Conversor IAE-CNAE

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

Annotations already indicate readOnlyHint=true, so the description adds minimal behavioral context. It includes 'Sin clave' (no key), hinting at authentication requirements, but does not elaborate on other behaviors.

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 extremely concise with two sentences, no wasted words, and directly states the core 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?

Despite having 4 parameters and no output schema, the description fails to explain parameters, return values, or usage details, making it incomplete for effective tool selection and 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 description coverage is 0%, and the tool description provides no explanation of parameters (q, type, top_k, threshold). The agent gains no additional meaning beyond the 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 searches for IAE/CNAE codes by description using semantic search, which is specific and distinct from sibling tools that retrieve details by code.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like detalle_cnae or detalle_iae. The description only explains what it does, not 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 annotations already declare readOnlyHint=true, so the description's job is lighter. It adds that the tool returns specific fields (number, asunto, criterio, enlace) and that it searches 'por tema o texto', which provides additional context beyond the annotation without contradicting it.

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) and front-loaded with the core purpose. It could be slightly more structured but is efficient, with 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 no output schema, the description explains what the tool returns (number, asunto, criterio, enlace) and mentions it searches by topic or text. It lacks details on pagination or rate limits, but for a simple search tool with read-only annotation, it is sufficiently 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?

With 0% schema description coverage, the description needed to compensate. It explains the 'query' parameter as searching 'por tema o texto', which adds meaning, but the 'limit' parameter is not described at all, leaving its purpose unclear. The description is incomplete for both parameters.

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 the tool searches for TEAC resolutions and criteria by topic or text, listing specific tax areas (IVA, IRPF, etc.) and return fields (number, subject, criteria, link). It clearly distinguishes itself from siblings like buscar_codigo (search code) and calendario_fiscal (fiscal calendar) which serve different purposes.

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 does not explicitly state when to use this tool versus alternatives or when not to use it. It implies usage for TEAC doctrine searches via 'por tema o texto' and 'Sin clave' (without key) suggests no authentication, but no direct guidance on context 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?

Annotations indicate readOnlyHint=true, so the tool is read-only. The description adds 'Sin clave' (without key), implying no authentication is needed, but this is vague. No behavioral traits beyond what annotations provide are disclosed. 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, front-loaded sentence. It is concise with no wasted words. However, it is so brief that some necessary information is omitted, making it less effective than a slightly longer but more complete description.

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 (2 params, no nested objects, no output schema) and the presence of sibling tools, the description is minimally complete. It names the output 'Modelos AEAT y próximos plazos' but lacks details on format, pagination, or error cases. The agent may need to infer the response structure.

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 0%, the description must compensate. It mentions 'código IAE/CNAE', hinting that the 'code' parameter is such a code, and implies 'code_type' exists via the mention of 'IAE/CNAE'. However, it does not explain the default value, the pattern, or the optional nature. The agent may struggle to construct valid input.

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 provides AEAT models and upcoming deadlines for a given IAE/CNAE code. It identifies the resource (calendario fiscal) and the action (retrieve deadlines). However, it does not differentiate it from sibling tools like 'obligaciones_fiscales', which may overlap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives. The description does not mention prerequisites, limitations, or scenarios where this tool is preferred. The agent must infer usage from the name alone.

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 annotation indicates no destructive behavior; description confirms read-only nature and adds details about public doctrine, no personal data, and different responses based on authentication. This 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?

Description is succinct but somewhat disjointed, with multiple separate statements about free/paid tiers and a trailing 'Sin clave.' It front-loads the purpose but could be better structured for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple search tool with 2 parameters and no output schema, the description fully explains behavior, restrictions, auth requirements, and result differences between tiers. No gaps remain.

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 covers both parameters with descriptions; description adds critical context: query uses Spanish free text with stemming/accents, and code is an IAE code with dots available only in paid plan. This enriches schema 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?

Description clearly states it searches binding DGT queries by free text in Spanish, distinguishing free and paid tiers. It identifies the resource and verb, but does not explicitly differentiate from sibling search tools like buscar_codigo or buscar_doctrina_teac.

