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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only mentions checking status and validating a token, but does not state whether the tool is read-only, what it returns, or any side effects. For a tool with no annotations, this is insufficient.

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 that is front-loaded and free of extraneous words. It conveys the core purpose 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?

The tool has no output schema, so the description should explain what the agent can expect as a response (e.g., success/failure, account details). It does not, leaving a significant gap in understanding the tool's behavior. Given the simplicity of the tool (1 optional param), a more complete description is expected.

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% for the single parameter 'token' with a basic description. The description adds value by explaining that the tool validates the token, which goes beyond the schema's 'Optional Apify API Token to test' – it implies the token is tested for validity.

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: 'Checks the status of the Apify account and validates the API token.' It uses specific verbs ('checks', 'validates') and a specific resource ('Apify account', 'API token'), distinguishing it from sibling tools that deal with scraping and searching.

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 no guidance on when to use this tool versus alternatives, no prerequisites, and no context about when a status check is appropriate. It is purely a statement of function without usage 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?

No annotations are provided, and the description adds no behavioral context. It fails to disclose any notable traits such as authentication requirements (token is optional), rate limits, pagination behavior, error handling, or what happens if the datasetId is invalid. The agent has no insight into side effects or restrictions.

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, which is concise but overly minimal. It is front-loaded with the key action, but it lacks any structure or additional information. Every sentence should earn its place, and this one is too sparse to be considered efficient.

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 and no annotations, the description should cover return values, prerequisites, and pagination behavior. It does not mention that the dataset must already exist from a previous scrape, nor does it describe the format of the returned items. This is insufficient for a tool with four parameters and pagination.

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 input schema already describes all four parameters. The description adds no additional meaning beyond the schema. While it does not repeat the schema, it also does not explain how parameters like offset and limit relate for pagination, which would be helpful.

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 action ('fetches scraped items') and the resource ('from a previously generated Apify dataset ID'). It distinguishes this tool from siblings like subito_scrape_by_url (scraping) and subito_search (searching) by focusing on existing datasets.

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 guidance is provided on when to use this tool versus alternatives. It does not mention that it should be used after scraping, nor does it explain when to use subito_search or apify_check_status instead. No exclusions or prerequisites are 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 provided, the description must fully disclose behavioral traits. It mentions the use of an Apify Actor and provides parameters like timeout, which hints at asynchronous behavior. However, it does not disclose whether the tool is synchronous or asynchronous, if it returns results directly or only initiates a run, or what happens on failure (e.g., invalid URL, Actor timeout). The description is adequate but leaves gaps.

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, compact sentence that conveys the core purpose and implementation. It wastes no words and is easy to parse. This is exemplary conciseness.

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 has no output schema, 4 parameters, and no annotations, the description is too brief. It does not explain the return format (e.g., what the scraped data looks like), error behavior, or how to handle the Apify Actor lifecycle (e.g., need to check status or get dataset items separately). The presence of sibling tools like 'apify_check_status' and 'subito_get_dataset_items' suggests a pipeline, but the description does not connect them.

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% (all 4 parameters have descriptions). The tool description adds no additional parameter details, but the schema itself is complete and clear. The baseline is 3 per the rubric; the description includes the full search URL format example, which adds marginal value. Thus a score of 4 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 action ('scrapes classified ads'), the specific source ('directly from a Subito.it search URL'), and the implementation ('using Apify Actor'). The name 'subito_scrape_by_url' reinforces this. While the purpose is clear, it does not explicitly distinguish from siblings like 'subito_search' which might serve a similar but different purpose.

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 no guidance on when to use this tool versus alternatives like 'subito_search' or 'subito_get_dataset_items'. It does not mention prerequisites (e.g., valid search URL format), when not to use it, or what to do after scraping (e.g., check status or retrieve items). The agent is left to infer usage from 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that the tool 'scrapes the results via Apify' without clarifying the scraping mechanism, potential delays (though timeoutSecs exists), rate limits, error behavior, or whether the operation is purely read-only. The description adds minimal behavioral context beyond what a user could guess from the name and parameters.

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, well-structured sentence that front-loads the core action and key filtering dimensions. Every word carries meaning, with 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?

The tool has 10 parameters and no output schema, yet the description omits details about the result format, pagination behavior, or what information each scraped ad provides. It also fails to explain the role of Apify (external dependency, potential costs) or the significance of the timeout parameter. For a complex search-and-scrape tool, this is insufficient context for an AI agent to reliably interpret results or handle edge cases.

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 mentions general parameter categories (keywords, category, region, etc.) but does not add semantic detail beyond what the schema already provides for each parameter (e.g., how the price range interacts with sorting, or the relationship between region and query scope). The description is adequate but not enriching.

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 uses specific verbs ('Searches', 'scrapes') and identifies the resource ('Subito.it for ads'). It name-checks the key filtering dimensions (keywords, category, region, price range, shipping) and distinguishes the tool from siblings like subito_scrape_by_url (which handles URL-based scraping) and subito_get_dataset_items (which retrieves stored results).

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 provide any guidance on when to use this tool versus the listed siblings. It implies general search usage but offers no explicit context for preferring subito_search over subito_scrape_by_url or apify_check_status, nor does it mention any prerequisites or limitations.

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