Calcula la retencion MENSUAL de ISR de salarios (Art. 96 LISR) menos el subsidio al empleo vigente (DOF 2025). Determinista. Devuelve ISR de tarifa, subsidio aplicado y retencion final. Informativo, no asesoria fiscal.
| Name | Required | Description | Default |
|---|---|---|---|
| ingreso_gravado | Yes | Ingreso gravado del mes (base de retencion), en pesos. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds value by stating the tool is deterministic, listing the returned values (ISR tariff, subsidy, final withholding), and including a disclaimer ('Informativo, no asesoria fiscal'). 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 concise, front-loaded with the main action, and every sentence adds value: calculation type, legal basis, determinism, output, and disclaimer. 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?
The tool has a simple input (one number) and no output schema. The description adequately explains the output (three values) and provides legal context and a disclaimer, making it complete for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing complete parameter semantics. The description does not add additional meaning beyond what the schema already 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?
The description clearly states that the tool calculates the monthly ISR withholding on salaries (Art. 96 LISR) minus the current employment subsidy, and returns three specific values. It distinguishes from siblings like fiscal_isr_estimado by specifying 'MENSUAL' and 'salarios'.
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 guides usage by specifying monthly salary withholding, but does not explicitly list when not to use or provide alternatives among siblings. The context is clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct fiscal or labor calculation (aguinaldo, CFDI validation, IMSS, ISR estimation, etc.) with no overlap. The descriptions clearly differentiate their purposes.
All tools follow a consistent 'fiscal_<noun>' pattern, using snake_case and clear, domain-specific nouns (e.g., fiscal_aguinaldo, fiscal_isr_retencion). No deviation.
10 tools cover the essential calculations for Mexican fiscal and payroll management (aguinaldo, finiquito, IMSS, ISR, CFDI, etc.) without being excessive or insufficient.
The set covers major tax and labor calculations but lacks a few common tools like PTU (profit sharing) or IVA (VAT) handling. However, it is fairly comprehensive for its stated scope.