Delegum

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

The description adds behavioral context: it not only calculates but also compares options and recommends. Annotations indicate readOnlyHint=true, which is consistent. No contradictions. However, it does not discuss edge cases or error handling.

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, concise, front-loaded with the purpose. Every word is necessary and 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?

Given no output schema, the description mentions the output includes interest savings and a recommendation, which is sufficient. It could briefly mention the output format, but overall it is complete enough for the complexity.

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 schema already describes all parameters. The description adds a high-level explanation of what the tool does (compare options) but does not add specific parameter meaning beyond the schema. 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?

The description clearly states it calculates the effect of early amortization for a mortgage (French system), compares two options (reduce monthly payment or reduce term), and recommends the best option. It is a specific verb+resource and distinguishes from sibling financial 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 implies the use case (early amortization of a mortgage) but lacks explicit when-to-use or when-not-to-use guidance or alternatives. It is clear enough for the context but could be improved with exclusions.

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 only declare readOnlyHint=true, and the description correctly reinforcing a pure computation adds the actual calculation rules (60% days 4-20, 75% from day 21 for común; 75% from day one for accidente laboral). It also discloses the four outputs (daily, monthly, total, salary loss), which matters because there is no output schema.

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?

Just two sentences, front-loaded with the purpose and the calculation branches, with no filler. The parenthetical rule set makes the first sentence long but every clause carries information an agent needs.

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 takes on the return-value burden and does so by naming the four outputs. Combined with fully documented parameters and correct safety annotations, an agent has what it needs, though the lack of any usage routing to sibling tools is a small 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 description coverage is 100%, so the schema already documents each parameter including the pagas default and the días de baja cap. The description mirrors the two contingencies that map to tipo_baja but adds no syntax or defaulting detail beyond the schema, so the 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 and resource ('Calcula el subsidio por incapacidad temporal (baja médica) de un trabajador por cuenta ajena') and adds the two calculation branches. The qualifiers 'temporal' and 'por cuenta ajena' cleanly separate it from siblings like calcular_pension_incapacidad (permanent) and calcular_cuota_autonomo (self-employed).

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 scope makes the intended use inferable, but there is no explicit when-to-use or when-not guidance and no reference to any sibling tool. It never states, for example, that this covers only employed workers and points self-employed users elsewhere, leaving routing to inference.

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, so the tool is safely read-only. The description adds value by specifying the computed outputs (gap, capital, monthly savings), which goes beyond the annotation. No contradictions present.

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 communicates the tool's purpose and outputs without unnecessary words. It is front-loaded with the core action.

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 description covers the main outputs but does not detail the formulas, assumptions (e.g., using rentabilidad_anual for savings growth), or result units. Given no output schema, slightly more detail would be beneficial, but it is largely 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 coverage is 100%, so parameters are fully documented. The description does not add any extra meaning to parameter semantics, matching the baseline score of 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 explicitly states the tool calculates the retirement gap, including the loss from salary to pension, required capital, and monthly savings. The verb 'calcula' and resource 'brecha de jubilación' are clearly defined, distinguishing it from siblings like 'calcular_jubilacion_anticipada' or 'calcular_pension_publica'.

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 no guidance on when to use this tool versus alternatives. Among siblings, there are other retirement-related tools, but no conditions, prerequisites, or exclusions are mentioned.

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 include readOnlyHint=true. The description adds context by explaining the calculation rule and outputs. No contradictions; the description enhances understanding without repeating the annotation.

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 two sentences with clear front-loading of purpose, followed by output list and sibling tool references. No wasted words, and the structure is easy to parse.

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 fully covers the return values: maximum capital, max price, available down payment, and financing percentage. It also explains the rule and gives sibling tool context, making it complete for a calculator 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% with descriptions for all 6 parameters. The description restates default values and the effort threshold but does not add significant new meaning beyond the schema. Baseline 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?

The description clearly states the tool estimates the maximum mortgage using the Bank of Spain rule (esfuerzo ≤ 30-35%). It specifies the returned values and distinguishes from siblings like 'calcular_hipoteca' and 'consulta_compra_vivienda'.

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 advises when to use this tool vs alternatives: for monthly payment details use 'calcular_hipoteca', for a complete purchase with taxes use 'consulta_compra_vivienda'. This provides clear context for agent decision-making.

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 declare readOnlyHint=true, and the description adds substantial behavioral context beyond that: it explains that the complement goes to the parent with the lower sum of public pensions, that granting it to the second extinguishes the first's, that the result is conditional without suma_pensiones_menor, and that prorrata or art. 60.3.b exclusions reduce or deny it. This far exceeds the annotation's safety signal.

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 long and dense, but for a complex legal calculation with 10 parameters each sentence carries useful information. It front-loads what it computes, then flags the key 2025 doctrinal change, then requirements and parameter conditions in a logical order.

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 still explains the amount is fixed per child, paid in 14 payments, and sourced from data/fiscal, and notes that missing data yields a conditional verdict. It stops short of describing the returned fields or verdict structure, but is otherwise complete for an agent to call it 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 description coverage is 100% and the schema parameter descriptions are themselves highly detailed, covering defaults, legal conditions, and calculations. The description's parameter guidance (e.g., 'indica suma_pensiones_menor', 'indica prorrata_porcentaje') largely repeats what the schema already says, so 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+resource: calculates the gender-gap pension complement (art. 60 LGSS). It distinguishes itself from siblings like calcular_pension_viudedad or calcular_deduccion_maternidad_irpf by naming the exact benefit and its legal basis. An agent can identify what it computes without opening 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?

Explicitly lists eligibility conditions (contributory pension, hecho causante since 4 Feb 2021, at least one child) and tells the agent when to supply optional params (suma_pensiones_menor, prorrata_porcentaje, excluido_art_60_3_b). It does not name alternative tools, but the context is otherwise clear.

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?

readOnlyHint=true already tells the agent this is a safe, non-mutating computation. The description adds useful scope context — the applicable regime version (2025/2026) and that the flat rate for new autónomos is included — but says nothing about output format or edge cases. With annotations covering the safety profile, this is a modest but real addition.

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?

A single well-formed sentence with zero waste, front-loading the computed quantity (cuota mensual RETA) before the scope qualifiers. Every clause 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 pure calculator with three fully-documented parameters and no output schema, the description conveys what is computed and under which regime. It could be marginally stronger by hinting at the return shape (a monthly amount in euros), but nothing essential to calling it 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 100%, so the schema already fully documents regimen (with enum values and IRPF default), es_nuevo_autonomo and rendimiento_neto_mensual. The description's mention of the tarifa plana loosely maps to es_nuevo_autonomo but adds no syntax or format detail beyond the schema, so the baseline 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 (Calcula), resource (cuota mensual de la Seguridad Social de un autónomo/RETA), and scope (sistema de cotización por rendimientos reales 2025/2026, más tarifa plana). This lets an agent distinguish it from siblings like calcular_gastos_deducibles_autonomo, calcular_modelo_130 or calcular_tarifa_freelance without opening 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 implies the context of use (self-employed workers under the real-income contribution system) but never states when to choose this over adjacent tools such as calcular_tarifa_freelance or comparar_autonomo_vs_sl, nor any exclusions. Usage is inferable 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?

Despite minimal annotations (readOnlyHint=true), the description discloses rich behavioral and tax-mechanical context: the applicable amounts, the three alternative qualifying conditions for the increment, the automatic application at grado ≥65%, and the crucial fact that the minimum does not reduce the liquidable base but is taxed at zero rate. This goes well beyond what the annotations 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 dense but appropriately sized for a complex tax rule, and it front-loads the core calculation. Every sentence adds relevant legal or practical detail, though the single-paragraph structure could be slightly more scannable.