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 context on when to use the free vs. paid version (with API key), including the limitation of results without key. However, it does not address when to avoid this tool in favor of 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 provide readOnlyHint=true. The description adds the batch size limit ('Hasta 50 fichas') and authentication requirement, enhancing transparency without contradicting 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 the core function, no redundant words. Every sentence provides critical information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (2 simple params, no output schema), the description covers purpose, constraints, and auth. It is missing explicit mention of return format or error handling, but these are not critical for basic 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?

With 0% schema description coverage, the description should compensate, but it only hints at the 'type' parameter ('IAE o CNAE') and does not explain the 'codes' parameter beyond its existence. The schema provides the structure, but the description adds minimal 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 it performs a batch query of up to 50 IAE or CNAE records in one call. This distinguishes it from sibling tools like 'detalle_iae' and 'detalle_cnae' which handle single records.

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 specifies the requirement of a payment key ('Solo con clave de pago') and the batch limit, implying it's for bulk queries. However, it does not explicitly state when to use this tool versus individual lookup 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?

Discloses read-only nature (matches annotation readOnlyHint=true), public data, no authentication needed ('Sin clave'), and calculation method. No contradictions 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?

Extremely concise: two sentences with no redundancy. Every word adds value: operation, scope, exclusions, data source, auth status.

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?

Lacks output format description (no output schema), and parameter details are minimal. Adequate for simple tool but incomplete for full 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 0%, so description must compensate. Only 'base' is implied by 'base liquidable'. No explanation for 'anio' or 'escala' despite defaults and enum. Limited value beyond 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?

Description clearly states verb 'calcula' and resource 'cuota íntegra ESTATAL del IRPF', specifies marginal sum method, and distinguishes from autonomous scale and minimums. Sibling tools like 'escala_irpf' and 'cuota_reta' are 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?

Explicitly states what it does and what it excludes (autonomous scale, minimums), implying when not to use. Could mention alternatives like 'escala_irpf' for scale details, but overall clear 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 declare readOnlyHint=true, so the tool is safe. The description adds 'datos públicos, sin clave' indicating no authentication required. However, it does not disclose that results are estimates, or that the calculation is based on a specific year (only the title mentions 2026). With annotations providing safety, the description adds some context but not rich behavioral details.

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 very concise (two sentences), but this conciseness comes at the cost of missing essential parameter and usage details. Every sentence is functional, but the brevity leaves gaps that harm overall 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?

Given 3 parameters, no output schema, and sibling tools, the description is too minimal. It lacks explanation of the output format, how parameters affect the calculation, and the year of rates. A calculator tool with multiple configurable options should provide more context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% – no parameter descriptions exist in the schema. The description fails to compensate: it only mentions 'rendimiento neto' (neto parameter) but does not explain 'anio' (year) or 'tabla' (general/reduced table). For a tool with 3 parameters, this is inadequate.

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 bracket and minimum estimated fee for self-employed (RETA) based on net income. It mentions public data and no key needed. However, it does not explicitly differentiate from sibling tools like cuota_irpf, though the RETA focus is distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The context is implied (calculating RETA quota) but no exclusions or comparisons are provided. Given sibling tools like cuota_irpf and escalas_irpf, the description should mention when to prefer this 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?

Annotations already indicate readOnlyHint=true. The description adds that no key is required and mentions data freshness, providing useful 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?

The description is a single sentence with no wasted words. It is front-loaded with the core 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?

Given zero parameters, no output schema, and a simple self-descriptive purpose, the description fully covers what the tool does and what it returns.

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?

There are no parameters (schema coverage 100% trivial). The description explains the tool's purpose, which serves as sufficient semantic context for an inputless tool.

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 is a self-description of the service covering catalogs, RPCs, and data freshness. This distinguishes it from sibling tools focused on specific tax/code lookups.

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 (get metadata about the service), but there is no explicit guidance on when to use this vs alternatives or conditions like authentication.

