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

With no annotations provided, the description carries the full burden. It discloses the partial match, case-insensitivity, return fields, and the 5-result limit. It does not mention error handling or no-match behavior, but for a read-only search this is sufficient.

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 a single, efficient sentence that front-loads the action and includes key details (matching behavior, return fields, limit) without any unnecessary wording.

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 low-complexity tool with one parameter and no output schema, the description covers the essential information: what it searches, how it matches, and what it returns. It lacks explicit error or empty-result behavior, but that is not critical for a simple search.

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 schema has only one parameter (nombre_cliente) with 0% description coverage. The description adds that the provided name is used for partial, case-insensitive matching, which clarifies the parameter's semantics beyond the raw name. However, it does not provide format or length constraints.

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 verb (busca), the resource (clientes en Odoo), the matching behavior (parcial, case-insensitive), and the return fields with a max limit. This distinguishes it from sibling tools like buscar_producto which search a different entity.

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 implies its usage for searching customers by name, but it does not explicitly mention when to use it over alternatives or any exclusion criteria. For a simple search tool, this is adequate but not explicit.

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 behavioral burden. It discloses partial matching, case-insensitivity, and a maximum of 5 results, which is useful. However, it does not mention read-only nature or error handling, though these are typical for search tools.

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 with no fluff: the first states the purpose and matching rules, the second lists return fields and the result cap. Information is front-loaded and 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?

For a simple one-parameter search with no output schema, the description covers the essential aspects: what it searches, how it matches, and what it returns. It does not specify empty-result behavior, but that is a minor gap for a search 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?

The schema has no description for 'nombre_producto', so the description compensates by explaining the parameter's role as the name to match and how matching works (partial, case-insensitive). This adds meaning beyond 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?

The description clearly states the verb 'Busca' (searches), the resource 'productos en Odoo', and the matching criteria (partial, case-insensitive). It distinguishes from siblings like listar_productos by focusing on name-based search and explicitly lists returned fields.

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 implies usage when a product name is known, but does not explicitly mention when not to use it or compare it to alternatives like listar_productos. The context is clear but lacks explicit routing 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?

With no annotations provided, the description carries the full burden. It discloses that the tool verifies state before and after and requires 'draft' or 'sent' status, which is useful. However, it doesn't disclose what happens on failure, whether the operation is reversible, or what the response contains. The state verification detail adds value but the mutation's side effects are not fully described.

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 with no filler. The core action is front-loaded, followed by the state precondition and verification behavior. Every sentence earns its place.

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 single-parameter tool with no output schema, the description covers the essential action and precondition. However, it lacks information about error handling, what the confirmation result looks like, and any side effects (e.g., sending the order, locking it). Given no annotations and no output schema, a bit more behavioral context would make it 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 compensate. It explains that cotizacion_id is the ID of the quote to confirm, which adds meaning beyond the bare schema. However, it doesn't specify the ID format beyond being an integer, which the schema already provides, so the added value is modest.

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 action ('Confirma una cotización (Orden de Venta) en Odoo usando su ID') and identifies the resource (cotización/Orden de Venta). It distinguishes itself from siblings like crear_cotizacion by focusing on confirmation, though it doesn't explicitly name a sibling alternative.

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 provides clear context: the cotización must be in 'draft' or 'sent' state, and it verifies state before and after. This implies when to use the tool (when confirming a quote) and gives a precondition, though it doesn't explicitly state when not to use it or name alternatives.

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 behavioral burden. It does disclose that this is a creation operation and that it returns either the new quote ID or an error message. However, it omits details about authorization requirements, side effects, idempotency, or failure modes beyond the generic 'mensaje de error', leaving meaningful gaps for a mutation 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?

The description is compact, well-organized, and front-loaded with the core purpose. The Args, Returns, and example sections each earn their place, adding concrete usage detail without unnecessary verbosity.

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 creation tool with no annotations and no output schema, the description covers the essential context: what the tool does, the exact parameter shapes, and the return value. It falls slightly short of a 5 only because it does not mention preconditions such as the client and products needing to exist, or what error conditions can be expected.

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 compensate, and it does thoroughly. It explains cliente_id as the client ID and lineas as a list of dicts with product_id and product_uom_qty keys, and it provides a concrete example. This tightens the loose schema, where lineas items have additionalProperties: true.

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: 'Crea una nueva cotización (Orden de Venta) en Odoo para un cliente específico con las líneas de producto dadas.' This clearly states what is created, in which system, and for whom. It is also easy to distinguish from the sibling tools, which are search/listing/confirmation operations rather than creation.

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 invocation context obvious: an agent should call this tool when it needs to create a new sales quotation with specified product lines for a client. It does not explicitly name alternatives or list when not to use it, but the creation-oriented wording is unambiguous enough to avoid confusion with the search/confirm siblings.

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 burden and does disclose the return shape: a formatted string with ID, name, code, and price, or an error message. However, it does not mention ordering, pagination, read-only status, or side effects, leaving moderate gaps.

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 compact and well-structured, with the main action front-loaded and an Args/Returns section. Every sentence adds meaningful information, aside from the minor redundancy of 'Args: None' with the schema.

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 0-parameter listing tool with no output schema, the description is nearly complete: it identifies the resource and specifies the returned fields and error fallback. It omits details about pagination beyond the first 20, but that is a minor gap for this complexity level.

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 has zero parameters, so the 0-parameter baseline of 4 applies. The description reinforces this with 'Args: None', and the input schema already fully covers the empty parameter set.

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: listing the first 20 sellable products in Odoo, with a clear scope. This distinguishes it from the sibling buscar_producto, which searches for a specific product rather than listing a range.

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 guidance is given about when to use this tool versus buscar_producto or the other siblings. The only signal is implicit, and the description never states exclusions or the selection rule that would route an agent to this tool.

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