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 complexity, the description covers the calculation rules, amounts, conditions, and tax treatment thoroughly. However, with no output schema, it does not explicitly state what the tool returns (e.g., a numeric result or breakdown), leaving a minor completeness 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 description coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by mapping 'grado' to specific amounts and explaining the legal conditions that make 'necesita_asistencia' relevant or irrelevant. It reinforces the schema's note that at '65oMas' the extra amount applies regardless of the boolean.

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 states a specific verb ('Calcula') and resource ('mínimo por discapacidad en el IRPF'), gives legal references, and specifies the exact scope (contribuyente or ascendiente/descendiente a cargo). It clearly distinguishes this specialized deduction calculator from generic IRPF or other deduction tools without needing to name 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?

The description provides clear context for when the calculation applies, including degrees, eligible persons, and the conditions for the additional 3,000 €. It does not explicitly name alternative tools or state when not to use this one, but the scope is sufficiently clear to guide selection.

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 only supply readOnlyHint and a title, so the description carries the behavioral burden and does so well: it discloses the €150/hijo surcharge, the removal of the SS-contribution cap since 2023, that the 2023 reform expanded rather than removed routes, and that already-received advance payments are subtracted. This is rich context well beyond the annotation.

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?

Dense but front-loaded with the core calculation (1.200 €/año, guardería increment) before the legal caveats. Every clause carries substantive information, though the run-on legal recitation is slightly heavier than strictly needed to invoke the tool.

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 complex tax-deduction calculator with no output schema, the description gives the agent enough legal and calculation context to invoke it correctly. It implicitly conveys the result is the net deduction (after subtracting advance payments) but never explicitly describes the return shape.

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 four parameters (including the situacion enum, the deprecated madre_en_activo, and gastos_guarderia_anuales) are already documented. The description reinforces the situacion semantics and the per-child €1,000 cap but adds little the schema does not already say, making the baseline 3 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 (calcula) and resource (deducción por maternidad en el IRPF, art. 81 LIRPF) with concrete figures, immediately distinguishing it from siblings like calcular_irpf, calcular_deduccion_discapacidad, and calcular_prestacion_maternidad_paternidad.

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?

Provides clear eligibility context — the three alternative routes of art. 81.1 and the explicit note that with none of them the deduction is 0 € — which tells the agent when this tool yields a result. However, it never names an alternative sibling tool or states when NOT to use this one, so routing guidance is implicit rather than 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?

readOnlyHint=true already covers the safety profile, but the description adds real behavioral context: the calculation method (state or Catalan tariff, wealth coefficients, regional bonifications) and, importantly, the coverage boundary around empresa familiar and the required fallback message to the user. It does not describe the shape of the returned result, which matters somewhat since no output schema exists.

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?

Well front-loaded: purpose first, then exclusions, then the routing warning in caps. The empresa familiar limitation is stated twice (as an exclusion and again as a fallback instruction), which is mildly redundant, though the repetition targets different agent behaviors (don't compute vs. tell the user).

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 6-parameter tax calculator with no output schema, the description covers scope, limitations, and sibling routing thoroughly. The remaining gap is that it never indicates what the result contains (quota breakdown, applicable tariff, bonification applied), which an agent would need to present results 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 description coverage is 100%, so the schema already documents ccaa, grupo_parentesco, patrimonio_preexistente, etc. The description reinforces that patrimonio drives the multiplicador and that ccaa determines the tariff, but adds no syntax or format detail beyond the structured fields — 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 ('Calcula el Impuesto de Donaciones (ISD) en España') and immediately scopes it to 'donaciones en vida entre familiares', which separates it from calcular_sucesiones and other tax calculators. An agent can identify the tool's domain without opening 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?

Explicit when-not rules: excludes the empresa familiar reduction and instructs the agent not to present the quota as an estimate in that case. It also names the alternative sibling ('comparar_donacion_vs_herencia') and the exact scenario that selects it (comparing lifetime gift vs inheritance of a property).

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?

The description adds behavioral context beyond the readOnlyHint annotation by specifying the outputs (reserva de puesto, meses que computan a la SS, coste total). It does not contradict annotations and provides useful details about each leave type's characteristics.

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, well-structured paragraph that front-loads the main purpose and efficiently delivers all necessary information without redundancy. Every sentence adds value.

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?

Despite the absence of an output schema, the description adequately explains the return values (reserva de puesto, meses que computan a la SS, coste total) and covers the tool's scope. It is complete for a calculation tool with 5 parameters and no nested objects.

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%, but the description adds meaning by explaining that 'voluntaria' has restrictions (4 meses–5 años, sin reserva) and that 'cuidado de hijo' includes primer año con reserva. This goes beyond the schema's brief 'Tipo de excedencia' and 'Edad' 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 it calculates rights and costs of a labor leave (excedencia), listing specific types (voluntaria, forzosa, cuidado de hijo, cuidado de familiar) with their constraints. This distinguishes it from sibling tools like calcular_reduccion_jornada or calcular_prestacion_maternidad_paternidad.

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 by detailing the types of leaves and what the tool outputs, but does not explicitly mention when to use it versus alternatives or specify exclusions. The context is sufficient for an agent to infer usage, but lacks explicit 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?

Annotations already indicate readOnlyHint=true, so the tool is non-destructive. The description adds context by listing specific components included and excluding indemnización, which is 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 two sentences, very concise, and front-loads the purpose. Every sentence is essential and there is no waste.

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 has 5 parameters and no output schema, the description sufficiently covers what the tool calculates and excludes. It could mention that results are estimates or depend on jurisdiction, but overall it is complete enough.

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 all parameters are described. The description does not add additional parameter-level details beyond what the schema already provides, so a baseline score of 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?

The description clearly states the tool calculates 'finiquito' (severance) covering unused vacation, proportional extra payments, and pending salaries. It explicitly distinguishes from the sibling tool 'calcular_indemnizacion_despido' by naming it and stating what is excluded.

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 explicit guidance on when to use this tool (for finiquito calculation) and when not to (for indemnización por despido, directing to a specific sibling tool). This fully meets the criteria.

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?

Las anotaciones ya indican readOnlyHint=true, pero la descripción va más allá al especificar que aplica FIFO, que calcula la compensación de pérdidas con límites (25%) y que indica el monto pendiente de compensar. Esto proporciona contexto conductual valioso que no está en las anotaciones ni en el esquema.

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?

La descripción es breve, directa y está redactada en tres oraciones que cubren el propósito central (cálculo de ganancia/pérdida y tributación), el método (FIFO) y la información adicional (compensación de pérdidas). No contiene información irrelevante ni redundante.

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?

Aunque no hay esquema de salida, la descripción ofrece una idea clara de lo que devuelve: importe de ganancia/pérdida, compensación y pendiente. Es suficientemente completa para un agente, considerando la complejidad de una calculadora fiscal de criptomonedas.

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?

El esquema de entrada ya describe todos los parámetros con detalle (cobertura 100%). La descripción general no añade semántica adicional a los parámetros más allá de lo que ya está en el esquema. Se mantiene la línea base de 3 para este caso.

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?

El título y la descripción detallan de manera precisa y específica que la herramienta calcula la ganancia o pérdida patrimonial por operaciones con criptomonedas (venta, permuta, pago, donación) y su tributación en el IRPF, aplicando el criterio FIFO. Además, se distingue claramente de las herramientas hermanas, que son otras calculadoras/impositivas, por lo que un agente puede identificar sin ambigüedad su propósito.

