EveryHourDeal Shopping

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

No annotations are provided, so the description carries the full burden. It discloses the comparison output shape (which is cheapest and fastest) but never states this is read-only, what happens with unknown/duplicate IDs, or whether missing fields cause errors. It reads as a safe read, but that is inferred rather than declared.

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 compact sentence that front-loads the verb, the resource, and the operand range, then appends the compared dimensions and the derived result. No filler or redundant restatement.

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 right thing by summarizing return value (cheapest and fastest). It is complete for a simple one-parameter comparison tool, though it could note the read-only nature and behavior on invalid IDs given the absence of annotations.

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 0% and the single 'ids' array has no item-level description. The description partially compensates by establishing that the values are EveryHourDeal product identifiers and that 2-5 must be supplied, matching the min/maxItems. It still omits the ID format (slug vs numeric) needed to populate the array.

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 (Compare) and resource (EveryHourDeal products) with the 2-5 operand range and the exact dimensions compared (price, highlights, delivery days). It also previews the derived verdict (cheapest/fastest). It doesn't name a sibling tool to differentiate from, but the comparison semantics are distinct from get_product/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?

Usage is implied by 'Compare 2-5 products side by side', which suggests reaching for this when evaluating multiple candidates rather than a single lookup. However, there are no explicit when/when-not rules and no mention of the sibling tools (get_product, search_products) that an agent must use first to obtain IDs.

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?

No annotations are provided, so the description carries the full burden. It does disclose a useful behavioral trait — that the result is time-sensitive, including when the next deal starts — but says nothing about freshness guarantees, read-only nature, caching, or rate limits.

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 sentence with the resource front-loaded and no filler. Every clause earns its place by adding the 'right now' and 'next one starts' semantics.

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 sketches the return shape (the featured product plus the next deal's start time), which is the right move. It is close to complete for a zero-param, zero-annotation lookup; only freshness/permission behavior 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?

The tool takes zero parameters, so per the rubric the baseline is 4. There is no parameter surface for the description to explain or for the schema to omit.

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 — 'the product featured as EveryHourDeal's Deal of the Hour right now' — which clearly distinguishes it from the search/get/compare sibling tools. It lacks an explicit verb ('returns'/'fetches'), but the resource and scope are unambiguous.

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 to call when it needs the current featured deal, but there is no explicit when-to-use statement, no exclusions, and no reference to the sibling product tools it competes with.

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?

No annotations are provided, so the description carries the full behavioral burden. 'Get one' implies a read, but nothing is said about authentication, error behavior for an unknown id, or what a successful result contains — for a lookup tool with zero annotation coverage this is a notable 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?

A single short sentence with the scope constraint front-loaded and no filler. Every clause earns its place, including the provenance hint.

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 one-parameter lookup this is roughly adequate, but with no output schema and no annotations the description leaves the return shape and failure mode unstated. It covers the minimum an agent needs to make the call but not to 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?

There is one parameter and schema description coverage is 0%, so the single field is documented nowhere structurally. The description partially compensates by identifying the id as an EveryHourDeal product id obtained from search_products, but adds no format or validity details beyond that.

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 ('Get one ... product') with an explicit scope qualifier ('by id'), so the agent knows this is a single-item retrieval rather than a list. It gestures at sibling context by noting the id originates from search_products, but does not otherwise differentiate itself from compare_products or deal_of_the_hour.

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 parenthetical '(from search_products)' implies a usage path by telling the agent where the id comes from, which is genuinely useful. However, it never states when to use this over compare_products or deal_of_the_hour, nor any exclusions or prerequisites.

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?

With no annotations, the description carries the full disclosure burden. It usefully reveals that results are aggregates (department plus product count), implying a read-only browsing operation, but says nothing explicit about read-only behavior, result ordering, pagination, or whether departments carry identifiers usable in follow-up calls.

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 no filler, and the key content (departments + counts) is front-loaded. It is terse to the point of reading as a fragment rather than a tool instruction, 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?

For a trivial zero-parameter list tool with no output schema, the description adequately signals return content (department names paired with product counts). Minor gaps remain around result format, ordering, and whether department identifiers are returned for downstream calls, but these are small for a tool this simple.

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; baseline of 4 applies. No parameter-level context is needed or missing.

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 (EveryHourDeal's departments) and what is returned (product count per department), which is enough to separate it from product-oriented siblings like search_products and get_product. The verb 'list' is only implied by the tool name, and the description reads more like a data label than an action statement, keeping it below a 5.

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 mention of alternatives (compare_products, get_product, etc.), and no context on when a department overview is preferable to searching products directly. The agent must infer the use case from the resource name alone.

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?

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses return fields (name, price in USD, link, image, delivery days) plus shipping/returns policy, but says nothing about pagination, the limit ceiling, rate limits, or error behavior for a 6-parameter query tool.

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, no waste, and the catalog scope is front-loaded before the return-value list. Slightly listy on return fields but still efficient.

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 and no annotations, the description does cover return fields, which is valuable. But it omits usage routing and most parameter semantics, so for a 6-parameter search tool it is only minimally 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 description coverage is only 33% across 6 parameters, so the description should compensate but does not. It never explains sort ordering, limit semantics, price-range filtering, or how 'department' relates to the enumerated categories, leaving min_price/max_price/sort/limit undocumented anywhere.

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 ('Search EveryHourDeal's US catalog') and enumerates the product domain, so the agent knows exactly what this retrieves. It does not, however, position itself against siblings like get_product or list_departments, so sibling differentiation is left to inference.

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 guidance on when to search versus compare_products, get_product, or list_departments, nor any stated prerequisites. Usage is only implied by the word 'Search'; an agent must guess at routing.

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