PuntoSeguro · Seguros de vida y salud

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world). The description adds genuine value beyond them: the exact formula, the rounding rule, that a breakdown is returned, and the informational-only/non-advice caveat plus geographic restriction.

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 plus a short disclaimer; the formula and result are front-loaded, and every sentence carries distinct information (method, output, legal scope) with no redundancy.

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

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

An output schema exists so return values need no explanation, yet the description still notes the amount plus breakdown. For a three-parameter calculator with full annotation coverage, nothing an agent needs to invoke it correctly is missing.

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

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

Schema coverage is 100%, so the baseline is 3. The description goes further by explaining how each input feeds the formula (five years of net income, debts added, existing cover subtracted), giving the agent a semantic model of the parameters rather than just their 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?

States a specific verb (calculates), resource (life-insurance coverage amount), target population (Spain residents), and even the exact method used. It is clearly distinguishable from the sibling quote/application tools, which price or apply rather than estimate coverage.

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 this applies (a Spain-resident, indicative estimate) and delineates scope by excluding individualized advice, premiums and savings products, which subtly routes the agent to the quote tools. However, no alternative tool is named and there is no explicit 'use this instead of X when Y' 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?

Beyond the readOnly/idempotent annotations, the description discloses a key pricing behavior: each premium is the highest that can apply at that age, so exact-date-of-birth quotes will be the same or lower. It also clarifies the output fields and the limitation that results are not a whole-market comparison.

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 purpose is front-loaded and most clauses earn their place, including the alternative tool and the premium-bound caveat. The main sentence is dense and could be split for easier scanning, but it is not bloated.

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 output schema, rich annotations, and full schema description coverage, the description is complete for correct invocation. It supplies the business context, the alternative path, and the key pricing caveat that the structured fields do not capture.

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

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

Schema coverage is 100%, and the schema already documents both parameters with their ranges. The description restates that age is in whole years and that a coverage amount is required, but it does not add format or constraint details 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 states a specific verb and resource: it returns annual life-insurance premiums for a resident of Spain by age and coverage amount, and lists the exact returned fields. It clearly distinguishes this aggregate age-based lookup from list_life_insurance_quotes, which uses an exact date of birth.

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

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

It explicitly says the tool works without a date of birth and routes the agent to list_life_insurance_quotes when the exact date of birth is available. It also states that the date of birth is required for the application link and warns that this is not a whole-market comparison.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond that: the shape of the payload (sections, inclusions/exclusions, payment options, variants), the cross-tool data dependency, and the geographic restriction to Spain. It does not say what happens on a mismatched or unknown insurer_id, which is the main remaining gap.

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

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

A single front-loaded sentence puts the return payload first, then the identifying key and its provenance, then the eligibility constraint. No filler or redundancy; every clause carries information an agent needs.

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

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

With an output schema present, the description need not explain return values in depth, and annotations cover the safety profile. It supplies the preresquisite tool, matching keys, and geo restriction. The only shortfall is error/failure behavior when the quote cannot be found or the birth/coverage inputs disagree with the listed quote.

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%, including the coverage_variant default guidance, so the schema already documents all six parameters. The description only restates that insurer_id originates from list_life_insurance_quotes and that birth date/coverage amount must match the earlier lookup; it adds no syntax or constraint detail 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 names a specific verb and resource (returns details of one life-insurance quote) and enumerates exactly what comes back: coverage sections, included/excluded items, payment options and premium variants. It also pins the lookup key to an insurer_id produced by list_life_insurance_quotes, which separates it from siblings like calculate_life_insurance_coverage and start_life_insurance_application.

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

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

It establishes the prerequisite sequence — the insurer_id must come from list_life_insurance_quotes, with the same birth date and coverage amount — and scopes eligibility (Spain residents only). There is no explicit contrast with calculate_life_insurance_coverage (e.g. 'use this to inspect an existing quote rather than compute coverage'), so the alternative-selection guidance is implied rather than stated.

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

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

Annotations already cover read-only/idempotent/closed-world, and the description adds real context beyond them: a fallback response shape when inputs are absent, an explicit 'indicative' qualifier, the no-medical-information constraint, and the limited-insurer-panel caveat. It stops short of saying how fresh the premiums are or how the comparison interface behaves when unsupported.

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

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

Front-loads purpose, then fallback behavior, then caveats — a sound order with no filler sentences. The one inefficiency is the long enumeration of returned fields (insurer, product, cover type, copay, covers, documentation, link), which duplicates the output schema.

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 an output schema covering return fields and annotations covering safety, the description supplies exactly what is left: eligibility domain, missing-input fallback, result limitations, and privacy scope. An agent can call this correctly without further inference.

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 both parameters are fully documented with types, ranges, and the province enum, so the baseline applies. The description only reconfirms that ages are per-person and province is the residence province, adding no syntax or validation detail 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?