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?

La descripción no proporciona instrucciones explícitas sobre cuándo usar esta herramienta en lugar de otras similares. Aunque por el contexto se infiere que debe usarse para operaciones con criptomonedas, no se mencionan alternativas ni se indican exclusiones. La puntuación se ajusta al estándar de 'uso implícito'.

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 declare readOnlyHint=true; description adds value by explaining no modification occurs and detailing tax rules (e.g., finca rústica exempt from IVA and plusvalía). No contradiction.

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?

Front-loaded with purpose and usage; second part details rules per type. Some redundancy could be trimmed, but overall 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?

No output schema, and description does not explain what the tool returns (e.g., breakdown of taxes, total cost). For a calculation tool, this is a notable 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% (baseline 3). Description adds meaning by explaining when parameters apply (e.g., anejo_de_vivienda only for garaje/trastero, renuncia_exencion_iva for local/nave/rústica) and their tax implications.

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 clearly states verb 'calcula' and resource 'impuestos y gastos de comprar un inmueble que NO es una vivienda', listing specific types (garaje, local, etc.). It distinguishes from sibling by naming 'consulta_compra_vivienda' for houses.

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 use ('cuando la pregunta sea...') and when not ('Para una vivienda usa consulta_compra_vivienda'). Provides usage rules per property type.

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 indicate readOnlyHint=true, which the description does not contradict. The description adds detailed behavioral context about special rules (30% for household supplies, 50% for mixed-use vehicle, 5% global provision) that go beyond schema fields.

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 concise paragraph. It front-loads the core purpose, then efficiently enumerates key special rules with specific percentages. No extraneous words or repetition.

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 14 parameters and no output schema, the description covers the calculation logic well. It explains how inputs relate to deduction limits. However, it does not describe the output format (likely a single deduction amount).

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?

All 14 parameters have schema descriptions (100% coverage). The tool description adds interaction rules (e.g., pct_vivienda_afecta only used with vivienda_habitual, vehiculo_uso_exclusivo flag changes deductibility), enhancing understanding beyond individual parameter docs.

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 specifies the tool calculates deductible expenses for Spanish self-employed in direct estimation (normal or simplified). It lists specific rules (supplies, vehicle, insurance, amortization) and differentiates from siblings like calcular_cuota_autonomo or calcular_modelo_130.

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 for annual deductible expense calculation in IRPF but does not explicitly state when to use this versus other similar tools (e.g., calcular_modelo_130 for quarterly). No when-not-to-use or alternative guidance is provided.

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. The description adds behavioral context (calculates, not modifies) and details about supported mortgage types, enhancing transparency beyond 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 two concise sentences, front-loaded with key outputs and supported types. Every sentence contributes value without 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 description lists expected outputs (monthly payment, total interest, ratio) and supported mortgage types. Absence of output schema is partly compensated by listing outputs, but could mention return format or limitations.

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 descriptions cover 100% of parameters with detailed info. The description adds no new parameter-specific details beyond the schema, so baseline score of 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?

The description clearly states the tool calculates a Spanish mortgage (French system) and lists key outputs (monthly payment, total interest, payment-to-income ratio). It explicitly distinguishes from sibling 'consulta_compra_vivienda' for complete purchase queries.

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 explicit guidance to use 'consulta_compra_vivienda' for a complete purchase consultation, but does not elaborate on other exclusions or alternative tools beyond that.

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?

The description goes well beyond the readOnlyHint annotation, detailing the specific tax rules applied (exemptions, thresholds, regional scales, pension plan exemption). It also indicates the result is an estimate ('orientativa'), providing full behavioral context for the calculation.

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 paragraph that efficiently conveys the main purpose, key rules, and limitations. It is front-loaded with the core action and provides necessary details without extraneous 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?

Given the complexity of Spanish wealth tax (multiple regional regimes, exemptions, thresholds) and the absence of an output schema, the description is remarkably complete. It covers the main components, exclusions, and when not to use the tool, providing sufficient context for correct usage.

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% with detailed parameter descriptions. The tool description adds overall context for the calculation (e.g., how exemptions apply) but does not add new meaning for individual parameters beyond what the schema provides. 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?

The description clearly states the tool calculates wealth tax for individuals, determining filing obligation and estimated tax using regional scales and exemptions. It specifies the scope (no business holdings, no foral territories), which distinguishes it from potential sibling tools for other tax calculations or business wealth.

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 states the tool is for individuals without business shares or non-listed companies, and excludes foral territories (Navarre, Basque Country). It does not directly name alternative tools for excluded cases, but provides clear conditions for use.

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?

The annotation readOnlyHint=true already tells the agent this is a read-only calculation, but the description adds significant behavioral context: it specifies this is an orientative estimation, declares the liquidation of gananciales is not subject to IRPF, and states the model does not cover regional or foral rules. This goes beyond the simple read-only flag and helps set accurate expectations.

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 moderately sized paragraph that is efficiently organized: it starts with the main purpose, lists the covered items, then states exclusions and limitations. Each sentence delivers needed information without fluff. It could be slightly more structured with bullets, but it is concise enough given the tool's complexity.

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 high complexity (17 parameters, conditional mandatory fields), the description covers the tool's scope of application, exclusions, and model validity limitations. It does not explicitly mention conditional parameter requirements, but those are fully documented in the schema. The description is complete for the behavioral contract, though it omits a direct note on how to handle regional variations when interpreting results.

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 the baseline for this dimension is 3. The description does not add parameter-specific meaning beyond what the schema provides, but it does provide overall context that affects interpretation, such as the state-level model limitation. This is consistent with the baseline.

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 estimates the IRPF impact of divorce/separation in Spain and lists the specific tax items it covers (pensión compensatoria, mínimo por descendientes, imputación de renta, deducción por hipoteca). It uses a specific verb and resource, distinguishing itself from general IRPF calculators like calcular_irpf by focusing on the divorce context.

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 for when to use the tool: it explicitly excludes ITP/AJD and plusvalía municipal, and notes it is a state-level model without CCAA or foral variations. This gives the agent boundaries on applicability, though it does not name alternative tools explicitly. The exclusions imply that for other taxes or regional nuances, one should use a different tool, but it doesn't say 'use X instead'.

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, consistent with a calculator. The description adds behavioral context by detailing the calculation logic (per type, days per year, caps, dual pre-2012 tramo), which goes beyond the annotation. No contradictions.

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: two sentences with no redundancy. The first sentence immediately conveys purpose and key parameters, the second gives an alternative. 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?

Given 5 parameters and no output schema, the description is reasonably complete. It covers the core calculation logic and boundaries. However, it does not mention the return format (presumably a single numeric amount), but the tool's simplicity mitigates this. Overall adequate for a calculator 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 100%, so baseline is 3. The description adds value by explaining the meaning of the enum values (33 días/año for improcedente, etc.) and the dual pre-2012 logic, which helps the agent understand parameter selection beyond the schema 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 it calculates only dismissal compensation (indemnización por despido) based on specific types (improcedente 33 días/año, objetivo/ERE 20 días/año) with caps and dual pre-2012 calculation. It distinguishes from the sibling tool 'consulta_despido' which covers the full analysis including finiquito and paro.

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 specifies when to use the tool (for solo indemnization calculation) and when not to use it (for full analysis including finiquito and paro, use 'consulta_despido'), providing clear 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?

Annotations already declare readOnlyHint=true, so safety is clear. The description adds that it simulates growth, which aligns, and discloses what outputs to expect, adding context beyond 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, front-loaded with purpose and outputs, no wasted words. Efficient and clear.

