SuntekStore catalog

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

Beyond the annotations, the description discloses genuinely useful behavior: each line is validated against current price, listing status and stock; nothing is charged by the call; stock is not reserved; the shopper pays on the hosted link with US address and tax added there. The notable gap is that idempotentHint=false is never explained — it doesn't say whether repeat calls create duplicate carts.

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?

Five tight sentences, purpose front-loaded, then validation, payment flow, side-effect disclaimer, and the item limit. No filler and nothing repeated from the schema 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 should cover the transaction lifecycle, and it does well: cart creation, validation, hosted checkout, tax, and the no-charge/no-reservation guarantee. It is slightly incomplete on the return value (cart id vs. link) and on authentication/idempotency expectations.

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%, so the description must carry parameter meaning, and it partially does: it explains that items are products with quantities, that each line is validated, and that up to 12 different items are allowed. It omits where SKUs come from (e.g. search_products/get_product) and the per-line quantity cap of 10, leaving real gaps.

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 resource: bundle several products with quantities into one order and return a single Stripe Checkout link. That is far more than a restatement of the name. It stops short of differentiating from the sibling create_checkout_link, which sounds like an overlapping capability, so an agent cannot fully disambiguate from the description 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 implied by 'several products ... into one order' (i.e., use this for multi-item carts), and the up-to-12-item ceiling gives a practical bound. However, there is no explicit when-to-use/when-not guidance and no routing to create_checkout_link or search_products, which an agent would plausibly need.

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 and openWorldHint=false, so the safety profile is covered. The description still adds meaningful context beyond that: no charge is made and no stock is reserved, clarifying the non-mutating semantics in domain terms. It omits failure behavior for an invalid SKU, but the added value is real.

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 padding, and the key outcome (a payment link) is stated first. Every clause earns its place by either defining the action or clearing up the no-side-effect 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?

For a two-parameter tool with no output schema, the description covers what is returned (a link), that inputs are validated, and that no charge or stock reservation occurs. Only edge behavior on validation failure and the default quantity are left unstated.

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 description names both inputs and states they are validated, which is the minimum needed to interpret them. It does not explain the quantity bound (1-10) or the SKU format, though the numeric constraints themselves live in 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?

Names a specific verb ('validate') and resource ('link the shopper opens to pay on Stripe Checkout'), so the outcome is unambiguous. It doesn't explicitly contrast with the read-only catalog siblings (get_product, search_products), but its purpose is transparently distinct from 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?

The sentence 'the shopper completes payment themselves' implies the intended scenario (delegating payment to the buyer), and 'does not charge anything or reserve stock' scopes what the tool is not for. There is no explicit when-to-use vs. an alternative tool, so usage is only implied.

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 and openWorldHint=false, so safety is covered; the description adds useful behavioral context by listing the returned fields (status, items, carrier, tracking, ETA) and the privacy guarantee that no personal details are returned. It stops short of covering access failures or error behavior for a bad order/email pair.

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 lookup scope and inputs come first, the return payload second, and the privacy caveat last. No filler or repetition of the title.

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 present, the description usefully enumerates what is returned, and it identifies both required parameters. A minor gap is that it does not state what happens on a non-matching order/email (error vs empty), but for a simple two-param read this is close to 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 0%, so the description must carry both parameters — and it does: order_no is clarified with a concrete format example (ST2610010001) and email is clarified as the address used at checkout. That meaning is not derivable from the bare string types in 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 (look up) and resource (an order) plus the exact inputs needed (order number like ST2610010001 and checkout email). It also enumerates the returned fields, so an agent can distinguish it from the cart/checkout/product siblings at a glance.

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 the required identifier pair — you call this when you have an order number and email — but the description names no alternatives or when-not conditions. Since no sibling tool overlaps this purpose, the omission is not costly, but no explicit routing guidance is 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=true and openWorldHint=false, so the safety and scope profile is covered. The description adds the content inventory (what policies are returned), but says nothing about return format, currency/locale applicability, or freshness — though for a static read-only tool the bar is lower.

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 that identifies the resource first and then the payload. It is dense and topic-list style rather than prose, but every element earns its place with no filler.

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 lookup with no output schema, the description supplies the essential information: the resource and the set of policy topics returned. Only minor gaps remain (no indication of currency/region or update frequency).

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 schema is empty and nothing in the description is needed to compensate for 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 a specific resource (store policies) and enumerates the exact topics covered — shipping, delivery times, returns, tax, payment, how to buy — so an agent knows precisely what content comes back. It does not explicitly contrast with siblings, but the retrieval scope is 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?

There is no statement of when to call this versus other tools, nor any preconditions or exclusions. Usage must be inferred from the topic list; nothing tells the agent to prefer this over answering policy questions from general knowledge.

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 and openWorldHint=false, so the safe, non-external-fetch read profile is covered. The description adds what the payload contains (specs, price, stock, delivery, returns, links), but says nothing about behavior on a missing/unknown SKU. With annotations carrying the safety burden, a 3 is appropriate.

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, front-loaded with the core purpose and then the return contents and an inline example. No filler and nothing an agent must hunt for.

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-param read tool with no output schema, listing the returned facts (specs, price, stock, delivery, returns, links) largely compensates for the absent output schema. The only real gap is error/not-found behavior, which is minor for this 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 coverage is 0% and there is one required param, so the description must carry the semantics. It supplies both the meaning (SKU) and a concrete format example (ST-54137787), which meaningfully exceeds the bare 'string' type in the schema. It could go further on case sensitivity or format rules.

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 with scope ('one product by SKU') and enumerates the returned fields, which distinguishes it implicitly from the plural search_products sibling. It stops short of naming that sibling explicitly, so it is clear but not maximally differentiated.

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 'one product by SKU' versus a search tool, but there is no explicit when-to-use/when-not statement or named alternative. An agent can infer the keying requirement from the required sku param, but nothing in the text routes it against create_checkout_link, get_policies, or 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 cover safety (readOnlyHint=true, openWorldHint=false), and the description adds genuinely non-obvious behavior: the grouping semantics of non-relevance sorts, the free US shipping note, the returned fields including Prop 65 warning and return policy, and the filters_excluded_all signal. This goes well beyond structured fields.

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 dense, single-paragraph definition front-loaded with purpose and scope before behavioral details. Every sentence carries information, though the length is on the heavier side for a search tool.

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 return-value burden and does so well (fields returned, shortened descriptions, fallback). The main gap is pagination guidance for page/per_page given a 9-parameter 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?

With 56% schema coverage, the description compensates by mapping keywords, category, price range, delivery days and sort options to the parameters and, importantly, explaining the sort grouping semantics that the schema enum cannot convey. Page, per_page and in_stock_only remain undocumented in both places, so it is strong but not exhaustive.

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 (search SuntekStore's catalog of specialty parts) and scopes it (filters by keyword, category, price, delivery). It also distinguishes itself from the sibling get_product by noting that descriptions are shortened here while get_product returns full text.

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 agent is told how to filter and sort and is explicitly routed to get_product when full descriptions are needed. The filters_excluded_all fallback also clarifies behavior when filters return nothing, though there is no explicit 'when not to use this tool' statement.

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