fisco-it

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds transparency by stating 'Gratis (€0), deterministico, nessun login richiesto', which are behavioral traits not covered by 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 followed by a short phrase, front-loaded with the main action. 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?

With 7 parameters and no output schema, the description identifies what is calculated (imposta e contributi) but does not specify return format or additional details like calculation constraints. Adequate but not 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 100%, so the schema already documents all parameters. The description only mentions 'fatturato e (opzionale) codice ATECO', which is already in the schema, adding no extra 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 'Calcola imposta sostitutiva e contributi INPS del regime forfettario italiano' using a specific verb and resource. It distinguishes from sibling tools like calc_imu and calc_iva.

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 Italian flat-rate tax calculation but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives. It does note it's free, deterministic, and no login required.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds that the tool is free, deterministic, and requires no login—useful context beyond annotations. 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?

Three sentences, no redundancy. Front-loaded with main purpose. Every sentence adds distinct value (what, how, operational 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?

Despite many parameters and no output schema, the description provides a high-level overview but lacks details on output format (e.g., whether it returns tax due, breakdown, or just summary). Could be more 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 covers all 11 parameters with descriptions. The description adds high-level context by mapping parameter categories to property types (e.g., rendita catastale for buildings), improving selection reasoning for the agent.

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 Italian IMU tax (L.160/2019) for three property types, using specific inputs. It distinguishes itself from sibling tools (none are IMU-related) with a specific verb and resource.

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 when to use the tool (for IMU calculation on buildings, agricultural land, developable areas) and implies exclusivity among siblings. It lacks explicit ‘when not to use’ or alternatives, but is clear enough for 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 already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable context: the tool is free, deterministic, requires no login, and explicitly explains how the two taxable bases are calculated (contributo integrativo vs rivalsa INPS). 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 a single paragraph that efficiently conveys all key aspects: purpose, rates, withholding, regimes, special bases. Every sentence is necessary and informative, 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 the complexity of 7 parameters and no output schema, the description provides sufficient context about what the tool returns (exposing base_iva and base_ritenuta separately) and its deterministic, cost-free nature.

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 meaning by explaining the interplay between parameters (e.g., contributo integrativo enters IVA base but not withholding base), which goes beyond the schema's per-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 the tool calculates Italian VAT with specific rates, optional withholding, and handles different tax regimes. It distinguishes between two taxable bases, making its purpose distinct from sibling tools like calc_forfettario or calc_imu.

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 when to use this tool (for Italian VAT calculations with complex scenarios). It does not explicitly state when not to use it or name alternatives, but the context is clear given sibling tool names.

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, destructiveHint=false, and idempotentHint=true, indicating safe, non-destructive, idempotent behavior. The description adds context: 'Gratis (€0), deterministico, nessun login richiesto.' This provides additional useful behavioral traits beyond annotations. 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 relatively long but well-structured with clear sections. It is front-loaded with the main purpose and then details about components, composability, and limitations. Each sentence adds value, though some redundancy exists (e.g., restating 'NON genera il modello ministeriale'). Still efficient for the 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 tool's complexity (two modes, nested objects) and lack of output schema, the description fully covers the return format: 'righe strutturate (sezione, codice, anno, importo, scadenza indicativa) + una resa testuale.' It also explains the non-official nature and additional context like cost, determinism, and no login. Complete for an agent to understand 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 description coverage is 100% with detailed property descriptions. The description adds value by explaining the relationships between parameters (e.g., forfettario.imposta from calc_forfettario) and clarifying that input comes from specific sibling tools. This goes beyond the schema descriptions, which already provide good definitions.

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 composes rows of the F24 form for specific sections (Erario, INPS, IMU) using official codes and causes. It distinguishes itself from sibling tools (calc_forfettario, calc_imu) by noting it takes their outputs as input. It also explicitly states what it does not do (generate official form, PDF, or facsimile).

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 notes when to use the tool: 'l'input tipico sono gli output di calc_forfettario... e calc_imu'. It also clearly states it is an indicative compilation, not a substitute for a commercialista or verification at Agenzia delle Entrate. This guides the agent on appropriate use and limitations.

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, idempotent, and non-destructive. The description adds value by noting it is deterministic, free, requires no login, and explains the homocodic variant is assigned by the Agenzia.

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 but lacks structural elements like bullet points. It is a single paragraph that conveys all needed info, though slightly dense.