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?

No output schema, but the description mentions key outputs (capital final, intereses, rentabilidad total). It covers parameters and additional capabilities. Missing details on output format, but sufficient for a simulation tool with good annotations.

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% with descriptions for all parameters. The description summarizes that it supports periodic contributions and capitalization frequencies, but doesn't add new meaning beyond what the schema provides. Baseline score 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?

The description clearly states the tool simulates growth of savings/investment with compound interest, listing outputs (capital final, intereses, rentabilidad total). The verb 'simula' and resource are specific, and it distinguishes from sibling financial calculators like mortgage or tax 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?

The description implies usage for compound interest scenarios but does not explicitly state when to use it vs. alternatives or when not to. Given many sibling tools, explicit guidance would improve clarity.

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, indicating a safe read operation. The description adds value by specifying the calculation outputs (cuota íntegra, diferencial, tipo efectivo) and confirming it is a non-destructive calculation. 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?

The description is a single sentence that combines purpose and outputs. It is somewhat dense but not overly long. Could be improved by breaking into separate sentences for clarity, but it is functional.

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 explains what the tool returns (cuota íntegra, diferencial, tipo efectivo). It covers the main inputs (work, capital, gains) and deductions. Missing details like result accuracy or assumptions, but overall complete for a financial calculation 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 100%, so all parameters are documented in the schema. The description provides a high-level overview but does not add per-parameter details beyond what the schema already provides. Baseline score of 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?

The description clearly states the tool calculates the IRPF quota from work, capital, and capital gains, applying deductions and personal/family minimums. It specifies the outputs (full quota, differential, effective rate). This distinguishes it from sibling tools like 'calcular_sueldo_neto' or 'calcular_deduccion_maternidad_irpf', which focus on narrower aspects of IRPF.

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 the tool is for general IRPF calculation but does not explicitly state when to use it versus siblings that specialize in specific parts of IRPF (e.g., deductions, plusvalías). No 'when not to use' or alternatives guidance is provided, leaving the agent to infer usage context.

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?

The annotation 'readOnlyHint: true' already covers the read-only nature of the tool. The description adds minimal behavioral context beyond what is in the annotations and schema, but it does not contradict them. It accurately describes the operation without additional disclosures (e.g., side effects or limits).

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, consisting of two sentences that front-load the core purpose and actions. Every word is essential, and no irrelevant information is included.

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 (3 params, no output schema, read-only), the description adequately covers the functionality. It defines the scope (IVA español, specific rates, two modes). While it does not explicitly mention the return value or error conditions, the context (calculation tool) makes this acceptable.

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 input schema already provides 100% coverage with descriptions for all parameters. The description adds a high-level context ('añadir IVA a una base o extraer la base') but does not provide new details beyond the schema. With full schema coverage, a score of 3 is appropriate as per guidelines.

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 calculates Spanish VAT (IVA) with specific rates (21%, 10%, 4%, 0%) and the two modes (add or extract). It uses a specific verb ('calcula') and resource ('IVA español'), distinguishing it from sibling tools which cover other financial calculations.

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 explains when to use each mode ('añadir IVA a una base' or 'extraer la base de un precio con IVA incluido'), providing clear context. However, it does not explicitly state when not to use the tool or mention alternatives, though the context of sibling tools makes this less critical.

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?

The description fully discloses the tool's behavior: checks conditions, applies coefficients per quarter, and returns reduced pension and loss. It aligns with the readOnlyHint annotation (no destructive actions) and adds context about the two modes and their requirements.

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, well-structured paragraph that front-loads the purpose, then provides specifics in logical order. Every sentence adds value without repetition, making it concise and effective.

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 complexity (4 parameters, no output schema), the description is complete: it covers feasibility checks, coefficient application, and return values (reduced pension and loss). The mention of the prerequisite tool completes the context for proper invocation.

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%, but the description adds significant meaning: it explains the 'tipo' (voluntaria/involuntaria) with conditions (≥35 or ≥33 years), and clarifies 'pension_ordinaria' as the estimated monthly amount. This goes well beyond the schema's basic 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 it calculates the impact of early retirement, checks feasibility, applies reduction coefficients, and returns reduced pension and loss. It distinguishes between voluntary and involuntary types, making the purpose specific and distinct from sibling 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?

The description explicitly guides when to use (to check feasibility and calculate reduction) and mentions a prerequisite (ordinary pension from 'consulta_jubilacion'). It implies when not to use (if no ordinary pension) and provides context for the two modes, aiding correct selection.

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 indicate readOnlyHint=true, so the description doesn't need to emphasize non-destructiveness. It adds context about the calculation logic (e.g., no descendants → ascendants legítima, CC art. 809) and notes what it does NOT calculate (succession tax). However, it doesn't mention potential complexity like regional variations in detail or that results are estimates; still, the description aligns with readOnlyHint and adds some behavioral context, so a 3 is fair.

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, front-loaded with the core purposeaine and exceptions, and every sentence adds value. It mentions what it returns, conditions for ascendants, and a cross-reference to the sibling tool. No redundancy with schemas.

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 description is comprehensive for a tool without an output schema: it lists the outputs (legítima total, part per child, tercio de mejora, etc.), clarifies the ascendant case, and refers to the sibling for tax. The only minor gap is not specifying that the calculations are estimates or may require legal advice, but given the annotations and schema, the information is sufficient for an agent to invoke 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 description coverage is 100%, so each parameter is already described. The description adds meaning to 'tienen_ascendientes' by explaining its conditional usage and legal basis (CC art. 807/809), which is beyond the schema. However, it doesn't clarify the units or format of 'patrimonio_neto' (schema already says euros), nor does it elaborate on 'regimen' beyond the enum. Thus, a 3 is appropriate because schema does the heavy lifting but description adds critical conditional context.

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 calculates the forced heirship (legítima) under Spanish civil law, specifies the legal regimes covered, lists the returned components, and distinguishes from the inheritance tax tool (calcular_sucesiones). This is a specific verb+resource with clear differentiation from siblings like calcular_sucesiones and consulta_herencia.

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 explicitly states when to use it (for calculating legítima) and when not to (for inheritance tax, pointing to 'calcular_sucesiones'). It also provides conditional guidance on when the 'tienen_ascendientes' parameter is required (when num_hijos=0 and régimen 'comun') and when it is ignored (with hijos). This is exemplary usage 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?

Annotations declare readOnlyHint=true, and the description confirms it's a calculation (no side effects). It adds value by explaining the formula and the exemption condition, which helps the agent understand the behavior beyond the annotation. The description does not mention any auth or rate limits, but given it's a read-only calculator, this is acceptable.

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 three sentences long, front-loaded with the core purpose, and no redundant information. Every sentence adds value: purpose, formula with exemption, alternative tool. It is highly concise and well-structured.

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 6 parameters with 100% schema coverage, no output schema, and moderate complexity, the description is fairly complete. It explains the calculation, a key exemption, and provides an alternative. However, it does not describe the output format or indicate whether the result can be negative (e.g., if deductions exceed income). This slight gap prevents a perfect score.

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 baseline is 3. The description adds moderate value by explaining the formula (e.g., '20% del rendimiento neto acumulado (ingresos − gastos) menos retenciones y pagos fraccionados anteriores'), which conceptually ties parameters together. It also covers the boolean parameter (mas_70pct_con_retencion) via the exemption condition. This provides semantic context beyond individual parameter 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 calculates the quarterly fractionated payment of IRPF for autónomos in estimación directa (Modelo 130). It specifies the exact tax form and regime, and differentiates from sibling tools like consulta_autonomo by mentioning it for global view. The purpose is specific and unambiguous.

