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

No annotations are provided, so the description carries the full burden. 'Return metadata' clearly signals a read-only operation and enumerates the response categories, but it does not explicitly state that it is non-mutating or describe response structure beyond the listed fields. For a simple metadata endpoint this is adequate, though not fully explicit.

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 with no filler; the purpose and the response contents are front-loaded. 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?

The tool is simple (no params, no output schema). The description lists the four metadata categories, telling an agent what to expect, though it omits the exact response shape (e.g., JSON object). For an 'about' tool this is nearly complete, but specifying the response format would close a small 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?

There are zero parameters and an empty object schema, so the baseline is 4. The description lists the metadata categories that will be returned, which is all that is needed; there are no parameter semantics to clarify.

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 specific verb ('Return'), a resource ('metadata about this MCP server'), and enumerates the contained fields (version, data source, coverage, tool list). This clearly distinguishes it from the sibling search/get/list 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?

The description makes the use case explicit: retrieve server-level metadata when that information is needed. It does not explicitly contrast with sibling tools or state when not to use it, but the distinction is inferable from the sibling names and the tool's singular purpose.

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 behavioral burden. It transparently indicates a read-style retrieval operation and scopes it to exact reference lookup. It does not discuss not-found behavior or response shape, but for a simple single-parameter getter this is reasonably transparent.

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, tightly worded sentence that starts with the action and resource, then immediately gives the required identifier format with examples. Every element earns its place and there is no extraneous information.

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-parameter retrieval tool with no nested objects and no output schema, the description is complete enough for an agent to select and use the tool correctly. It names the exact input needed and provides realistic reference formats. No additional context is necessary.

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%, and the description itself mirrors the schema's parameter documentation. It adds example values, but those examples already appear in the schema description. The description does not add significant semantic value beyond what the schema provides.

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 specific verb ('Get'), a specific resource ('a specific ANSPDCP decision'), and the identifying mechanism ('by reference number'). It also gives concrete examples. This distinguishes it from sibling search tools like ro_dp_search_decisions, which is about finding decisions rather than retrieving a known one.

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 phrase 'Get a specific ... by reference number' clearly conveys that this tool is for when a known decision reference is available. It implicitly contrasts with search, but it does not explicitly say 'use ro_dp_search_decisions when you don't have a reference,' so it stops short of full exclusion 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?

The description and tool name convey a read operation, and specifying the target resource helps. However, with no annotations and no output schema, the description does not disclose what the response contains (full text, metadata, etc.) or error behavior.

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 with no filler. Every word contributes to understanding the tool's purpose and operation.

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-parameter getter, this is nearly complete: it names the resource, the lookup key, and the source of that key. The only notable gap is not clarifying whether the returned value is the full document text or just metadata, especially given there is no output schema.

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% and the single parameter is already documented with its type and provenance. The tool description adds no parameter-level detail beyond what the schema provides.

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 (Get), resource (ANSPDCP guidance document), and selection mechanism (database ID). This clearly distinguishes it from sibling tools like ro_dp_search_guidelines (search vs. retrieval) and ro_dp_get_decision (guideline vs. decision).

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 schema's parameter description identifies the ID as coming from ro_dp_search_guidelines results, implying this tool is used after searching. Context is clear, though there are no explicit exclusions or comparison to alternatives.

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 present, so the description carries the full burden. It discloses output scope (all topics, Romanian/English names) and the relevance of IDs, but does not describe response structure, format, or limits. Acceptable for a simple non-destructive listing operation.

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 tight sentences with no redundancy. The action is front-loaded, and the downstream usage is stated in the second sentence. 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?

Given zero parameters and no output schema, the description still tells an agent what the tool returns (topics in two languages) and why to call it. It does not spell out the exact item schema, but that is not essential for correct selection and invocation here.

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?

There are zero parameters, so schema coverage is complete by default. The description adds useful context by indicating that topic IDs are the key output used downstream, which is valuable for correct use.

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?

Description uses specific verb 'List' and resource 'all covered data protection topics', and adds detail about Romanian and English names. This clearly differentiates it from sibling decision/guideline search 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?

Second sentence gives a concrete use case: obtaining topic IDs to filter decisions and guidelines. It doesn't explicitly name alternative tools, but the context clearly marks it as a lookup/reference tool for the other operations.

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?

There are no annotations, so the description carries the behavioral disclosure burden. It communicates that the operation is a read-only search and specifies what is returned: reference, entity name, fine amount, and GDPR articles cited. It does not mention pagination, result limits beyond the schema's default, or query matching nuances, but these are less critical for a search operation.

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 with no filler: the first states the action and scope, the second states the return content. Every sentence adds information an agent needs.

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, so the description adequately compensates by naming the key fields of matching decisions. With four parameters, a fully documented schema, and no output schema, the description covers the essential context, though explicit mention of the 'opinion' type and pagination could improve 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?

Schema description coverage is 100%, so the schema already documents all parameters including examples for query and defaults for limit. The description adds little parameter-specific meaning, but this is acceptable because the schema carries the load.

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 specific operation, 'Full-text search,' and a specific resource, 'ANSPDCP decisions,' with concrete examples of included content. It also distinguishes this tool from siblings like ro_dp_search_guidelines by narrowing scope to decisions.

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 this tool is for free-text searching across decisions, but it does not explicitly state when to prefer it over ro_dp_get_decision or ro_dp_search_guidelines. There is no 'when not to use' guidance or named alternative.

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 mentions the topics covered (GDPR, DPIA, cookies, CCTV) but does not disclose return format, result contents, pagination/limit behavior, or whether the search is read-only. The absence of this context for a search tool with no output schema is a significant gap.

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 with no filler. The core function is front-loaded ('Search ANSPDCP guidance documents'), and the second sentence adds valuable scope details without 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?

For a simple search tool, the description provides adequate scope and topic coverage. However, it omits guidance on sibling differentiation and return behavior, and since there are no annotations or output schema, those omissions leave the agent with meaningful uncertainty.

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 adds useful topic context (e.g., 'videomonitorizare (CCTV)') that aligns with query and topic parameters, but it does not go substantially beyond what the parameter descriptions already provide.

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 ('Search') and identifies a clear resource ('ANSPDCP guidance documents'), listing the document types included (guidelines, opinions, recommendations, FAQs). It is clear and actionable, though it does not explicitly differentiate from the sibling tool ro_dp_search_decisions beyond the implicit 'guidance' vs. 'decisions' distinction.

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 states what the tool searches but gives no explicit guidance about when to use it instead of a sibling like ro_dp_search_decisions. It does not mention alternatives or exclusions, leaving the agent to infer routing from tool names alone.

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