minor items such as ordering or whether the grouping is hierarchical are left unstated, which is acceptable at this 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 tool takes zero parameters, so the baseline is 4. The description does not need to explain inputs, and it adds a useful cross-tool note that the slugs it returns feed the 'category' argument elsewhere.

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 (the catalogue categories YallaDeals covers) and states the returned content: grouped categories, slugs, and per-category product counts. It is clearly distinguishable from siblings like get_product or search_products, though it never explicitly contrasts itself with them.

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 parenthetical '(for the category argument)' hints that this call exists to supply slugs to other tools such as search_products, which is genuinely useful routing information. However, there is no explicit when-to-use / when-not-to-use statement or named alternative, so it stays at the implied-usage level.

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 real behavioral context beyond that: the 30-day lookback window, the pricing-integrity constraint that excludes fake 'was' prices, and the geographic framing (UAE/Dubai). It does not mention result ordering or pagination, but that gap is minor against 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?

Two sentences, both earning their place: the first defines the data semantics, the second gives intent-matching example queries. The defining constraint is front-loaded before the usage examples.

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 discovery tool with no output schema, the description covers what set of products is returned and enough pricing semantics to interpret the result. It leaves the exact return shape and ordering implicit, which is the only remaining 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?

Schema description coverage is 100% with only two optional parameters, so the schema already explains limit (1-25, default 10) and the optional category slug/name. The description contributes no additional meaning to either parameter, and per the baseline rule a 3 is correct when 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?

States a precise resource and an unusually specific filter: products cheaper now than in the last 30 days and priced well against their usual price. The 'no inflated was prices' clause defines the semantic that separates it from a generic search_products listing, so an agent can tell it apart from siblings without opening either 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?

Gives explicit trigger phrases ('what is on sale', 'any deals on headphones', 'best discounts in Dubai today') that map directly to user intent, which is strong positive routing. It stops short of naming when not to use it (e.g., a specific-model lookup should go to get_product/search_products), so it is clear context rather than full when/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?

Beyond the annotations (readOnly, idempotent, non-destructive), it discloses real behavior: cross-site price aggregation, a 'good price' verdict in the result, Arabic/plain-language understanding, and automatic conversion of a natural-language budget into a price filter. It still does not say anything about result count limits, ranking, or what happens when nothing matches.

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 what the tool returns, followed by usage scope; the example queries are compact and directly illustrative rather than filler. Nothing repeats 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?

With no output schema, the description carries the burden of describing the return ('lowest current price across Amazon.ae and noon, with whether that price is a good one') and it does so. All 7 parameters are schema-documented, so the definition is complete enough for an agent to call 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?

Schema coverage is 100%, so the baseline is 3, but the description adds cross-parameter semantics the schema does not: a budget expressed inside 'query' ('under 300', 'between 100 and 200') is translated into the min_price/max_price filters, which tells the agent these can be driven either way. The Arabic/plain-language note reinforces the query parameter's expected form.

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 ('Find products sold in the UAE') plus the two sources it aggregates (Amazon.ae, noon) and the added value it returns ('their lowest current price ... and whether that price is a good one'). That scope clearly separates it from single-item lookup (get_product) or discovery siblings (similar_products, price_drops).

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?

'Use for any shopping question in the UAE' plus four concrete query examples establishes the intended context well. It gives no explicit exclusions or mentions of the sibling tools for narrower tasks (e.g. get_product for a known item), so the when-not-when is inferred rather than 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 one useful behavioral detail — that results include prices — but says nothing about ranking basis, result count behavior, or what happens when no similar products 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?

Two tight sentences with zero filler. The value proposition (similar products + prices) is front-loaded, and the accepted input forms follow immediately.

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-parameter read-only tool with full schema coverage and annotations covering the safety profile, the description is adequate — it even hints at return content (prices), which matters since no output schema exists. It is only slightly short on how similarity is determined and what an empty result looks like.

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 the schema already defines both 'product' (url, slug, or name) and 'limit' (1-15, default 6). The description's 'Accepts a product url, slug or name' simply repeats the schema, adding no new syntax or matching-precedence guidance. 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 resource and behavior: returns products most similar to a given one, along with their prices. This is clearly distinct from get_product (single lookup) in intent, though it never names a sibling to route between them. Clear but no explicit 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?

The phrase 'to compare or suggest alternatives' implies a recommendation/comparison use case, but there is no when-to-use vs when-not guidance and no mention of search_products as the alternative for keyword-driven discovery. Usage is implied rather than stated.

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