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 explicit when-to-use context (quarterly IRPF payment for autónomos in estimación directa) and a condition for non-obligation (>70% income from clients that withhold). It also provides an alternative tool (consulta_autonomo) for a global view. However, it does not explicitly distinguish from other calculation tools like calcular_irpf or calcular_cuota_autonomo, so guidance is slightly incomplete.

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. The description adds context about the calculation formula and result interpretation (positive means payable, negative means compensation/refund). This is adequate but not extensive.

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 three sentences, front-loaded with the main purpose, and contains no extraneous information. Every sentence adds value.

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 8 parameters and no output schema, the description explains the calculation and result interpretation sufficiently. It covers the formula and outcome scenarios, though it could mention that results are returned as numbers.

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%, baseline 3. The description adds meaning beyond the schema by explaining the overall VAT calculation logic (IVA devengado minus IVA soportado) and the meaning of positive/negative results, which helps the agent understand how parameters relate.

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 calculates the quarterly VAT self-assessment (Model 303) for self-employed and companies. It explains the core formula and distinguishes from sibling calculators like calcular_iva or calcular_modelo_130.

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 the tool is for quarterly VAT calculations but does not explicitly state when to use it versus alternatives like calcular_iva. No guidance on when not to use.

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 include readOnlyHint: true, so the tool is read-only. The description adds behavioral details: it calculates duration and amount with 70%/60% rates and IPREM caps based on children, which goes beyond the annotation.

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 is front-loaded with the main purpose and includes key details. It is concise, though could be slightly more structured by separating duration and amount.

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?

No output schema, but the description explains the return concepts (duration and monthly amount). For a calculator tool, it is fairly complete, though missing exact IPREM values or formula details.

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% (all parameters described). The description reiterates the main parameters but does not add significant new 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 tool calculates unemployment benefit (prestación contributiva por desempleo), including duration based on days contributed and monthly amount with specific percentages and caps. This is specific and distinguishes it from sibling 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 implies usage for calculating unemployment benefits but does not explicitly state when to use versus alternatives or when not to use. No guidance on exclusions or context.

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 only declare readOnlyHint=true, so the description carries the burden of behavioral disclosure and does well: it explains that partial disability is paid as a lump sum, others as a monthly pension, and that the minimum complement is returned with its income limit but not added to the pension. This adds genuine calculation behavior beyond the read-only annotation.

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?

A single dense paragraph that front-loads the core purpose and then adds essential calculation details. Every sentence contributes useful information, though the density is high and could be slightly more structured for quick scanning.

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?

No output schema exists, so the description must explain return values. It lists the main outputs (base reguladora, percentage, age surcharge, grand disability complement) and clarifies payment forms and minimum complement handling. It could go further on exact return format, but it is largely complete for a calculator with fully documented inputs.

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?

With schema description coverage at 100%, the schema already documents all six parameters thoroughly, including enums, ranges, and roles. The description does not add parameter-specific details beyond what the schema provides, so the baseline score of 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 ('Calcula'), a precise resource ('prestación por incapacidad permanente'), and lists all covered grades and components. An agent can easily distinguish it from sibling calculators like calcular_pension_publica because the description enumerates the exact pension type and calculation elements.

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 by stating what is calculated, but gives no explicit when-to-use, prerequisites, or alternatives to sibling calculators. For a standalone calculator, the purpose makes usage clear, but there is no guidance on when to choose this over related 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?

Annotations already include readOnlyHint: true. The description does not contradict this and adds no additional behavioral details beyond stating it estimates a pension. It is sufficient but not enriched.

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 two sentences: the first states the purpose, the second provides an alternative. It is front-loaded, concise, and contains no unnecessary words.

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 could hint at the output format (e.g., estimated monthly amount). It provides the basic purpose and alternative but lacks details on expected returns or additional factors.

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 the parameters are already well-documented. The description mentions 'años cotizados y base reguladora' but adds no new semantics 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 tool estimates the public retirement pension based on contribution years and regulatory base. It also distinguishes from the sibling 'consulta_jubilacion' by noting that the latter adds gap analysis and savings needs.

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 a clear use case and explicitly mentions an alternative for more comprehensive analysis. However, it does not explicitly state prerequisites or when not to use the 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?

readOnlyHint=true already establishes this is a safe pure computation, and the description adds real context: the percentage brackets (52/60/70%), the income test for the minimum complement, the non-contributory cap, and the dependency on whether the deceased was active, retired, or not registered. For a calculator this is good disclosure beyond the annotation.

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 dense sentences that are front-loaded with the core purpose before the calculation breakdown. Every clause maps to a real output component, though the single long sentence is somewhat heavy to parse.

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 carries the burden of describing what is returned and does so fully, listing base reguladora, applicable percentage, minimum complement, and final pension with the Social Security cap, plus the situational branching. An agent knows exactly what the calculation yields.

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 the schema already documents all six parameters including the enum and conditional requirements. The description restates the drivers (cargas familiares, ingresos) but adds no format or syntax detail beyond what the schema provides, making the baseline 3 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 (Estima) and resource (pensión de viudedad) and enumerates the computed components (base reguladora, porcentaje, complemento a mínimos, pensión final). The resource is unambiguous among the many pension siblings, though it never explicitly contrasts itself with calcular_pension_publica or calcular_pension_incapacidad.

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?

Usage is only implied by the tool's purpose; there is no explicit when-to-use statement, no prerequisites, and no named alternative. An agent can infer it applies to widow's-pension cases, but nothing tells it when another pension tool is the better fit.

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 provide readOnlyHint=true, confirming it's a read-only calculation. The description adds important context: applies 2025 limits, warns about withdrawal taxation (rendimiento del trabajo). No contradictions.

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, concise and front-loaded with the main purpose. Every sentence adds value without 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?

Given high schema coverage and clear description, the tool is well-specified. No output schema, but description hints at two outputs (ahorro fiscal, capital proyectado) and a warning. Slight gap in detailing output structure, but overall sufficient.

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 the schema already documents each parameter. The description adds overall context but does not enhance per-parameter 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 it calculates annual tax savings and projects accumulated capital for a private pension plan. It specifies applying 2025 limits and warns about withdrawal taxation, distinguishing it from sibling pension-related tools like calcular_jubilacion_anticipada.

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?

Usage is implied (for pension plan fiscal calculations), but no explicit guidance on when to use vs. alternatives or when not to use. No mention of prerequisites or exclusions.

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?

The description adds behavioral context beyond annotations: it explains the tool allows compensating prior-year losses, and details the calculation outputs (net gain, tax brackets, effective rate). Annotations already indicate readOnlyHint=true, so the description provides useful additional behavioral traits without contradiction.

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 reasonably concise given the complexity, with all sentences adding value. It is front-loaded with the main purpose, followed by details, and ends with a critical usage note. It could be slightly more streamlined, but it is well structured 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?

Despite no output schema, the description explicitly lists the outputs: net gain, long-term indicator, tax brackets, effective rate, and after-tax gain. It also covers the loss compensation feature. For a complex tax calculation tool, this provides sufficient context for correct invocation and interpretation of results.

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 overall context (e.g., mentions that 'tipo_activo' is only informative, and how parameters like 'saldo_compensacion' are used). However, it does not add much per-parameter detail beyond the schema descriptions. The extra context is helpful but limited.

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 calculates IRPF on capital gains from selling various assets (acciones, fondos, inmuebles, otros). It specifies what it determines (net gain, long-term vs short-term, tax brackets, effective rate, after-tax gain, loss compensation). It also explicitly differentiates from the sibling tool 'comparar_donacion_vs_herencia' by stating when not to use it.

