BorsaBovini

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

With no annotations, the description carries the full transparency burden. It explicitly discloses that contacts are not included and that replies are done through the page link, and it scopes to active ads only. These are meaningful behavioral details beyond the schema, though pagination and output format remain unaddressed.

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 concise sentences: the first front-loads the resource and content fields, the second states the contact limitation. There is no redundancy or 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?

For a low-complexity, zero-required-parameter listing tool with no output schema and no annotations, the description is reasonably complete. It provides the key output fields and a critical limitation, while the schema covers parameter defaults and formats. It lacks explicit usage routing and pagination details, but those gaps do not seriously undermine the ability to select 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?

The schema already documents 'tipo' via an enum with default and 'provincia' as name or abbreviation, while 'razza' is undocumented. The description mentions razza and provicia as output fields, hinting at their filtering role, but it does not directly explain how parameters refine results. With 67% schema coverage, the description adds a little context but does not fully compensate for the incomplete 'razza' parameter.

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 resource (active ads on the BorsaBovini board), states who it covers (sellers and buyers of cattle), and lists the returned fields. It is semantically distinct from siblings like prezzi_bovini, piazze_disponibili, and cerca_trasportatori. Though no explicit verb like 'list' is used, the meaning is unambiguous.

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

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

No explicit when-to-use or when-not-to-use guidance is provided, and no sibling tool is named. The intended usage is implied by the description: use this tool for active buy/sell announcements rather than for prices or transporters. The guidance is adequate but not 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?

With no annotations, the description carries the burden; it discloses that the tool is a public listing with 170+ firms and includes served zones, vehicles, and contacts. However, it does not explicitly state the return behavior, such as whether all records are returned when no filters are supplied.

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 lead with the registry's purpose and content, then state the filter action. No redundant phrases or 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?

For a low-complexity lookup tool, the description conveys the available data and filter dimensions, but the absence of an output schema and explicit return-value description leaves some ambiguity about what the agent will receive.

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

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

Schema description coverage is ​0%, so the description must compensate. It identifies regione and provincia as filters, but gives no format guidance, allowed values, or clarification that both are optional or can be combined.

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 resource (public registry of livestock carriers) and the action (filtering by province/region). It is distinct from the sibling tools by domain, though it does not explicitly name or contrast them.

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 filter instruction implies when the tool is useful, but there is no explicit guidance on when to prefer it over sibling tools or what scenarios it is not suited for. The context is inferable from the domain 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?

With no annotations, the description carries the full burden and it delivers: it discloses that the result is 'sempre un INTERVALLO, non un numero secco', that the yield is declared with its provenance, and that yield varies with breed. It does not mention error or validation behavior, but for a conversion tool the key behavioral traps are covered.

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 every sentence carries useful information: operation, rationale, interval output, yield variability, and usage. It is longer than strictly necessary due to the illustrative Piemontese/Frisona example, but the example supports the behavioral point rather than 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?

Given five parameters, no annotations, and no output schema, the description explains the input types, output shape (interval), yield provenance, and when to call it. It leaves the exact response structure unspecified, but an agent has enough context to invoke the tool and interpret the result.

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 80%, so the schema already documents most parameters; the description adds only a general hint that 'la razza conta più della categoria'. It does not elaborate on the optional razza or the required valore beyond what the schema states, which is acceptable given the high coverage.

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 first sentence begins with a specific verb and target: 'Trasforma un peso o un prezzo da peso vivo a peso morto (carcassa) e viceversa', which clearly identifies the operation and resource. This makes it immediately distinguishable from the sibling market-data tools, which do not perform conversion.

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 gives a concrete trigger for use: 'Da usare prima di confrontare due prezzi con basi diverse' and explains why via the Camere di Commercio vs Commissione Europea mismatch. It lacks explicit exclusions or alternative-tool routing, but no sibling competes for this job, so the absence is minor.

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?

With no annotations, the description carries the transparency burden and does real work: it discloses that the result includes source lists, validity dates, and a file fingerprint, and it explicitly promises that confidential documents will be reported as unavailable rather than silently omitted. This is useful behavioral context beyond the schema.