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, and the description adds that basic access is free while advanced features (correspondence with IAE, CNAE 2009, enrichment) require a key. This provides behavioral context beyond the annotation, such as tiered access and what is included in the basic result.

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. The first sentence clearly states the tool's purpose and key fields, and the second sentence covers access conditions. It is front-loaded and efficient, though it could be slightly more 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 the tool's low complexity (one parameter, no output schema), the description is fairly complete. It covers the purpose, available fields, and access tiers. However, it does not describe the return format or typical usage scenarios, which would be helpful for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not explain the single 'code' parameter beyond implying it is a CNAE code. With 0% schema description coverage, the description should compensate, but it only mentions 'un código CNAE 2025' without detailing the format or meaning. The schema's pattern is present but the description adds no semantic value.

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 provides a card for a CNAE 2025 code, listing fields like title, description, category, and sector. It distinguishes from the sibling tool 'detalle_cnae_2009' by specifying the 2025 version.

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 mentions free access without key and that advanced features require a Professional key, which implies usage conditions. However, it does not explicitly state when to use this tool versus alternatives like 'buscar_codigo' or 'detalle_cnae_2009', nor does it provide 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. The description adds behavioral context: free access and that mapping to new codes requires a key. 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 are efficient and front-loaded with the core purpose. 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 description covers purpose, access, and mapping limitation. For a simple detail fetch with one parameter and no output schema, this is nearly complete. Could mention output format or error cases, but not essential.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no description for the 'code' parameter. The description does not explain what the parameter represents or its format beyond the pattern. With 0% schema coverage, the description should compensate but fails to do so.

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 provides details (ficha) for a CNAE 2009 code and that it is obsolete. This differentiates it from sibling 'detalle_cnae' which presumably handles the current version, though not explicitly.

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 mentions free access without key and that correspondence to CNAE 2025 requires a key, giving context on when to use this tool. However, it does not explicitly recommend alternatives like 'detalle_cnae' for current codes.

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, and description reinforces free access without key. Adds behavioral context: enrichments require key, qualified codes disambiguate sections, exceeding annotation-only information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each serving a clear purpose: core function, access conditions, code qualification. No redundant 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?

Complete for a simple tool with one parameter: covers purpose, free vs. paid access, and input nuances. No output schema but description sufficiently prepares agent for 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?

Only one parameter 'code' with pattern in schema. Description adds meaning by giving example format (B831) and explaining its role in disambiguation, covering additional semantics beyond pattern.

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 it provides a fact sheet for an IAE epigraph (title, description, modules eligibility). Verb 'detalle' matches resource. Distinguishes from siblings like 'detalle_cnae' by specifying IAE.

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 context on free access, key requirements for enrichments, and use of qualified codes for disambiguation. Does not explicitly mention when not to use or 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?

Annotations already mark the tool as read-only (readOnlyHint=true). The description adds behavioral context beyond annotations: it clarifies that no personal data is involved (Ley 37/2007) and that the output sample size varies based on key presence. This is useful additional transparency 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 concise: three sentences, each providing essential information. The first sentence defines purpose and outputs, the second adds legal context, and the third explains key behavior. No extraneous 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 covers the main aspects: input (CNAE code), output (various statistics), and key-based behavior. However, it lacks explicit details on the output structure (e.g., exact field names for count, capital stats, provinces, monthly trend). Since there is no output schema, this would be helpful for an agent to understand the response format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description does not add information beyond the schema. The schema already describes the 'code' parameter as a CNAE-2025 code with example '6820'. The description merely reiterates that it accepts such a code, so no added value beyond 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 returns statistics of company incorporations (count, average/median capital, monthly trend, provinces) for a specific CNAE-2025 code. This is a precise verb+resource combination that distinguishes it from siblings like 'detalle_cnae', which likely provides CNAE details rather than incorporation statistics.

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 key usage: without a professional key, only a sample of 3 recent incorporations is returned; with the key, the full list of recent constitutions is available. However, it does not explicitly compare to sibling tools, leaving some ambiguity for when to use this tool versus others like 'detalle_cnae'.