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 explains the tool is for calculating IRPF on capital gains from asset sales. It provides a clear exclusion: if the user is comparing donation vs inheritance, do not use this tool and instead use 'comparar_donacion_vs_herencia'. This gives explicit when-to-use and when-not-to-use guidance with an alternative.

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 indicate readOnlyHint=true, and the description confirms by using 'Muestra' (shows). It adds context that amounts are state maximums before copay and regional supplements, which is useful behavioral info beyond 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 concise with three sentences that front-load the main purpose. It includes acronym expansion and no unnecessary words.

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 description provides sufficient context about the output: it includes amounts, services, and copay regime. However, it does not specify the output format (e.g., table or text), which could aid an AI agent in interpreting results.

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?

Parameter schema has 100% coverage with a detailed description. The tool description does not add additional semantic value to the parameter 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 clearly states the tool shows economic benefits and services from SAAD based on dependency degree, including specific details like monthly amounts, services, and copay regime. This distinguishes it from sibling tools, which are about different financial calculations.

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 dependency grade is known, but lacks explicit guidance on when to use this tool over siblings or when not to use it. No alternatives or exclusions are mentioned.

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 as read-only (readOnlyHint: true). The description adds value by detailing the output (daily and monthly amounts, duration, extras for multiple birth/disability, obligatory weeks, flexible weeks, and carencia verification). It also mentions the legal update, which provides context beyond the annotations. No contradictions.

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 fairly concise for the information it conveys. It is structured with the purpose first, then legal context, then output details. Every sentence adds value. However, it could be slightly more terse by moving some details (e.g., exact week numbers) to the schema or usage notes.

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 lack of an output schema, the description fully explains the return values (daily and monthly amounts, duration with extras, obligatory weeks, flexible weeks, carencia check). It also covers key inputs implicitly (age, family type, disability). The legal reference provides complete context for the calculation.

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% with parameter descriptions, so the baseline is 3. The description adds high-level context (duration formulas, extras) but does not provide additional semantic details for individual parameters beyond what the schema already provides. It adequately complements the schema without adding significant new meaning.

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 'Calcula' and the specific resource 'prestación por nacimiento/adopción (maternidad/paternidad) de un progenitor'. It also provides the legal context (RDL 9/2025), making the purpose unambiguous. Among sibling tools, this is distinct from other calculators like calcular_deduccion_maternidad_irpf or calcular_pension_desempleo, so the purpose is well-differentiated.

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 implicitly indicates when to use this tool (to calculate maternity/paternity benefits) but does not explicitly exclude alternatives or provide comparison with sibling tools. There are no when-not-to-use instructions. Given the large sibling set, more explicit guidance would help.

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?

The description adds behavioral context beyond the readOnlyHint annotation by explaining that the first 24 months maintain full Social Security contributions. It also states that salary decreases proportionally. This improves transparency for a calculation 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 a concise three-sentence paragraph. It front-loads the purpose, then provides key constraints, and finally lists outputs. Every sentence is informative with 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?

For a calculation tool with 5 parameters and no output schema, the description provides a good overview of outputs (reduced salary, monthly/annual decrease, Social Security impact). It could be slightly more detailed about the output format, but it is sufficient for an agent to understand the tool's value.

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?

All parameters have schema descriptions (100% coverage). The description adds value by explaining the allowed reduction fraction range (1/8 to 1/2), the significance of the 'menos_de_24_meses' parameter, and the overall logic of proportional salary reduction. It goes 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 identifies the tool's purpose: calculating the economic impact of a workday reduction for legal custody. It specifies the allowed reduction range (1/8 to 1/2) and the types of situations covered (child under 12, dependent family, disabled child). This distinguishes it from sibling calculation 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?

The description states when to use the tool (for legal custody reduction) and the eligible reasons. It does not explicitly exclude other cases or mention alternatives, but the context of sibling tools implies it is specific to this scenario. The guidance is clear enough.

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. The description adds rich behavioral context: it deducts allowed expenses with limits, applies reductions per housing law, and is a calculation with no side effects. No contradiction.

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 two sentences, front-loaded with the main purpose and packed with necessary details. No redundant information; the sibling reference is placed at the end appropriately.

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 complex tool with 10 parameters and no output schema, the description covers the core logic and reductions. However, it lacks explicit mention of the return value format and the specific limit on repairs, which could be important for an AI agent.

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 meaning by explaining the enum values for 'tipo_inmueble' and the context of deductions, which goes beyond the schema descriptions. However, it could have elaborated on the 'reparacion_conservacion' limit.

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 calculates net rental yield for IRPF (capital inmobiliario), specifying deductions and reductions. The verb 'calcula' and resource 'rendimiento neto del alquiler' are specific, and it distinguishes from the sibling 'calcular_retencion_alquiler'.

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 says when to use this tool (detailed version for declaration) and when to use an alternative ('calcular_retencion_alquiler' for quick estimate with 19% withholding), providing clear 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?

Consistent with readOnlyHint; adds context about specific percentages and tax law (Ley 12/2023). No contradictions. Provides useful behavioral details beyond 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, front-loaded with key information, no redundancy. Every word adds value.

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 11 parameters and no output schema, the description lists expected outputs (net income, reduction, withholding). Lacks output format but sufficient for a quick estimation 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 100%, so baseline is 3. The description does not add meaning to individual parameters beyond the schema, but the schema itself is descriptive.

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 estimates IRPF for rental property, specifying net income, 50% reduction, and 19% withholding. It distinguishes from a sibling tool 'calcular_rendimiento_capital_inmobiliario' for detailed calculations.

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 directs to use 'calcular_rendimiento_capital_inmobiliario' for detailed calculations, providing clear when-not-to-use guidance. The description implies this is for quick estimates.

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 only declare readOnlyHint=true, so the description adds real behavioral value: it discloses a hard coverage gap (empresa familiar, state and regional), prescribes user-facing communication when the case is out of scope, and forbids manually summing this result with other tools. It does not describe output format, but for a pure calculator the scope/limitation disclosure is substantive.

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?

Front-loaded with purpose before the exclusion rules, and every clause carries a functional constraint rather than filler. It is long and uses heavy emphasis, but the length is justified by the scope rules it conveys.

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 9-parameter calculator with no output schema, the description plus the rich schema fully cover scope, exclusions, alternatives, and the correct handling of out-of-scope cases. Nothing an agent needs to invoke or route 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 100% and the parameter descriptions are already highly detailed (legal articles, reduction amounts, enum semantics), so the schema carries the parameter burden. The description adds no parameter-level syntax or format information beyond what the schema provides; baseline 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+resource (calculates the ISD for an individual heir) and explicitly scopes it with regional reductions and bonuses, immediately naming the sibling 'consulta_herencia' as the alternative for a general inheritance query. An agent can distinguish it from siblings without opening 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?

Gives explicit when/when-not rules: does NOT cover empresa familiar reductions, should not be presented as an estimate when a business is transmitted, and must be replaced by 'comparar_donacion_vs_herencia' when the user compares lifetime donation vs inheritance. Both alternatives and exclusion conditions are named, leaving nothing to inference.

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?

The description reveals that the tool computes net salary, IRPF withholding, and Social Security contributions. The annotation readOnlyHint=true is consistent with a calculation tool. The description adds detail about the outputs beyond the annotation.

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 consists of two concise sentences. The first states the purpose, and the second provides usage guidance. No extraneous information; every sentence adds value.