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 return is the 'base' CF but does not specify format or length. Error cases or edge conditions are not covered, but for a simple tool it is adequate.

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 individual parameter descriptions. The description adds context, such as the alternative between comune and codice_belfiore, and the role of provincia for 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 explicitly states it generates an Italian Codice Fiscale from personal data, listing required fields and alternatives. It clearly distinguishes from sibling tools like validate_codice_fiscale.

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 (to generate a CF) and what is returned (base CF). While it lacks explicit exclusions, it is clear for its purpose and does not mislead.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the tool is known to be safe. The description adds critical behavioral context: it doesn't generate the telematic file (explicit limitation), has no silent defaults (errors on missing required data), validates offline, and includes disclaimers. 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 relatively long but well-structured, with the main purpose first, followed by details, warnings, and usage advice. Every sentence adds value, though it could be slightly more concise without losing essential 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 tool's complexity and the lack of an output schema, the description fully covers what the tool returns (populated sections, totals, deadline, textual control statement), its limitations, and prerequisites. It also references sibling tools for related tasks, making the overall context 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 100%, so the schema already documents all parameters. The description does not add parameter-level meaning beyond the schema; it focuses on overall behavior. Baseline 3 is appropriate as the description doesn't compensate further.

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 composes and validates INTRASTAT summary sections from operation lines, assigning each line to the correct section. It uses specific verbs ('compone', 'validando') and resources ('SEZIONI dell'elenco riepilogativo INTRASTAT'), and distinguishes from siblings like intrastat_periodicity and verify_payee.

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

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

The description explicitly advises when to use this tool ('determina prima la periodicità con intrastat_periodicity'), when not to use it (does not generate the telematic file, use verify_payee for live VIES verification), and provides context about the tool's limits (max 25 rows on anonymous surface). It gives clear guidance on 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 readOnly, idempotent, non-destructive. The description adds valuable behavioral context: deterministic, free, no login required, indicative nature, and detailed logic (thresholds, asymmetry, normative sources). This exceeds what 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 verbose, containing multiple paragraphs and specific legal references. While informative, it could be more concise. The main purpose is front-loaded, but the density may hinder quick parsing by an AI 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 complexity (multiple thresholds, criteria, law references) and no output schema, the description is quite complete. It explains the logic, asymmetry, and normative sources, and hints at return values (periodicity, deadline, notes). Some output expectations could be clearer.

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 100% coverage with detailed descriptions for all 5 parameters. The description reiterates some threshold values but does not add significant new 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 the tool's purpose: determine INTRASTAT periodicity and deadline based on previous quarters. It distinguishes from sibling tools like intrastat_compose and intrastat_reference by focusing specifically on periodicity calculation.

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 determining INTRASTAT filing periodicity and deadline, but provides no explicit guidance on when to use this tool versus alternatives like intrastat_compose or intrastat_reference. No exclusions or prerequisites 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 provide readOnlyHint: true, idempotentHint: true, destructiveHint: false. The description adds that it's gratis, deterministic, and requires no login. It also details exactly what is returned and what is excluded. 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 somewhat long but front-loaded with the most important purpose. Every sentence adds unique value, though it could be slightly trimmed 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?

Given zero parameters and no output schema, the description is remarkably complete. It covers all returned information types, includes specific values, and explicitly states what the tool does not provide, leaving no 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 tool has zero parameters and schema coverage is 100%. The description excels by explaining that no input is needed and precisely describes the rich output content, including specific examples like the €2,000,000 threshold and Northern Ireland code.

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 starts with a clear verb 'Restituisce' (returns) and specifies the exact content: reference tables, member states with codes, thresholds with amounts and sources. It explicitly distinguishes from sibling tools like `intrastat_compose` and `intrastat_periodicity`.

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 usage scenarios: 'Usalo per validare gli input prima di intrastat_compose, per popolare un form, o per citare la fonte di una soglia invece di ricordarla a memoria.' It also lists what the tool does NOT produce, helping avoid misuse.

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, idempotentHint, and destructiveHint=false. The description adds that it's free, deterministic, and requires no login, which are useful but not critical beyond the annotations. It does not describe error behavior for invalid codes.

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 no extraneous information. It is front-loaded with the core action and efficiently adds context about cost, determinism, and authentication.

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, the description covers the main functionality: what it does, input, and output (returning activity description). It lacks explicit mention of error handling for invalid codes, but overall it is adequately complete for a read-only lookup.

