Compraventa360 — PYMEs en venta (Ecuador)

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

Annotations already declare read-only, idempotent, closed-world behavior, but the description adds substantial scope information: what public fields are included, that confidential figures (revenue, EBITDA, employee counts) require an NDA, that demo listings are excluded, and that private contact data is never returned. This goes well beyond the 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?

The description is front-loaded with the primary action and resource, then efficiently adds return scope and exclusions. There is no redundant filler; every clause adds useful constraint or content 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 simple ID-based lookup with no output schema, the description is complete enough: it explains what fields are returned, what is excluded for confidentiality, and which listings are skipped. Annotations cover the safety profile, so the remaining description content fills the return-value gap well.

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%, and the single business_id parameter is already documented as a UUID in the schema. The description reinforces that the ID is a UUID but does not add syntax, format, or validation details beyond what the schema provides, so a baseline 3 is appropriate.

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 ('Devuelve'), resource ('información pública de un negocio publicado en Compraventa360'), and retrieval key ('dado su ID (UUID)'). This clearly distinguishes it from the sibling search tool, which would be used for discovery rather than direct detail retrieval by ID.

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 that the tool requires a business ID and returns public detail, so an agent can infer it should be used when the ID is known. It does not explicitly name the alternative search_businesses or say when not to use this tool, 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?

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: results are restricted to 'inventario aprobado' and financial figures (revenue, EBITDA, employees) are deliberately withheld pending an NDA, which prevents the agent from promising data this tool cannot return.

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: capability/scope, filter list, and return/limitation note. No redundancy and the core purpose leads the text.

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-shape burden and does it well: it names the returned fields (nombre, categoría, ciudad, asking_price_usd, URL pública) and explicitly flags the data that is NOT returned and why. Nothing essential for correct invocation 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 100%, so all six parameters are already documented in the schema. The description restates the filter dimensions and the USD unit for min_price/max_price, but adds essentially no syntax or format detail 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?

States a specific verb and resource ('Busca listados públicos activos del marketplace Compraventa360') with scope (PyMEs en Ecuador) and enumerates the filter dimensions. The contrast with the sibling get_business is inferable from 'listados' (search/list) versus a single-resource fetch.

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 filtering dimensions are described, which implies when the tool is useful, but there is no explicit when-to-use vs when-not guidance and no mention of the sibling get_business for retrieving a single listing. Usage is left to inference.

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