Gameshop Enter — retro Nintendo & Pokémon TCG (EU)

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 covered. The description adds genuinely useful context about what the returned checkoutUrl does (adds to cart, opens checkout) and that url/local follow the buyer's country, but says nothing about failure modes for unknown SKUs or out-of-stock items.

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 sentences that lead with the action and its scope, with no filler. The trailing country clause is somewhat compressed and slightly redundant with the schema, but it is not wasted space.

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?

There is no output schema, so the description carries the return-value burden, and it does so reasonably by naming price, stock, details, url and checkoutUrl. Missing only edge-case behavior (unknown SKU, stale stock), which is minor for a simple read.

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 country parameter's description is already very detailed, so the description only restates it in compressed form. With the schema doing the heavy lifting, baseline 3 applies; the "as returned by search_products" hint for sku is the only marginal addition.

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 — fetching current price, stock and details for one product by SKU — and explicitly ties the SKU to search_products, so it is distinguishable from that sibling at a glance. It also names the extra artifacts (url, checkoutUrl) the caller gets back.

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 "SKU (as returned by search_products)" phrasing implicitly routes the agent here after a search, and the country note explains the variant-selection behavior. It stops short of explicitly stating when not to use it or how it differs from get_quote/store_info.

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 only cover read-only/idempotent/non-destructive safety; the description adds substantial semantic context beyond that: what is bundled into the quote (shipping tier, promotion, duties for US), the 219-country coverage, and the country-specific extra fields (`local`, `storeUrl`, localised item URLs). This is exactly the value-add the annotations cannot supply.

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 lead sentence is well front-loaded, but the middle clause listing 24 country codes followed by "and 174 more countries worldwide" is self-defeating bulk that could be compressed. The final sentence about local currency and store URLs is long but does carry real information.

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 takes on the burden of describing return values and does so explicitly (checkoutUrl, `local` amounts, `storeUrl`, localised item URLs). For a 2-parameter read-only tool with annotations already covering safety, nothing material 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 100%, so the baseline is 3; the description earns extra by explaining quantity-through-repetition of SKUs and by spelling out country-driven behaviour (US duty inclusion, per-country currency and store URL) that the bare `country` parameter does not convey. Minor deduction for the sprawling country enumeration, which adds bulk more than precision.

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?

Opens with the exact question the tool answers ("what does this cost in total, delivered?") and then enumerates the return payload — items, checkout shipping tier, promotion, EUR total. A specific verb-plus-resource framing that is clearly distinct from search_products, get_product and store_info.

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 "what does this cost in total, delivered?" framing makes the when-to-use case obvious, and "Pass the same SKU twice for quantity 2" tells the agent how to express quantity. It stops short of naming an alternative sibling or an explicit when-not condition, so it is not a full 5.

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 read-only/idempotent/non-destructive, and the description goes well beyond them: it discloses the returned fields (price in EUR, stock status, url, checkoutUrl), explains that checkoutUrl has a cart side effect and opens checkout, and describes how currency and store domain vary with the country argument. That is exactly the behavioral context the annotations cannot convey.

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 purpose is front-loaded, but a large share of the text is marketing and shipping minutiae ("personally tested", 27 EU countries, a 17-country enumeration, 174 more countries) that has no bearing on whether or how to call the tool. That enumeration also duplicates the `country` schema description, so the length is not justified.

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 correctly compensates by naming the return fields and the checkoutUrl side effect, and it explains country-dependent behavior. It falls short only on sibling routing — nothing tells the agent when to escalate to get_product, get_quote or store_info.

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; the description earns more by adding that `query` understands abbreviations ("gba"), Dutch/English names, typos and Pokémon names in German, French, Italian and Spanish. It also restates the country's local-currency/store behavior already documented in the schema, which is redundant but harmless.

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?

Opens with a specific verb+resource: "Search the live catalog of Gameshop Enter" and scopes it to retro Nintendo, PlayStation and Pokémon TCG products. An agent can distinguish it from get_product (single-item lookup) by inference, but the description never names or contrasts the 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?

It gives useful in-parameter guidance ("Pass the buyer's country to get the product pages of that country's own store...") and notes the query engine tolerates abbreviations, typos and non-English names. However, it never says when to prefer this over get_product or store_info, and offers no 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so safety is covered. The description adds useful scope boundaries beyond that: free-shipping thresholds apply EU-only, customs rules apply outside the EU, and coverage spans 191 non-EU destinations — telling the agent what the answer will and will not cover.

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 highest-value item (shipping costs and delivery times) front-loaded, no filler. The trailing clause about 'public profiles where Gameshop Enter can be verified' is marginally tangential but still describes retrievable content.

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, no output schema and thorough annotations, the only thing the description must convey is what content comes back — and it enumerates that fully. Nothing an agent needs to decide to call it 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?

The tool takes zero parameters, so the baseline is 4. The description usefully clarifies that this single call returns the whole policy catalogue with no per-country filtering argument required.

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 enumerates the concrete resource contents (shipping costs, delivery times, customs rules, return policy, payment methods, languages), so an agent can tell this is a static store-policy lookup rather than a product or quote tool. It never states a verb such as 'returns' or 'retrieves', but the resource is unambiguous and clearly distinct from the product/quote 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?

No explicit 'use this when...' statement and no reference to the sibling tools, so the agent must infer that this is the tool for shipping/returns/payment questions. The content enumeration makes that inference easy, which matches the 'implied usage' level rather than full routing guidance.

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