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

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

Two compact sentences front-load the core purpose and then add one high-value behavioral caveat about confidential documents. The phrasing is slightly narrative, but every sentence earns its place and there is no real 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?

For a read-only lookup with three optional parameters and no output schema, the description covers purpose, source content, and the refusal behavior. It is incomplete on base_peso semantics and does not fully describe the returned document structure, leaving some ambiguity for an 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?

Schema coverage is only 67%; 'dal' and 'fonte' have descriptions, but 'base_peso' is just an unlabeled enum ('vivo'/'morto'). The description reinforces validity dates and source lists but never explains how to set base_peso, so an agent cannot confidently fill that parameter.

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 resource ('i documenti originali dietro le nostre quotazioni') and the function: retrieving the original commodity-market list behind a quoted price, including validity dates and file fingerprint. It doesn't explicitly contrast with a sibling tool, but the purpose is specific enough for an agent to distinguish it from price-lookup tools.

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 gives a clear use case: 'Serve a chi vuole risalire dal numero alla carta' – trace a price back to its source document. That is clear contextual guidance, though it stops short of naming alternatives or explicit when-not-to-use conditions.

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?

No annotations are provided, so the description carries the full burden. It identifies the tool as informational ('what it offers, how it is used'), which implies a read-only, side-effect-free operation. It does not detail the response format, whether the information is static, or any limitations, but for a simple info tool this is a reasonable level of disclosure.

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-structured sentence that front-loads the purpose ('what BorsaBovini.it offers and how to use it') followed by a compact list of covered topics. No filler or redundancy; every element contributes meaning.

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 zero-parameter, no-output-schema informational tool, the description gives enough context to understand its purpose and place among the siblings. It could be slightly more explicit that the output is likely a static text summary, but the scope is small and the description sufficiently covers it.

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 the schema coverage is complete (100%), so the parameter semantics baseline is 4. There is nothing for the description to add about parameters, and it correctly omits any.

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 this tool tells the user what BorsaBovini.it offers and how to use it, enumerating content areas (quotations, bulletin board, scan, transport, contacts). This distinguishes it from the sibling tools, which are specific feature-based tools, though the distinction is implicit rather than explicit.

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 this is the general overview/help tool while the siblings cover specific functions, and the listed topics hint at those alternatives (quotazioni -> prezzi_bovini, bacheca -> annunci_bacheca, trasporti -> cerca_trasportatori). However, it never explicitly states when to use this tool versus a sibling, or when not to use it.

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

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

With no annotations provided, the description carries the full burden. It discloses that the data is user-declared (not official), is a regional 'pulse', and includes the number of sources ('con il numero di chi lo ha rilevato'). This gives important behavioral context about data reliability and what the output will contain. It does not mention side effects, but this is a read operation and the description adequately conveys its non-authoritative nature.

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

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

The description is three sentences, front-loaded with the core purpose. It is slightly verbose but each sentence adds value: purpose, differentiation, and behavioral caveat. It is well-structured and not overly long for a tool with this 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 four optional parameters and no output schema, the description is incomplete. It explains the nature of the data and hints at the output containing a count, but it does not explain parameter usage, whether all parameters are optional, or what the response looks like beyond that count. It also mentions 'per settimana' without a corresponding parameter, leaving ambiguity. The description should provide more guidance for effective invocation.

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

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

Schema description coverage is only 25% (only 'regione' has a description). The tool description mentions 'per zona' which maps to regione, but does not explain 'razza', 'base_peso', or 'categoria'. It also implies weekly data but no week parameter is in the schema, creating potential confusion. With low coverage, the description fails to compensate by clarifying the other parameters.

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

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

The description clearly states it provides prices declared by market participants (breeders, operators, associations) per zone and week, and explicitly distinguishes itself from official quotations. It does not name a specific sibling tool for differentiation, but the 'not official' contrast effectively separates it from likely alternatives like prezzi_bovini.

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 context that it reflects real regional prices that can deviate from national references, and explicitly states it is not an official price and does not replace quotations. However, it does not name an alternative tool or provide explicit when-to-use conditions beyond 'for real regional data' vs. official. It implies usage but lacks direct routing.

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?

