mydatapass

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

No annotations are provided, so the description carries the full burden of explaining behavioral traits. It only describes the content of the tool (what MyDataPass is), not its behavior such as whether it is read-only, what it returns, or any side effects. This lack of behavioral disclosure makes it difficult for an agent to know what to expect from invoking it.

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 fully captures the tool's purpose without extraneous words. It is front-loaded and every phrase adds meaning, making it highly concise and well-structured.

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's simplicity (no parameters, no output schema), the description provides a reasonable overview but leaves gaps: it does not clarify the return format (e.g., plain text vs. structured data) or confirm that the operation is safe/read-only. Since there are no annotations to supplement this, the context is only partially 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?

The tool has zero parameters, and the schema is empty. Per the rubric, a base score of 4 is appropriate when there are no parameters to describe. The description does not need to add parameter details since none exist, and it does not introduce confusion.

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 purpose: it provides information about MyDataPass, its category, and its target audience. While it lacks an explicit verb, the 'what/who' structure makes the intent unambiguous. It also distinguishes from sibling tools like check_compliance_requirement or get_pricing by focusing on the product itself rather than specific features.

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 that this tool is used when one needs general information about MyDataPass, but it does not explicitly state when to use it or when to prefer alternatives. No exclusions or alternative tool references are provided, so the usage context is only indirectly conveyed.

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 of behavioral disclosure. It states that the tool checks how MyDataPass relates to a regulation, but does not disclose the output format, whether it is read-only, or potential limitations (e.g., unsupported regulations or how results are presented). The description is minimally transparent but lacks behavioral depth.

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-formed sentence that immediately states the tool's purpose and includes examples. There is no filler, tautology, or unnecessary detail.

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's low complexity (one parameter, no nested objects, no output schema), the description covers the essential usage. However, because there is no output schema, it could be more complete by indicating whether the result is a status, a summary, or detailed requirements mapping. Still, it is adequate for a simple lookup 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 provides a clear description for the only parameter ('regulation') with an example. The description repeats the same examples without adding extra meaning or context beyond what the schema already specifies. With 100% schema coverage, 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?

The description uses a specific verb ('Check') with a clear resource ('MyDataPass') and target ('data/privacy regulation'), and gives concrete examples ('GDPR', 'EU Data Act', 'Article 20'). It clearly distinguishes this tool from siblings like get_pricing or verify_certificate by focusing on regulatory compliance relationships.

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 clearly implies the tool should be used when the user asks about how MyDataPass complies with a specific regulation. It does not explicitly list exclusions or alternatives, but the examples and sibling names make the appropriate use case unambiguous.

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 of behavioral disclosure. It only states what the tool returns (offboarding flow and client deliverables) but does not mention whether it is a read-only operation, requires authentication, or has any side effects. For a get/informational tool, the lack of explicit safety disclosure is a minor gap, but still present.

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 directly states the tool's output and content. It is front-loaded with the key information and contains no filler or redundancy, making it highly scannable for an AI agent.

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 is simple with no parameters and no output schema, so the description is mostly adequate. However, it could benefit from a phrase like 'Use to understand the offboarding process' to clarify intended context. As written, it tells what is returned but not why or when to use it, leaving a small but notable gap in completeness.

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 per the baseline rule, the description does not need to add parameter semantics. The schema is empty and the description doesn't attempt to describe parameters, which is appropriate. No information is missing here.

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 indicates the tool provides the step-by-step offboarding flow and what the client ultimately receives. While it is a noun phrase rather than an explicit verb+resource, the name 'get_offboarding_guide' combined with this description makes the purpose unambiguous and distinct from sibling tools about pricing, compliance, or certificate verification.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, appropriate contexts, or when to avoid it. The only hint is the offboarding topic, which differentiates it from siblings, but the description itself provides no usage direction.

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 behavioral burden, and it discloses nothing: no indication of whether pricing is live or cached, whether authentication is required, or whether results can change. The only implicit signal is that it reads public prices, which is weak but non-destructive.

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?

One compact sentence with the resource front-loaded and a concrete product list; nothing is wasted. It falls short of 5 because the fragmentary phrasing lacks an action verb, making it terse at the expense of clarity.

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 zero-parameter read tool with no output schema, the description conveys the returned domain and enumerates the products, which is adequate coverage. It omits return structure and any hint about currency, refresh cadence, or ordering, so it is minimally sufficient rather than 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?

The tool takes zero parameters, so there are no parameter semantics to explain; the baseline for a 0-parameter tool is 4. The description correctly adds no parameter discussion, though it also does not clarify that no filtering options exist.

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 the resource (MyDataPass products and their public prices) and enumerates the covered products, so the content domain is identifiable. However, it is a noun phrase with no verb, so the agent cannot tell whether it lists, looks up, or returns pricing on request. It is distinguishable from siblings by content but not explicitly differentiated.

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?

There is no guidance on when to call this tool, when not to, or what alternative to use for related needs. The agent must infer that this is the pricing lookup versus about_mydatapass or check_compliance_requirement purely from the resource name.

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?

Without annotations, the description carries full burden. It specifies that the tool provides instructions for offline verification, which is a behavioral trait. However, it does not disclose what happens when the optional token is provided or the format of the explanation, leaving some ambiguity.

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 with no filler, front-loading the action ('Explain') and specifying the exact resource and conditions. Every word 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 simple informational tool with one optional parameter and no output schema, the description plus schema cover the essentials. However, the description doesn't explicitly state what the user should expect as a result (e.g., a step-by-step guide), which leaves 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?

The input schema fully documents the single parameter (token) with a description stating it is optional and verification is done offline. The tool description itself adds no parameter-specific information beyond the schema, 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?

The description clearly states the tool's function: 'Explain how to independently verify a MyDataPass delivery certificate (offline).' It uses a specific verb ('Explain') and resource ('delivery certificate'), and the offline/independent qualifiers differentiate it from any online verification tools. It stands apart from siblings which focus on general info, compliance, offboarding, and pricing.

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 the tool is for users seeking offline verification instructions, but it does not explicitly state when to use this tool over alternatives or when not to use it. No exclusions or alternative tool mentions are provided, so the guidance is implied rather than explicit.

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