Hacé Cuentas — Calculadoras

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

With no annotations, the description carries full burden. It states the tool 'calculates a live result' and returns JSON, implying a read-only computation. It does not disclose potential side effects, authentication needs, or error handling. The behavioral traits are basic but not detailed.

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 concise (three sentences) and front-loaded with the core action. Every sentence serves a purpose: action, input structure, optional parameter, output format. No redundancy.

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?

The tool is moderately complex with nested inputs and no output schema. The description tells the agent to see get_calculator for inputs but provides minimal detail on the return format ('Devuelve el resultado calculado en JSON'). More specifics on result structure would improve completeness.

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 baseline is 3. The description adds value by connecting the 'inputs' object to fields from get_calculator, clarifying its structure. The optional lang parameter is also highlighted. This goes beyond the schema's individual descriptions.

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's purpose: 'Calcula el resultado de una calculadora en vivo' (calculates the result of a live calculator). It specifies the verb (calcular) and resource (resultado de calculadora), distinguishing it from siblings get_calculator and search_calculators.

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: it explains how to use the tool (pass slug and inputs object, optional lang) and references get_calculator for field definitions. This implies a prerequisite workflow. However, it does not explicitly state when to avoid using this tool or contrast with alternatives, so a 4 is appropriate.

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?

No annotations are provided, so the description must convey behavioral traits. It describes the output but does not mention error behavior (e.g., what happens if slug not found) or side effects. For a simple lookup, this is acceptable but not fully transparent.

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 sentence that efficiently conveys purpose and usage. It is front-loaded and contains no redundant information, though it could be slightly more concise.

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?

Given the tool's simplicity (one param, no output schema, no annotations), the description adequately explains what it does and how to use it alongside compute. It lacks only minor details like error handling, but is sufficient for an agent to use 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?

The schema covers the single 'slug' parameter with a description and example. The description does not add new semantic information about the parameter, though it provides context for the output. With 100% schema coverage, baseline score is 3.

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 it returns a calculator card by slug, listing inputs, types, valid values, and an example URL. It differentiates from siblings by explicitly positioning it as a prerequisite to compute.

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 explicitly advises to use the tool before compute to learn parameters, providing clear when-to-use guidance and context relative to sibling tools.

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?

No annotations provided; description makes clear it is a search tool returning identifiers. It does not mention any side effects, but as a search tool, this is adequately transparent.

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 efficiently convey purpose, usage, parameters, and relationship to siblings with no superfluous 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?

Given no output schema, the description adequately specifies the return value (slug) and its intended use. Could be slightly more explicit about the exact structure of results, but sufficient 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?

Schema coverage is 100% and the description adds meaning by explaining the purpose of each parameter (keyword, optional category, limit) and the role of the return value (slug).

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 it searches calculators by keyword (e.g., 'imc', 'préstamo') and differentiates from siblings by specifying it returns slugs for use with get_calculator or compute.

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 to search by keyword, optionally filter by category and limit, and that the result slug is intended for subsequent use with sibling tools.

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