Precios del Campo

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior beyond that: it discloses exactly what a hit contains (identifier, ámbito, unidad, frecuencia, fuente, último precio con fecha), which matters since there is no output schema.

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

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

Two sentences, zero filler: the search capability and its examples come first, the return shape second. Every clause carries information an agent can act on.

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

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

With no output schema, describing the returned fields is exactly the right compensation and it is done well. The gaps are minor: how 'texto' interacts with ámbito/fuente filters and the role of the limite default (10, max 20) are left to the schema alone.

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 75%, so most parameters are already documented in the schema. The description's four example queries usefully illustrate what 'texto' accepts (including a combined product+province query) but adds nothing about ambito, fuente or the limite cap.

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 ('Busca series de precios') and enumerates the dimensions searched (producto, variedad, provincia) with four concrete example queries. The return statement about identifiers distinguishes it from siblings like precio_ultimo, but no sibling is named explicitly, 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?

Usage is implied by the examples ('naranja navelina', 'gasóleo zaragoza') and by the fact that it returns series identifiers for later lookup. There is no explicit statement of when to use this versus precio_ultimo or historico, and no exclusions or prerequisites are 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?

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds real behavioral content beyond them: the data is the last published day, prices include taxes, and it is a retail public-sale price, plus the returned comparison metrics. That extra context is genuinely useful.

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

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

A single dense sentence, front-loaded with the resource and price type before the scope details. It earns its length because there is no output schema to describe the returns, but the long clause chain sacrifices some 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 one-optional-parameter read tool with no output schema, the description does the necessary work: it explains what is averaged, what comparisons are returned, the day basis and that taxes are included. Only the absence of guidance on default behavior when 'provincia' is omitted is a minor gap.

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

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

Schema coverage is 100% and the single 'provincia' parameter is fully documented in the schema with examples. The description only echoes it as optional ('la provincia que se pida') without adding format or default-value semantics, so baseline 3 applies.

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

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

It states a precise resource ('precio medio del gasóleo B (agrícola) en las gasolineras') and the scope of the result (Spain, Comunitat Valenciana, requested province, plus ranking and extremes). This clearly identifies the retrieved data. However, it never distinguishes itself from siblings like precio_ultimo or historico, so the agent must infer the boundary.

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

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

Usage is only implied: the mention of the 'último día publicado' signals a latest-snapshot query, but there is no explicit when-to-use, when-not-to-use, or routing toward alternates such as precio_ultimo or historico. The agent can guess, but nothing is 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?

Beyond the annotations (which already cover read-only and idempotent safety), the description discloses important behavioral traits: truncation to the most recent points when the series exceeds max_puntos, and the escape hatch (full series in the linked CSV). This truncation rule is material and not visible in the schema. It does not describe the shape of returned points, keeping it from 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?

Purpose is front-loaded in the first clause, with coverage frequencies and truncation rationale following. It is dense but each element earns its place; the parenthetical of frequency history is long but informative rather than filler.

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

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

There is no output schema, and while the description explains truncation and the CSV fallback, it does not describe the returned series format (e.g., timestamped points). Annotations cover safety, so the remaining gap is the return representation, which leaves it 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 coverage is 75%, so most parameters are already documented (desde/hasta as optional dates, serie as the identifier). The description adds real value on max_puntos by explaining what happens on overflow, though it largely restates the default 104 and cap 520 already present in the schema. Baseline 3 fits a high-coverage schema doing most of the work.

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

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

Names a specific resource (price series) and the selection criteria (by identifier, between two dates), which is clearly distinct from siblings like gasoleo_hoy or precio_ultimo that return a single current value. It does not explicitly name those alternatives, but the temporal-range framing makes the scope inferable.

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 rather than stated: the range/identifier framing signals 'use for historical lookups' versus the point-in-time siblings, and the frequency notes tell the agent what history is available. There is no explicit when-to-use, when-not, or named alternative, so it stays at implied 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, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds only a small amount of behavioral context by noting that each result includes what happens and its official source; it does not discuss update frequency, data freshness, or any limitations.

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

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

A single well-formed sentence that front-loads the core purpose and packs examples and output details without any filler. Nothing extraneous.

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 read-only tool with rich annotations and full schema coverage, the description explains what the tool returns (event details and official source), which compensates for the missing output schema. It is nearly complete, though it could mention default behavior or any temporal scope limitations.

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

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

Schema description coverage is 100%, so the schema already documents both parameters (tema and desde) with examples and defaults. The description adds no additional meaning about how these parameters filter or behave, 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?

States a specific resource (upcoming official dates for agriculture) with concrete examples (PAC, quarterly taxes) and what the result includes (what happens that day and its official source). Clearly distinguishable from sibling tools like buscar_producto, gasoleo_hoy, historico, and precio_ultimo, which deal with prices rather than deadlines.

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 state when to use this tool versus alternatives, nor does it mention any alternatives. It only describes the content, leaving usage conditions entirely implicit.

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, so the safety profile is covered. The description goes further and enumerates the actual return payload (price, date, week, previous value, trend direction, source, license, link), which is valuable given there is no output schema, though it omits how many records are returned or what an empty result looks like.

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 sentence, front-loaded with the core purpose before listing return fields. It is dense but every clause earns its place; no filler or 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?

With no output schema, the description correctly shoulders the burden of describing return values, and it does so thoroughly. It does not note that all four parameters are optional or how multiple matches are handled, which is a minor remaining gap.

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

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

Schema coverage is 75%, so the schema already documents serie, ambito and producto. The description restates the serie-vs-producto dichotomy but adds nothing about ambito or limite, so it neither compensates for the gap nor extends the documented 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?

States a specific verb+resource: 'Último precio publicado de una serie' or of products matching a text. It also enumerates the returned fields, so the agent knows exactly what it retrieves. It does not, however, name or distinguish itself from siblings like historico or buscar_producto, 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?

Usage is implied: pass an exact identifier, or a search text when the identifier is unknown. There is no explicit when-to-use/when-not guidance and no reference to alternatives such as buscar_producto for discovering identifiers or historico for longer time series, so it remains only implicit.

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