With no annotations, the description carries the full behavioral burden and does substantial work: each quote includes source, timestamp, and stale/fresh status; the selected value follows an authority hierarchy rather than an average; vivo/morto are not comparable; and zona data are kept separate from the official price. These are non-obvious behaviors an agent needs to interpret results correctly.

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 compact five-sentence paragraph, front-loaded with the core purpose and then adding one distinct fact per sentence: provenance and staleness, authority rule, filters, and zona behavior. There is no filler or repetition beyond what 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?

For a tool with six optional parameters, no output schema, and no annotations, the description covers the essential facts needed for correct invocation: data source, per-price fields, authority selection, weight non-comparability, and optional zona behavior. Minor gaps such as an explicit return structure or default no-filter behavior remain, but the description is largely sufficient.

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 and the schema already documents all six parameters. The description adds value by restating the vivo/morto non-comparability caveat, clarifying that 'zona' appends separate Osservatorio readings, and explaining the authority rule that determines which value to cite, though it does not deeply expand on the other parameters.

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

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

The description states that this tool returns cattle quotations from Italian commodity exchanges ('Le quotazioni dei bovini rilevate dalle borse merci italiane') and lists the available filters, so its function is unambiguous. It does not use an explicit verb like 'restituisce' and does not name sibling tools, so it stops short of full sibling differentiation.

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 gives clear usage context: the price to cite follows an authority hierarchy (Modena first, ISMEA fallback, not an average), and it explains how to filter and when to use 'zona' to append separate Osservatorio data. However, it never explicitly says when to prefer a sibling tool such as osservatorio_zone or serie_storica, so exclusions are absent.

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?

With no annotations, the description carries the burden of disclosing behavior. It states the output will include median, count, and market locations per period, and the time window options. However, it does not disclose read-only status, how missing periods are handled, or any response/error details, leaving some behavioral uncertainty.

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

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

The description is three sentences, front-loaded with the core purpose and temporal options, then output details, then the question it answers. Every sentence adds value and there is no redundancy or repetition of schema 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 6-parameter tool with no output schema and no annotations, the description is reasonably complete: it covers the main query intent, temporal constraints, and aggregation output. However, it omits explanations of 'razza' and 'base_peso' and the precise filtering effect of 'piazza', which an agent needs to call the tool optimally.

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 only 33%, so the description must compensate. It adds meaning to 'passo' (weekly/monthly), 'mesi' (up to 24 months back), and 'categoria' (cattle category), and mentions 'piazze' in the output. However, it does not explain 'razza' or 'base_peso', and does not clarify that 'piazza' filters to a single market, leaving gaps.

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 function: showing the historical trend of cattle categories over time with weekly or monthly granularity. It specifies the resource (serie storica of cattle prices), the aggregation (median, count, piazze), and the question it answers (price up or down), which distinguishes it from single-value tools like prezzi_bovini.

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 a clear context: use this tool when you need to know whether a price has risen or fallen over time, which a single value cannot tell. It implies when not to use it (for current/spot prices) and scopes the time range and step, but does not explicitly name sibling tools or provide exclusion criteria.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool reports whether each source is fresh, delayed, or stopped, which is meaningful behavioral context. It could be more explicit about output shape or side effects, but for a zero-parameter informational tool this is solid.

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 well-structured sentences: the first enumerates exactly what information is returned, and the second explains the practical purpose. Every phrase contributes meaning, and the most important content is front-loaded.

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 inputs and no output schema, the description is remarkably complete. It specifies the kind of data included, the status categories, and the intended decision-making context. An agent has enough information to invoke the tool correctly and interpret its purpose.

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, so the baseline is 4. The description does not need to elaborate on parameters, and the schema already reflects an empty properties object. No additional semantic guidance is required.

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 provides information about every price source covered by BorsaBovini, including the source's real name, what it measures, its hierarchy weight, publication frequency, and current freshness status. This content is specific and distinct from the sibling tools, making the tool's purpose unambiguous even without an explicit verb.

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 a clear use case: 'Serve a sapere quanto fidarsi di un numero prima di citarlo' and also helps identify what is not working. It does not explicitly name alternatives or exclusions, but the context is strong enough to guide an agent on when to invoke this tool.

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