Precios del Campo

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description earns credit beyond that by disclosing the return shape (series identifier, ámbito, unit, frequency, source, and last price with date), which is essential given there is no output schema. It omits result-limit behavior and empty-result handling.

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, zero filler. The core search scope is front-loaded and the return contract follows immediately, with examples embedded inline rather than padded into a separate list.

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 4-parameter read tool with no output schema, the description covers the searchable dimensions and the returned fields, which is the bulk of what an agent needs. Remaining gaps are minor: no statement about the default/max result limit or what an empty match 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?

Schema coverage is 75%, so the baseline is 3, but the description adds real meaning: the example strings show what free text 'texto' accepts, and the phrase 'producto, variedad o provincia' plus the 'gasóleo zaragoza' example maps the free text onto the separate 'ambito' dimension. 'fuente' and 'limite' are left entirely to 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 ('Busca series de precios por producto, variedad o provincia') and reinforces it with four concrete query examples, so the agent knows exactly what corpus is searched. It does not, however, contrast itself with siblings like precio_ultimo or historico, which also return price data, leaving overlap to inference.

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 example queries ('naranja navelina', 'gasóleo zaragoza') show the shape of a valid lookup but the description never says when to pick this tool over precio_ultimo, historico or gasoleo_hoy, nor when it is the wrong choice. Adequate for a simple search tool, but no explicit routing 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, 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?

Annotations already cover the read-only/idempotent/closed-world profile, yet the description adds real value: it discloses per-source cadence and start dates, and the truncation rule (returns the most recent points when exceeding max_puntos, full series in the linked CSV). The truncation behavior is exactly the kind of result-shaping detail an agent needs.

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, purpose front-loaded, and the long parenthetical carries only substantive data-coverage detail. Dense but every clause 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?

With no output schema, the description adequately explains what is returned (a price series, truncated to max_puntos, with the full series available via CSV). Combined with annotations this is complete enough to call 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 coverage is 75%, and the description compensates for the undocumented max_puntos by explaining its default (104), cap (520) and recency behavior, plus the date-range meaning of desde/hasta. It adds meaning beyond the raw schema constraints.

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: returns the price series of an identifier between two dates. The date-range scope implicitly separates it from siblings like precio_ultimo and gasoleo_hoy, 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?

The parenthetical documents per-source data coverage and cadence (weekly from 2017 in Comunitat Valenciana, etc.), which helps judge fit, but there is no explicit when-to-use guidance or comparison against precio_ultimo/gasoleo_hoy/plazos. Usage is left 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 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 and closed-world, so safety is covered. The description adds value beyond them by disclosing the returned payload in detail (previous datapoint, up/down/flat trend, source, license, chart/history link), which matters since there is no output schema. Nothing about auth, rate limits, or empty-result behavior is stated.

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 leads with what the tool returns, then appends the payload fields. It is dense but earns its space given the absent output schema. The trailing field enumeration reads as a run-on and could be trimmed.

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 tool with no output schema, the description compensates by naming the returned fields, and it explains both identifier and text-search modes. Gaps remain around parameter combinations (e.g., `ambito` requiring `producto`, behavior with no arguments) and result limits, but an agent has enough to call 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?

Schema description coverage is 75%, with `serie`, `ambito` and `producto` documented inline; only `limite` lacks a description, though its default/min/max are in the schema. The description restates the identifier-vs-text distinction already in the schema but adds nothing about `ambito` scoping or `limite` behavior, 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?

The description states a concrete resource and scope: the last published price of a series (by identifier) or of products matching a text, and it enumerates what comes back (price, date, week, trend, source, license, link). An agent can tell it retrieves the latest datapoint rather than a series history. It never names its siblings (historico, buscar_producto), so differentiation is left to inference.

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 two operating modes — pass `serie` if you know the identifier, or match by `producto` text — which gives usable context. However, it never states when to prefer this over historico or buscar_producto, nor what happens if neither parameter is supplied. Usage is implied rather than prescribed.

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