SoundCreation Catalog

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

Beyond the annotations (readOnlyHint=false, idempotentHint=false), the description discloses a real side effect: it creates an order and generates a payment link. It also adds operational context: authentication header requirement, supported shipping destinations, and VAT-inclusive pricing consistency with get_product.

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?

Three sentences deliver the action, the auth requirement, shipping constraints, and pricing behavior with no filler. The main purpose is front-loaded, and every sentence adds decision-relevant 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?

For a write operation with nested objects and no output schema, the description covers the essential behavioral context: what is created, what the customer receives, auth expectations, and shipping limitations. It does not spell out the exact response field for the payment link, but the description and schema together give enough to invoke the 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 description coverage is 50%, and the description only indirectly covers parameter meaning by confirming prices/VAT and shipping country limits. It adds useful context for expected_total via the get_product price match, but it does not explain buyer or shipping_address semantics beyond what the schema already provides.

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 opens with a specific verb and resource: 'Create an order and get a Stripe payment link.' It clearly states the outcome and is distinct from the read/list/search sibling tools, so an agent can identify this as the checkout-creation action without needing to inspect the 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?

The description gives concrete preconditions and exclusions: authentication via X-Api-Key is required, shipping is limited to RO/HU/DE, and prices match get_product. It does not name an alternative tool, but among the siblings there is no other create/checkout tool, and the country restriction effectively tells the agent 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.

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

Annotations already mark the tool read-only and open-world, but the description adds substantial behavioral detail: it defines the substitute list's composition (up to 5, same kind, same price band, brief record fields) and what triggers it. No contradiction with the readOnlyHint/openWorldHint annotations.

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: the first establishes the core purpose up front, the second handles the only edge case an agent needs to know. There is no filler or repetition of schema 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 output schema, the description is the sole source for the return shape and it covers the main fields, the substitution behavior, and the complete record layout for alternatives. The tool is simple enough that an agent can invoke it correctly with the given information.

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% for both parameters, so the schema already documents product_id and language. The description adds only a slight tie-in via 'localized price' but does not need to compensate for a coverage gap.

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?

Description opens with a concrete action-resource pair ('Get full details for one product by id') and enumerates the payload (description, specs, stock, VAT-included localized price). The closing instruction 'offer them instead of searching' clearly separates this single-item lookup from the search_products sibling.

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 description makes the primary use case explicit (fetching one product by id) and gives a clear conditional: when the product is out of stock, surface substitutes rather than searching. It does not explicitly name search_products as the alternative, but the directive is unambiguous.

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=true, so the safety profile is covered. The description adds useful behavioral detail by specifying exactly what each result contains: set price, separate part costs, savings, and included 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?

Three sentences, each earning its place: definition, result contents, and use case. The practical example ('instrument plus the accessories normally needed with it') adds clarity without bloat, and the most useful guidance is front-loaded.

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 list tool with nine parameters and no output schema, the description covers the core domain concept, output shape, and appropriate use case. It relies appropriately on the schema for parameter details, though it could mention default language/currency or pagination if those were non-obvious.

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 89%, so the input schema already documents most parameters well. The description adds context about bundle semantics and result contents but does not substantially clarify parameter meanings beyond what the schema provides.

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 uses a specific verb and resource ('List bundles'), defines what a bundle is, and explicitly contrasts it with listing separate products. The 'recommending one set beats listing five separate products' line makes its purpose distinct from sibling product-search tools.

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 clearly states when to use the tool: for 'what do I need to get started' questions where a bundle is more helpful than separate product listings. It does not explicitly name alternative tools or state when not to use it, so it falls short of 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?

Beyond readOnlyHint and openWorldHint annotations, the description adds useful behavioral detail: each response entry corresponds to a physical unit with its own price, condition note, and product page. It also warns that availability is immediate-only because quantities are small and often one-of-a-kind — crucial guidance the annotations do not provide.

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 description is front-loaded with the core action, then adds a clear definition, per-unit output behavior, and a practical availability warning in three sentences. Every sentence earns its place, including the Romanian term which helps resolve locale ambiguity.

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 9 optional parameters, no output schema, and read/open-world annotations, the description fills important gaps: it specifies the shape of returned data, emphasizes immediate-only availability, and scopes the tool away from normal catalog listings. An agent has enough context to call the tool 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 89%, and parameter descriptions already explain sort, brand, limit, query, offset, category, language, max_price, and category_id. The description itself does not elaborate on any parameter semantics, so it stays at the baseline rather than adding extra value.

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 verb and resource: listing open-box/ex-display units, with clarifying terms like 'resigilat' and 'returned or opened stock sold cheaper.' It also distinguishes this tool from normal catalog listings by stating these units are NOT part of the normal catalog listings.

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 description gives clear context for when the tool is relevant: open-box/ex-display inventory with per-unit pricing and small quantities. It says these units are not normal catalog listings, implying search_products or similar tools are for catalog items, but it does not explicitly name an alternative tool.

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=true, so the safety profile is covered. The description adds useful behavioral context beyond that: each result carries current price and price_old, the default sort is by biggest reduction first, and the list reflects current promotions. No contradiction with annotations.

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?

Three short sentences, each earning its place: one for purpose and ordering, one for the key return fields, one for usage guidance. The most important information is front-loaded and there is 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 read-only list tool with no output schema, the description covers purpose, default ordering, return-field expectations, and when to use it. The optional parameters are well documented in the schema, so nothing an agent needs to select and invoke this tool correctly 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 description coverage is 90%, so the schema already documents most parameters well; the description mostly repeats the default sort behavior already present in the sort parameter." It does not add meaning beyond what the schema provides, so the baseline of 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 verb and resource: "List what is discounted at SoundCreation right now," with a clear ordering rule ("biggest reduction first"). It also distinguishes itself from search_products by saying "rather than searching product by product," so an agent can tell it apart from its 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?

Explicitly says when to reach for this tool: "when the customer asks what is on offer." It also names the alternative behavior to avoid (searching product by product) and points to the better tool for that case, giving the agent concrete selection 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 readOnlyHint and openWorldHint annotations, the description adds useful behavioral details: query results are relevance-ranked, filter-only results are sorted, and all prices include VAT and are locale-correct. No contradiction with annotations.

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?

Three sentences, each earning its place: core capability first, then behavioral distinction between query and filter modes, then pricing/locale note. No fluff or redundant schema restating.

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 13-parameter tool, the description combined with the 100%-covered schema is sufficient for selecting and invoking the tool correctly. There is no output schema, but the parameter descriptions already hint at returned fields like category_id and price_old, so the missing explicit return format is a minor 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 coverage is 100%, so the baseline is 3. The description adds composition guidance beyond the schema by showing how free text maps to fields like brand/model/category and by giving the 'cheapest in-stock electric guitar under 2000' example that combines multiple filters.

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 clearly states the tool searches the SoundCreation catalog by free text and/or filters, with a specific verb and resource. It doesn't explicitly differentiate from sibling tools like list_bundles or get_product, but the broad search scope is evident.

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 clear context on when to use a query (relevance-ranked) vs. filters only (sorted browse), including a concrete example. It does not provide explicit when-not-to-use guidance or point to specialized sibling list tools, so it falls short of a 5.

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