States a specific verb and resource (returns indicative monthly private health-insurance premiums) with a clear scope: Spain residents, via PuntoSeguro. The insurer/product/cover-type enumeration and the explicit 'not a whole-market comparison' boundary make it unmistakable and trivially separable from the life-insurance siblings.

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

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

Clearly implies when to call it (ages + province of Spanish residents) and documents the degraded path when those are missing ('returns PuntoSeguro's quote form and the list of missing details'). It does not name alternatives, but the sibling set is all life-insurance tools, so there is no same-domain route to redirect to.

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 carry readOnly/idempotent/non-destructive, so safety is covered. The description adds genuine value beyond them: the scope limitation to PuntoSeguro insurers (not whole-market), the missing-input fallback returning the quote form, and the conditional comparison interface. This is useful behavioral context not derivable from structured fields.

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

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

Two dense sentences, front-loaded with the return content, then the fallback and scope caveat. No wasted filler, though the first sentence is heavily packed.

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?

An output schema exists, so return values need not be explained. The description supplies the operant conditions (missing inputs -> form), scope limitation, and provider context, which is sufficient for a read-only, zero-required-param quote listing tool.

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

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

Schema description coverage is 100%, so the baseline is 3. The description echoes the meaning of DOB and coverage amount but adds no format, range, or constraint detail beyond what the schema already documents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (returns), resource (life-insurance premiums), provider (PuntoSeguro), and the exact output fields (insurer ids/names, death, death+disability, double/triple capital). It is clearly the quote-listing tool vs siblings like get_life_insurance_quote_details. It does not explicitly name siblings, so it stops short of a 5.

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

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

It implies usage via required inputs (exact DOB + coverage amount) and describes a fallback when they are missing. However, it never states when to prefer this over get_life_insurance_quote_details or open_life_insurance_quote_form, leaving routing to inference.

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

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

Annotations already cover the safety profile (readOnly, non-destructive, idempotent, closed-world), but the description adds genuinely new context: 'Sends and stores no personal data' and the eligibility constraint 'Residents of Spain only'. It also describes the post-submit behavior (quotes are shown). It does not mention how the form is surfaced or any UI/state side effects, keeping it short of a 5.

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

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

Three compact sentences, front-loaded with the primary action, then the user flow, then the optional parameter, privacy, and eligibility. Every clause carries information; nothing is padding.

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

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

An output schema exists, so return values need not be described. The description covers the action, the optional input's conditional use, data-privacy behavior, and a geographic eligibility gate — enough for an agent to decide and invoke correctly.

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

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

Schema description coverage is 100% and the single parameter is already documented with its conditional ('only if the user already stated or calculated one'). The description's 'Optionally preselects a coverage amount' merely restates the schema, adding no syntax, format, or boundary detail. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Displays PuntoSeguro's life-insurance quote form') plus the user flow it drives (date of birth, coverage amount, submit shows quotes). This clearly separates it from calculate_life_insurance_coverage, get_life_insurance_quote_details, list_life_insurance_quotes, and start_life_insurance_application, which are calculation, retrieval, listing, and application tools respectively.

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 it applies (a user wanting a quote) and notes the optional preselection, but it never explicitly says when to choose this over calculating coverage or listing existing quotes. No prerequisites or exclusions are stated, so routing relies on inference from sibling 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?

Annotations already establish readOnly, idempotent, non-destructive, closed-world behavior, so the bar is lower; the description usefully adds that nothing is submitted and no personal data is collected, that the questionnaire and signature happen on puntoseguro.com, and that the final premium depends on underwriting. That is real side-effect and outcome context beyond the annotations, though link expiry or reuse behavior is not mentioned.

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, front-loaded with the return value, followed by behavioral disclosure and the underwriting caveat. No sentence is redundant with the name, title, or schema.

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 six-parameter tool with a full output schema and annotations, the description covers prerequisites, side effects, and outcome uncertainty, which is close to complete. It stops short only on how it relates to the near-duplicate open_life_insurance_quote_form sibling.

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%, including ranges for birth_day/month/year and the enum for coverage_variant, so the schema already carries the semantics. The description only loosely restates that the quote is identified by insurer id, coverage option, date of birth and amount, adding no format or constraint detail beyond what is structured. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and artifact ('Returns the secure link to start an application on puntoseguro.com') plus the exact inputs that identify the quote. It explicitly ties itself to the list_life_insurance_quotes output, so an agent can tell it apart from the listing/quote siblings without opening a schema.

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

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

The description implies a clear prerequisite chain: the insurer_id must come from list_life_insurance_quotes 'for the same date of birth and coverage amount', so the agent knows this tool is a follow-up to quote discovery. It gives no explicit exclusions and never distinguishes itself from the very similarly named open_life_insurance_quote_form sibling, which is the main remaining ambiguity.

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