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 benefits from that baseline. The description adds 'public data' and 'sin clave', clarifying no authentication is needed, which is useful context. However, it does not describe potential rate limits or data freshness, which is acceptable for a simple data retrieval 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 single sentence that front-loads the key information: what data is returned, the year, and the type of scale. It is concise with no wasted words. However, it could be slightly more structured to improve readability for an agent.

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 (2 optional parameters, no output schema, read-only), the description covers the core function. However, it does not describe the return format or structure of the data, which would be helpful since there is no output schema. The description is minimally complete but could be more informative.

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?

Input schema has 0% description coverage for parameters, so the description must compensate. The description mentions 'año 2026' and 'general o ahorro', which partially maps to the two parameters (anio and escala). However, it does not explain the meaning of the parameters beyond their names and enum values, which are somewhat self-explanatory but not fully disambiguated for an AI agent unfamiliar with Spanish tax terminology.

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 returns brackets of the state IRPF scale for general or savings income for the year 2026. It specifies 'public data' and 'no key needed', making the scope clear. However, it does not explicitly differentiate from sibling tools like 'cuota_irpf' or 'gastos_deducibles'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as 'cuota_irpf' or 'calendario_fiscal'. The description implies use for retrieving tax brackets but does not provide context on prerequisites, other tools covering related concepts, or when not to use it.

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?

Beyond the readOnlyHint annotation, the description adds that the data is public and requires no API key. This is valuable behavioral context. However, it omits pagination, rate limits, or result format.

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, front-loaded sentence with no filler. Every word adds value, efficiently conveying purpose, scope, and access constraints.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with no required fields and no output schema, the description covers the essential inputs and access model. However, it lacks any indication of the output format (e.g., list of items, total amounts), leaving some ambiguity for the 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?

The description explains 'todos o por categoría', which directly maps to the 'categoria' parameter. However, the 'anio' parameter is not explicitly discussed; its purpose is only implied by IRPF context. With 0% schema coverage, this partial compensation is adequate.

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 returns deductible expenses for self-employed IRPF, either all or by category, and notes it's public data without authentication. This verb and resource combination is 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 provides context (public data, no key) but does not explicitly compare to sibling tools like 'cuota_irpf' or 'modulos_irpf_iva'. An agent can infer usage from the 'deducibles' keyword, but no when-not guidance is given.

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 annotations already declare readOnlyHint=true, and the description adds behavioral context: 'Datos públicos. Sin clave.' This clarifies that no authentication is required and data is public, which goes 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 three concise sentences with no redundancy. It front-loads the purpose and adds param context and access info. Slightly more structure could improve scanability, but it's efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only tool with no output schema, the description covers purpose, key parameter (slug), access (public, no key), and data source (IAE). It omits return value details, but given the tool's simplicity, it is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the slug parameter's purpose ('para desambiguar códigos con varias actividades') and implies the code is an IAE code. However, it does not fully describe the code format or the role of slug beyond disambiguation.

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: 'Régimen de estimación objetiva (módulos) de un IAE' (objective estimation regime/modules of an IAE code). It distinguishes from siblings like 'detalle_iae' by specifying it's for the module regime, and mentions optional disambiguation via slug.

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 querying public data on IAE modules and notes that no key is needed ('Sin clave'), but it does not explicitly state when to use this tool over alternatives like 'detalle_iae' or provide guidance on when not to use it.

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 that data is public and no key is required ('Datos públicos. Sin clave.'), which provides useful behavioral context beyond the annotation. However, it does not disclose other traits like rate limits or pagination.

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 very short (one sentence) and front-loads the core purpose, but it lacks structure such as separating parameter details or usage context. It is concise but at the expense of completeness.

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 is simple (2 params, no output schema), the description covers the basic return types and data publicity. However, it omits parameter semantics and does not fully compensate for the lack of schema descriptions or output 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 description coverage is 0%, yet the description provides no explanation of the two parameters (code and code_type). It only mentions 'un código' without defining valid values, formats, or the role of code_type. This is a major gap for a tool requiring parameter input.