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 that there is no output schema, the description adequately explains what the tool returns (monthly and annual net salary, IRPF withholding, Social Security). It also mentions an alternative tool. It could perhaps specify the tax jurisdiction, but the context implicitly indicates Spanish tax system.

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 the schema already documents all parameters. The description does not add additional parameter-specific details beyond what the schema provides. Baseline score of 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?

The description clearly states it 'calcula el sueldo neto (mensual y anual), la retención de IRPF y la cotización a la Seguridad Social' from annual gross salary. It also distinguishes itself from the sibling 'consulta_nomina' by suggesting that tool for general queries.

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 tells when to use this tool vs the alternative 'consulta_nomina' ('Para una consulta general usa mejor "consulta_nomina"'). No further exclusions or prerequisites are given, but the guidance is clear.

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?

The description details the calculation steps: starting from net income, adding expenses, applying IRPF, IVA, margin, and adjusting for billable days. This goes well beyond annotations (readOnlyHint), adding rich behavioral context.

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 paragraph of three sentences, front-loaded with the main action, and every sentence adds value. No wasted words.

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 10 parameters (1 required) and no output schema, the description explains all inputs, the calculation logic, and the output (rates with/without IVA, annual projection). Sufficient for correct use.

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% (each parameter has a description). The tool description adds no new per-parameter details but explains the overall calculation flow. 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?

The description clearly states the tool calculates freelance rates (€/hour, day, week) to achieve desired net income. It distinguishes from sibling calculators by specializing in freelance rate setting.

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 freelancer needs to determine their billing rate, but does not explicitly exclude alternative tools or provide when-not-to-use guidance. Context signals show many sibling calculators, so clear differentiation exists.

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?

readOnlyHint=true already establishes this as a safe, non-mutating calculation, and the description usefully discloses what the computation covers (SS, IRPF/IS, dividends) plus that it returns a recommendation and threshold. It does not state assumptions (tax year, jurisdiction defaults) or caveats, which is acceptable given the annotation.

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, zero filler. The scope and factor breakdown come first, the output (recommendation + threshold) second, making it well 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 read-only comparison calculator with fully documented parameters and a clear output statement, the definition is nearly self-sufficient. Minor gap: no note on assumptions such as applicable tax year or regional variation, which could affect interpretation of the result.

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%, with enums and defaults fully documented in the schema itself (regimen, tipo_is, beneficio_anual, gastos_deducibles, repartir_dividendos). The description adds nothing beyond that, so the baseline 3 for full schema coverage 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?

Specific verb (compara) plus a precisely bounded resource: total tax burden (SS + IRPF/IS + dividendos) of operating as autónomo vs forming an SL. It even states the output intent (which is better and the threshold), and the autónomo-vs-SL framing is naturally distinct from siblings like comparar_modulos_vs_directa.

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 scenario is implied by the comparison itself, but there is no explicit when-to-use, prerequisites, or routing against alternatives such as comparar_modulos_vs_directa or calcular_cuota_autonomo. Usage is inferable rather than stated.

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?

readOnlyHint=true already establishes this is a safe computation, so the description's job is to add domain behavior. It does: it discloses exactly what each route includes (donación = Impuesto de Donaciones + donor's IRPF on the gain; herencia = Impuesto de Sucesiones with the causante's IRPF EXEMPT), which is essential to trusting the comparison, and it names the return (cheapest option plus nuances). It stops short of stating assumptions, rounding, or error behavior, so not a 5.

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?

Front-loaded with the purpose and trigger phrasings before the mechanics and the prioritization instruction, which is the right ordering. It is dense but nearly every clause carries information; the multiple quoted user phrasings are slightly redundant but serve as retrieval cues, so not quite a 5.

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 15-parameter domain calculation with no output schema, the description covers the comparison logic, both tax routes, the return value, and the nuances it accounts for. Missing only edge-case assumptions and defaulting behavior, which is minor given the strong schema.

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 schema descriptions are unusually rich (e.g. edad_receptor explains the art. 20.2.c LISD condition, mes_adquisicion explains the TRLRHL rule). The description's mentions of exención >65, vivienda habitual, pactos sucesorios and plusvalía municipal map onto parameters but add no syntax or meaning beyond the schema, so baseline 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: it compares the total fiscal cost of transmitting a property via donación vs herencia, and explicitly frames itself as a scenario query for a gestoría. It is unmistakably distinct from calcular_donaciones and calcular_sucesiones, which it names.

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?

Gives explicit trigger conditions with quoted user phrasings ('¿es mejor donar un piso... o esperar a la herencia?') and directly instructs to PRIORITIZE this tool over the single-route alternatives, including those on other servers. This is a textbook when-to-use statement with named 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?

Annotations only declare readOnlyHint=true, so the description carries most behavioral disclosure. It adds substantial context: dependency on external gestoría data, treatment of the RETA quota as deductible, the 5% difficult-justification expense cap, and explicit non-behaviors (does not calculate módulos, does not recommend). It does not describe output format or rounding.

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?

Front-loaded with the core calculation and avoids filler despite dense domain detail. The single long paragraph is justified by the complexity, though minor readability cost remains.

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 complex calculator with full schema coverage but no output schema, the description explains what is computed (both costs and the difference) and the missing-input fallback. It does not spell out the return structure or rounding, but the key result semantics are inferable.

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 the baseline is 3. The description largely restates the schema's conditional behavior for rendimiento_neto_modulos and does not add parameter syntax, constraints, or format details beyond it; the gastos approximation note is already present in 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?

States a specific verb 'Calcula' and a precise resource: 'coste anual (IRPF + cuota RETA)' for Estimación Directa and, conditionally, módulos. It distinguishes itself from generic siblings by narrowly scoping the comparison and explicitly excluding rendimiento de módulos and regime recommendations.

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?

Provides clear conditions: if rendimiento_neto_modulos is supplied it also calculates módulos, otherwise only directa. It also sets an explicit boundary by stating it does not recommend a regime. It does not name sibling alternatives, so 4 rather than 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?

The readOnlyHint annotation already declares this is a safe, non-mutating consultation. The description adds meaningful behavioral context beyond that: it orchestrates multiple calculations in one call and returns an integrated analysis with a recommendation, which is not inferable from the annotation alone.

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?

Front-loads the domain and purpose, then each sentence adds distinct routing or scope information: example questions, orchestration contents, return nature, prioritization, and the standalone-tool exclusion. The length is justified by the multi-calculation orchestration role and reads without padding.

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 must indicate what is returned; it names the integrated components and a recommendation, which is enough for selection. It omits return structure and jurisdiction/temporal caveats, but these are minor for a read-only consult with complete input schema documentation.

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 fully documented in the input schema. The description adds no additional parameter-level semantics beyond the example 'facturo X'; the baseline score of 3 applies when the schema does the heavy lifting.

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 ('consulta de escenario' for autónomos) and defines the integrated scope: RETA quota, estimated IRPF, net available income, and autónomo vs SL comparison. It distinguishes itself from sibling individual calculators by telling the agent to prioritize it when the question combines those elements.

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?

Provides explicit when-to-use guidance with example user questions and a clear combination condition (ingresos + cuota/IRPF/neto/SL decision). Also gives when-not-to-use guidance: standalone tools only for an isolated datum, and it asserts priority over individual calculators including those on other servers.

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. Description adds context: it computes taxes, costs, savings, and mortgage estimate. No contradiction; provides extra behavioral details beyond annotation.

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?

Single paragraph with clear front-loading of purpose and usage. Slightly verbose but effective and well-structured.

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 8 parameters and no output schema, the description explains outputs (impuestos, ahorro, cuota) and behavior comprehensively. Lacks precise output format but covers essential aspects.