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 covers the single parameter 'code' with a description, pattern, and maxLength. The description does not add new information about the parameter beyond the schema, so the baseline 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 searches and validates an ATECO 2007 ISTAT code and returns the activity description. It uses specific verbs ('cerca e valida') and a specific resource (codice ATECO), and the purpose is distinct from sibling tools like lookup_cap.

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 ATECO code lookups, which is clear from the naming and context. However, it does not explicitly state when not to use this tool or mention alternatives, though the sibling list makes differentiation straightforward.

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?

While annotations provide readOnlyHint, destructiveHint, etc., the description adds valuable behavioral traits: free cost, deterministic behavior, no authentication needed, and the approximate nature based on 2-digit prefix.

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 wasted words. It front-loads the purpose and includes limitations efficiently.

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 simplicity of the tool (single parameter, no output schema), the description is fully complete: it explains what, how, limitations, and access conditions.

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

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

The schema covers the parameter with description. The description adds meaning by explaining the lookup logic (based on 2-digit prefix) and the format example, providing context 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 returns the indicative area/province of an Italian CAP based on the 2-digit prefix, not the exact town. It also notes limitations, making the purpose distinct from sibling tools like lookup_ateco.

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 usage context: free, deterministic, no login required, and mentions approximation and imprecision for certain cases. It doesn't explicitly exclude alternatives, but no sibling tool covers CAP lookup.

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 states the tool is deterministic, free, requires no login, and does not perform VIES verification. The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description complements these 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 with two sentences, each carrying important information: the first defines the purpose and outputs, the second clarifies limitations and features. No superfluous content.

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

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

For a simple tool with one parameter and no output schema, the description is complete. It covers what the tool does, its behavior (deterministic, free, no login), and what it does not do (no VIES verification), which is sufficient for an agent to select and invoke 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?

The schema covers 100% of parameters (one parameter, xml_content, with a description). The tool description does not add additional semantic detail 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?

The description clearly specifies the verb ('Estrae' / extracts), the resource (XML FatturaPA/SDI), and the data extracted (cedente, cessionario, righe, imposte). It also distinguishes itself from a sibling by stating 'nessuna verifica VIES', 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 indicates when to use this tool (for deterministic parsing, no VIES verification needed) and mentions it is free, deterministic, and requires no login. Although it does not explicitly list exclusions, the context of sibling tools (especially parse_verify_fatturapa) provides implicit guidance for 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?

Details deterministic extraction (not LLM), checksums for IBAN, P.IVA, CF, VIES live check, honest degradation when VIES down, red flag disclosures. Annotations (readOnly, idempotent, non-destructive) are consistent and description adds significant 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?

Description is verbose but every sentence adds value. Front-loaded with core purpose, then details. Slightly long but well-structured and not wasteful.

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 complexity (3 params, no output schema, 17 siblings), description covers extraction, verification steps, fallback behavior, cost (free), and comparison to sibling. Missing only potential rate limits, but maxLength and no-login hint at generous 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 description coverage is 100%, but description adds nuance: party default cedente because it's anti-fraud case, IBAN collected only for cedente, xml_content note about .p7m, expected_country default IT with fraud indicator explanation. Adds meaning 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 it extracts structured data from an XML FatturaPA/SDI and performs anti-fraud verification on the supplier. It distinguishes from siblings like parse_fatturapa (parse only) and verify_payee (verification only) by combining both actions.

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 (defense against IBAN change fraud on passive invoices) and when not (does not replace out-of-band verification). Compares to sibling verify_payee, noting VIES query behavior.

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 read-only, idempotent, non-destructive behavior. The description adds value by stating determinism and no login requirement, providing helpful 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 concise sentences: one states the function, the other lists key attributes. No redundant 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?

The tool has one parameter, schema covers it, and annotations cover safety. However, the description does not specify the return value (e.g., boolean or detailed result), which is a gap for a validation function without an 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?

With 100% schema coverage, the description adds no extra meaning beyond the schema's parameter description and example. 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 validates Italian tax code format and control character with omocodia handling, distinguishing it from sibling tools like generate_codice_fiscale or validate_partita_iva.

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 includes practical guidance (free, deterministic, no login), making it clear when to use this tool. It does not explicitly mention when not to use alternatives, but the usage context is well implied.

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, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: it is free (€0), deterministic, requires no login, and for Italian IBANs it identifies the bank from ABI code. 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 consists of two short sentences, delivering core functionality and key traits without extraneous text. Every sentence is informative and 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?

