Server Quality Checklist

Tool Scores

• list_categoryA
  3.6/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It discloses the return value (products plus facets) and pagination via nextCursor, which is useful behavioral context. It does not mention potential side effects (though it's clearly read-only) or any constraints like case sensitivity or error handling, but the disclosed behavior is adequate.

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

  Conciseness5/5

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

  The description is two sentences, front-loaded with the core purpose and followed by the key return value. Every sentence earns its place with no redundant wording.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has 7 parameters and no output schema, the description provides a solid overview: it explains the main input (category name), the return payload (products and facets), and pagination (nextCursor). It could additionally mention that filters are available via brand and price parameters, but those are already in the schema, so the description is sufficiently complete for an agent to invoke the tool correctly.

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

  Parameters3/5

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

  Schema description coverage is 86% (6 of 7 parameters have descriptions), so the baseline is 3. The description adds little beyond the schema for parameters; it mentions 'sorted and filterable' but does not elaborate on individual parameters like brand or price filters, which the schema already documents.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states a specific verb+resource ('Browse products in a category by name') and provides concrete examples. It implicitly distinguishes from siblings like search_products (full-text search) and get_product (single product), though it does not explicitly name alternatives.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The usage is implied: use it when you want to browse a category by name. However, there is no explicit guidance on when not to use it or which sibling tool to prefer for other scenarios, such as general search or comparing products.

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

• check_price_availabilityA
  4/5.0
  Behavior3/5

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

  There are no annotations, so the description carries the burden. It adds useful context like 'lightweight' and the inclusion of price-history position, but it doesn't explicitly state that it's read-only, describe error behavior, or mention any side effects or data freshness.

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

  Conciseness5/5

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

  Two concise sentences with no fluff; the first sentence front-loads the core behavior and output, and the second gives a clear use case. Every word earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a single-parameter read-like tool, the description covers the input, the output content (price, stock, price-history position), and the use case. No output schema exists, but the description adequately outlines what is returned. Minor gaps like error handling are not critical here.

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

  Parameters3/5

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

  Schema coverage is 100% and the parameter description already covers id, slug, or URL. The tool description repeats this and adds the 'one product' scope but provides no additional semantic detail beyond the schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The title says 'Check price & availability' and the description specifies a 'price + stock snapshot for one product' including price-history position. This is a specific verb+resource+scope that clearly distinguishes it from sibling tools like get_product or compare_products.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description says it's 'ideal for price tracking' and explicitly scopes it to 'one product' via id, slug, or URL, which gives clear context on when to use it. However, it doesn't explicitly name alternatives or state when not to use it.

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

• compare_productsA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It discloses the return shape ('Returns one detail object per input'), which is useful, but does not mention error handling for invalid inputs, behavior when some IDs fail, ordering, or rate limits. This is a notable gap for a batch operation.

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

  Conciseness5/5

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

  Two sentences, front-loaded with the action, no fluff. The first sentence states the purpose, the second clarifies the return format. Every word earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple one-parameter tool, the description explains the core function and return shape. However, without an output schema or annotations, it lacks details on partial failures, response ordering, or whether 'full details' matches get_product. The essentials are present, but edge-case behavior is unspecified.

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

  Parameters3/5

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

  The schema already covers the parameter fully with '2-8 product ids, slugs, or URLs to compare.' The description repeats 'by id, slug, or URL' and 'several products,' adding no new semantic detail beyond what the schema provides. High schema coverage means baseline 3 is appropriate.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool fetches full details for several products at once, with a specific verb ('Fetch') and resource ('products'), and includes the purpose 'for side-by-side comparison.' This distinguishes it from sibling tools like get_product (single product) and search_products (search), making its role unambiguous.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage for batch fetching and comparing multiple products, but does not explicitly contrast with alternatives like get_product for single items or search_products for discovery. It provides clear context but lacks explicit exclusions or alternative tool guidance.

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

• get_productA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description must convey behavioral traits. It clearly indicates a read operation via 'Fetch' and lists output fields, but does not disclose error handling, rate limits, authentication requirements, or behavior for invalid/missing products. It adds some context but leaves gaps typical for a simple fetch tool.

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

  Conciseness5/5

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

  One concise, front-loaded sentence that states the action, input, and output details. No filler or redundancy; every part contributes to understanding the tool's function.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with a single parameter and no output schema, the description covers the core purpose, accepted inputs, and returned data fields. It lacks explicit error/edge-case behavior, but overall it is sufficiently complete for an agent to invoke successfully in most scenarios.

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

  Parameters3/5

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

  The schema already describes the single parameter idOrUrl with 'Galaxus product id, slug, or full product URL' (100% coverage). The description echoes this and adds the nuance 'numeric id', but does not meaningfully enrich the parameter understanding beyond the schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb+resource ('Fetch full details for a single product') and enumerates the exact data fields returned (description, GTIN, specifications, images, rating, availability, price history). It clearly distinguishes from sibling tools like search_products (which lists products) and check_price_availability (which focuses on price/availability only).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage when needing comprehensive details for one specific product, and mentions accepted input formats (id, slug, URL). However, it does not explicitly name alternative tools or state when not to use it, though the context makes the intended use clear.

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

• search_productsA
  4.2/5.0
  Behavior4/5

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

  There are no annotations, so the description carries full burden. It transparently reports that results include price, rating, availability, URL, and a nextCursor for pagination, which is valuable behavioral context about output and pagination. It does not explicitly mention read-only nature or login requirements, but 'search' strongly implies non-mutating behavior, and no such missing details are critical.

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

  Conciseness5/5

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

  The description is a single, well-structured sentence that front-loads the purpose ('Search the Galaxus / Digitec catalog by keyword') and then lists the key return values. Every word contributes, with no redundancy or fluff.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has 8 parameters but a rich schema, no output schema, and no annotations, the description covers the essential return values and pagination mechanism. It does not mention the available filters (sort, brand, price, rating) in prose, but the schema handles those. Sibling alternatives are not referenced, but the description is largely complete for a search tool.

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

  Parameters3/5

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

  Schema description coverage is high (88%), so the baseline is 3. The description adds almost no parameter-level semantics beyond noting keyword search and the nextCursor return field; it does not explain sort, brand, price filters, or limit behavior, but these are already described in the schema properties.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states it 'Search[es] the Galaxus / Digitec catalog by keyword' and specifies return fields (price, rating, availability, URL, nextCursor). This verb+resource+scope distinguishes it from sibling tools like get_product (likely single-product lookup) and list_category (category browsing).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context for when to use: performing a keyword-based catalog search with pagination. However, it does not explicitly contrast with siblings (e.g., 'use get_product for exact product details') or state when not to use it, so it stops short of an explicit when/when-not.

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