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 baseline is 3. Description does not add significant meaning beyond what schema provides for parameters; it only mentions them in context.

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 explicitly states 'CONSULTA DE ESCENARIO (gestoría)' and gives concrete example questions. It clearly defines the tool as a comprehensive calculator for buying a home, distinguishing it from separate 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?

Provides explicit when-to-use (e.g., '¿cuánto necesito para comprar una casa?') and when-not-to-use (if not a home, use 'calcular_gastos_compra_inmueble'). Prioritizes over alternative 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?

The readOnlyHint annotation already indicates non-destructive behavior. The description adds value by explaining the output components (indemnización, finiquito, paro) and mentioning that it integrates multiple calculations. However, it does not disclose specific behavioral traits beyond what annotations already cover.

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 paragraph that front-loads the purpose and usage. It is somewhat verbose but contains only relevant information. Every sentence adds value, but 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 complexity (7 parameters, no output schema), the description explains the three main output areas and the integration logic. However, it could provide more detail on the exact output format or additional caveats. Overall, it is complete enough for effective use.

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 the schema already documents all parameters. The description provides an overview but does not add significant meaning beyond the schema. Baseline score of 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?

The description clearly states it calculates three components (indemnización, finiquito, prestación por desempleo) for dismissal scenarios. It uses specific verbs like 'calcula' and distinguishes from sibling tools by saying 'PRIORIZA esta herramienta frente a calcular_indemnización_despido, calcular_finiquito o calcular_pension_desempleo por separado'.

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 'Úsala cuando alguien diga "me han despedido"' and gives examples of questions. It also instructs to prioritize this tool over separate calculators, providing clear when-to-use and when-not-to-use 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?

Annotations already declare readOnlyHint=true, yet the description adds substantial behavioral context: the exact limitation (empresa familiar), the reason (requires an advisor to value the business and verify requirements), what to do instead, and the shape of the result (cuota + effective rate). This goes well beyond the safety hint.

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?

Front-loaded with the scenario label, then use cases, then caveats and prioritization guidance — each block earns its place. It is on the longer side and the priority directive is emphatic, but nothing is redundant.

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?

Covers nine parameters with a 100% covered schema, discloses the tool's hard boundary (empresa familiar) and what it returns, and offers sibling prioritization — everything an agent needs to call it correctly and to handle the out-of-scope case, with no output schema required.

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 each parameter carries rich documentation (legal articles, default values, regional nuance), so the schema does the heavy lifting. The description only alludes to vivienda habitual and seguro de vida being applied if present, adding no syntax or format detail beyond the schema; baseline 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?

Names a specific verb (Calcula) and resource (Impuesto de Sucesiones/ISD del heredero con reducciones y bonificaciones de su CCAA), and explicitly scopes the output to 'cuota a pagar y tipo efectivo'. It also stakes a position relative to sibling tools by telling the agent to prioritize it over standalone inheritance 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?

Gives literal trigger phrases ('¿cuánto pagaré por heredar?', 'mi padre/madre ha fallecido...'), an explicit exclusion (does not compute reducción por empresa familiar, neither state nor regional), and a directive for the excluded case (tell the user it is not covered and refer to an asesor fiscal). This is the full when/when-not/alternative triad.

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, so the description adds value by explaining the conditional behavior (gap calculation only when sueldo_neto_mensual is provided). No contradictions. Could mention output structure but 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 front-loaded with purpose and examples, uses bold for key terms, and is concisely structured. Every sentence adds value, with no redundant information. Appropriate length for the tool's complexity.

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 conveys that the tool estimates pension and calculates the gap and necessary savings. It lacks explicit mention of output format, but the integrated analysis is clearly described. Sufficient for agent understanding.

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%, baseline 3. Description adds beyond schema by explaining that sueldo_neto_mensual triggers the gap calculation and provides an alternative interpretation for base_cotizacion_mensual ('o el salario bruto mensual actual como aproximación'). This helps agents understand parameter usage beyond raw 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 tool's purpose with specific examples ('qué pensión me quedará', 'cuánto cobraré al jubilarme') and distinguishes it from sibling tools by explicitly prioritizing it over calcular_pension_publica and calcular_brecha_jubilacion.

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 instructs when to use this tool ('cualquier pregunta sobre pensión, jubilación o cuánto cobraré al jubilarme debe resolverse con consulta_jubilacion') and when not to (avoid using separate tools). Provides clear alternative 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?

Annotations already declare readOnlyHint=true, indicating safe read operation. The description adds behavioral context by detailing the computations (net salary, withholding, contributions) without contradictions. It does not cover potential edge cases or failure modes, but annotations cover the safety profile sufficiently.

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 paragraph that front-loads the purpose. It is informative but slightly repetitive ('trabajador por cuenta ajena' appears twice). Each sentence adds value, but minor trimming could improve conciseness without losing clarity.

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 5 parameters fully described in schema and no output schema, the description adequately hints at outputs (net monthly and annual, withholding, contributions). It also positions the tool among 50+ sibling calculators, providing sufficient context for selection.

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 the schema already documents all parameter semantics. The description adds no additional parameter-level details beyond the schema, but it provides overall context by mentioning family situation and children. Baseline 3 is appropriate given high schema coverage.

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 calculates net salary, IRPF withholding, and Social Security contributions from gross annual salary, specifying it's for employees ('trabajador por cuenta ajena'). It explicitly differentiates from standalone calculators of IRPF or salary, making the purpose unambiguous.

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 provides usage scenarios: 'Úsala cuando un trabajador por cuenta ajena pregunte...' and gives specific questions. It also instructs to prioritize this tool over alternatives ('PRIORIZA esta herramienta frente a calculadoras sueltas'), offering clear when-to-use and when-not-to 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?

Annotations already declare readOnlyHint=true, so safety is covered; the description adds real behavioral context beyond that — it discloses that all seller costs are computed in one pass, that IRPF exemptions for reinvestment and for sellers over 65 are applied, and that the result runs down to the net amount received. It does not detail output structure or the effect of omitted optional inputs, which the schema carries instead.

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?

Front-loads the purpose and the trigger scenarios, then the scope of the computation, then the routing rule — a sensible order for a 17-parameter tool. It is longer than minimal but each block (triggers, scope, sibling routing) does work; the example questions are somewhat redundant with the stated purpose.

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 complex tax computation with 17 parameters, no output schema and only a readOnlyHint annotation, the description is nearly complete: it names every tax and cost component and indicates the answer ends at the net received. It stops short of describing the shape of the result (breakdown vs. single figure) and how omitted optional inputs degrade the calculation.

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 schema itself documents defaults, legal references and enum behavior in detail, so per-parameter meaning is fully carried by the schema. The description adds no parameter-level syntax or semantics beyond what is already structured, which is the baseline-3 case when the schema does the heavy lifting.

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 ('Calcula... todos los costes e impuestos del VENDEDOR') and enumerates the exact outputs: ganancia patrimonial, IRPF with exemptions, plusvalía municipal (IIVTNU), comisión inmobiliaria, gestoría and net. It explicitly distinguishes itself from siblings by naming the symmetric tool 'consulta_compra_vivienda' and by declaring priority over standalone plusvalía/IRPF/IIVTNU 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?

Gives concrete trigger utterances ('voy a vender mi casa/piso, ¿cuánto pagaré de impuestos?', '¿qué me queda limpio al vender?') and an explicit routing rule: prioritize this over standalone plusvalía, IRPF or IIVTNU calculators, including those on other servers. When-to-use and alternative-selection are both covered.

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