The tool has no output schema, so the description should explain what the tool returns. It mentions validation and bank identification but does not specify whether the output is a boolean, a structured result, or an error message. This gap reduces completeness.

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

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

Schema description coverage is 100%, giving a baseline of 3. The parameter 'iban' has a schema description with an example. The tool description does not add new semantic information about the parameter beyond what the schema provides, though it contextualizes the validation process.

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 validates an IBAN using checksum MOD-97 and, for Italian IBANs, identifies the bank from the ABI code. This specific verb+resource combination distinguishes it from sibling validation tools like validate_codice_fiscale or validate_partita_iva.

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 notes that the tool is free, deterministic, and requires no login, implying it can be safely called without side effects. However, it does not explicitly state when not to use it or compare against alternatives, though sibling tools target different codes so there is little ambiguity.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description adds value by noting the tool is free, deterministic, and requires no login. No contradictions; the description reinforces and extends the behavioral profile.

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—two short sentences that immediately convey the tool's purpose, constraints, and key characteristics. No filler; every word 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?

The description covers the tool's core function and constraints but does not explain what the validation returns (e.g., boolean true/false, error details). Since there is no output schema, the description leaves ambiguity about the result format, which is a gap for a validation 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?

With 100% schema description coverage, the parameter already has a description. The tool description adds concrete format details (11 digits + Luhn checksum) and an example, providing 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?

Description clearly states the tool validates an Italian Partita IVA, specifying it is 11 digits with Luhn checksum. The title and description directly align, and the tool distinguishes itself from sibling validation tools (e.g., validate_codice_fiscale, validate_iban) by targeting a specific entity.

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 (free, deterministic, no login), which helps an agent decide when to use it. However, it does not explicitly mention when not to use it or suggest alternatives, though sibling tools imply different validation targets.

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, idempotentHint=true, and destructiveHint=false. The description adds valuable context: the tool is free, deterministic, and requires no login. This goes beyond the annotations and is not contradictory.

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 that front-load the core functionality and then add cost and behavior details. Every sentence earns its place 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?

For a simple one-parameter tool with no output schema, the description adequately explains what the tool does (format + domain validation) and mentions the output includes a confidence level. It could mention error handling or explicit output structure, but it is sufficient for an agent to understand and invoke the 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?

With 100% schema description coverage for the single parameter 'email', the baseline is 3. The description does not add additional detail about the parameter beyond what the schema provides, but it does explain the validation process (format + domain check), which indirectly enriches understanding of the input's role.

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 validates an Italian PEC address by checking format and domain against AGID certified providers, with a confidence level. This distinguishes it from sibling tools like validate_codice_fiscale or validate_iban, which handle different identity 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 provides clear context for using the tool (validating PEC addresses) but does not explicitly exclude use cases or mention alternatives. The sibling list implicitly provides alternatives, but the description itself lacks explicit 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?

The description adds significant behavioral context beyond annotations: it performs external I/O (VIES), and gracefully degrades to 'attention' (never false 'ok') when VIES is unavailable or budget exhausted. It also declares it is free and requires no login. This transparently discloses failure modes and constraints.

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 well-structured paragraph that front-loads the core purpose (anti-fraud before payment) and then details checks and behaviors. It is not overly long, but could be slightly more concise by grouping related details. Every sentence adds information, earning a 4.

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 output schema, the description adequately describes return values (verdict with three levels plus red flags). It covers edge cases (VIES down) and scope limits (out-of-band not replaced). With 6 parameters and external I/O, the description provides sufficient context for an agent to select and invoke the tool 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 baseline is 3. The description adds value by explaining how parameters like iban, vat_number, codice_fiscale, and expected_name are used in checks (e.g., 'ragione sociale reale via VIES'). However, it does not mention ateco or expected_country, leaving their role implicit. Overall, it provides useful context beyond 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 identifies the tool as an anti-fraud verification of a beneficiary before paying an invoice, specifically targeting IBAN change/BEC fraud. It lists specific checks (IBAN checksum, VAT, tax code, VIES) and distinguishes from sibling tools by stating it performs external I/O and combines multiple validations.

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 when to use the tool ('PRIMA di pagare una fattura') and provides exclusion guidance ('NON sostituisce la verifica out-of-band'). However, it does not explicitly mention alternative tools for simpler validations (e.g., validate_iban for IBAN format only), so guidance on choices among siblings is partial.

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