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 returns 'Modelos AEAT' applicable to a code, mentioning specific output fields (confianza, motivo, periodicidad, plazo). The verb 'aplicables' implies retrieval. It distinguishes from siblings by specifying a unique resource (AEAT models for a code), though not explicitly contrasting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'buscar_codigo' or 'consulta_dgt'. The description does not mention prerequisites, contexts, or when to avoid using it.

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 annotations set readOnlyHint=true, and the description adds behavioral details beyond that: it returns only open calls, includes a sample, and mentions a payment plan and filter. It also clarifies the data scope ('sin datos personales'). 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 well-structured with front-loaded purpose and list of outputs. It is concise but includes unnecessary phrases like 'Sin clave' and the ambiguous 'Con plan de pago: lista completa y filtro solo_actividad.' Still, it is efficient overall.

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 2 parameters and no output schema, the description provides a reasonable overview of the response structure (counts and sample fields). It covers data limitations (only open calls, no personal data). The 'plan de pago' mention could be clarified, but overall it is sufficiently complete for a simple query tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description does not add new information about the parameters beyond what the schema already provides. The description of 'solo_actividad' in the text is identical to the schema description. The mention of 'plan de pago' refers to output, not parameters.

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 returns open public subsidies for a CNAE code, specifying the output includes total count, counts for autonomous/SMEs, and a sample with title, body, scope, endowment, official link. It uses a specific verb 'Devuelve' and distinguishes itself from siblings like 'detalle_cnae' or 'empresas_por_actividad' by focusing on subsidies.

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 context by stating 'Solo convocatorias públicas, sin datos personales. Sin clave.', but it does not explicitly state when to use this tool versus alternative tools. There is no 'when-not-to-use' guidance or reference to sibling tools.

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

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

The description discloses that the free part returns total rate + application note, while the detailed breakdown requires a payment key (Authorization: Bearer cvr_…). It also notes that autónomos pay a different rate. This adds value beyond the readOnlyHint annotation, which only indicates no side effects.

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 two main sentences: one stating the purpose, the other explaining free vs paid features. It is front-loaded with the core function, and every phrase 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?

Given the tool has only one parameter and no output schema, the description fully explains what the free and paid responses contain, including an example for autónomos. It is complete for an agent to understand what to expect.

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 only parameter 'code' is covered 100% by the schema. The description provides an example (6820) and notes that dots are optional, but this does not add significant meaning beyond the schema's pattern and description. 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 verb (obtener/consultar tarifa AT/EP) and resource (actividad CNAE-2025), and distinguishes it from sibling tools like 'detalle_cnae' or 'cuota_irpf' by focusing specifically on accident and occupational disease rates.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: it's for getting AT/EP rates by CNAE, with free vs paid tiers. However, it does not explicitly state when not to use it or suggest alternatives, though the free/paid distinction implies when to upgrade.

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 does not need to repeat that. It adds context by specifying 'Solo texto en vigor (no histórico)' and 'citable como fuente oficial', but introduces ambiguity with 'Sin clave. Con clave: hechos + texto completo' since no 'clave' parameter exists in the 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?

The description is somewhat fragmented with a mix of phrases and full sentences. It front-loads the core purpose but could be more structured. The mention of 'Sin clave. Con clave.' is unclear and adds unnecessary clutter.

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?

Without an output schema, the description does explain return values (norma, rango, estado, etc.) and special case for missing article. However, it omits details on error handling, invalid IDs, and the ambiguous 'clave' reference reduces clarity. It is adequate but not thorough.

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, but the description adds significant value by explaining the effect of omitting the 'articulo' parameter (returns index) and listing what fields are returned when it is provided. This goes beyond the schema's simple field 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 returns consolidated and current text of a BOE article, including norm, range, status, legal text, date, and link. It also specifies behavior when no article is given (returns index). This distinguishes it from sibling tools like 'buscar_codigo' or 'consulta_dgt' which deal with different legal sources.

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 that the tool returns only current text (no historical) and that it is citable as official. It implies usage for retrieving current BOE articles but does not explicitly state when to avoid using it or mention specific alternatives among siblings.

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