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

Without annotations, the description carries the full burden. It clearly indicates a read operation returning metadata with no side effects. However, it does not specify response format or size, which would add further transparency.

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, concise sentence that front-loads the purpose ('Return metadata') and lists key contents. Every word is earned with no 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 tool with zero parameters and a simple purpose, the description adequately covers what the agent needs to know. It mentions the return contents, though adding that it is a lightweight call or the response is typically small would 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?

There are no parameters, so the baseline is 4. The description adds meaning by listing what is returned, which goes beyond the empty schema. No parameter documentation is needed.

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 ('Return') and clearly states the tool provides metadata about the MCP server, listing specific items (version, data source, coverage, tool list). This distinguishes it from sibling tools that focus on decisions, guidelines, or topics.

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 usage for retrieving server-level information, but does not explicitly state when to use this tool versus alternatives, such as 'Use this to get an overview before making queries.' No exclusions or conditions are mentioned.

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. However, it does not disclose any behavioral traits such as whether the operation is read-only, requires authentication, or has any side effects. The description only states what the tool does, not how it behaves.

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, front-loaded with the action and resource. No unnecessary words; every part 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?

Given the tool's simplicity (one parameter, no output schema), the description is sufficient for an agent to understand its purpose and usage. It could be enhanced by noting what the response contains, but that's optional.

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 covers 100% of parameters with a description. The tool description adds concrete examples of reference numbers, which helps the agent understand the expected format. This adds value beyond 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?

The description clearly states it retrieves a specific IMY decision by reference number, with examples. It distinguishes itself from sibling tools like se_dp_search_decisions by focusing on a single known 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 description implies when to use: when you have a specific reference number. It does not explicitly state when not to use, but the mention of 'by reference number' guides the agent to only use this tool if a reference is available, otherwise search.

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 full burden. It only says 'get a specific...' without disclosing error behavior, return structure, or any side effects. Minimal behavioral insight.

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?

Extremely concise, one sentence. No wasted content, though it may be too brief to fully inform. Structured well for a simple getter.

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?

Adequate for a simple retrieval tool. Lacks details on output format or error handling, but given no output schema and one parameter, it covers the essential 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?

Schema coverage is 100% with a clear parameter description. The tool description adds no extra meaning beyond what the schema provides, so baseline score 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 retrieves a specific IMY guidance document by database ID. It differentiates from the search sibling, though does not explicitly contrast with get_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?

No explicit guidance on when to use this tool over alternatives. The parameter description hints the ID comes from se_dp_search_guidelines, but the description itself lacks context on prerequisites or use cases.

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 must carry the transparency burden. It accurately describes a read-only operation (list all) without side effects, making behavior transparent for a simple zero-parameter tool.

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 front-load the core action and add a useful usage hint. Every sentence adds value with no redundancy or fluff.

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 no parameters, no output schema, and simple behavior, the description is complete. It explains what the tool returns (bilingual topic names) and how to use the results with sibling tools.

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 no parameters (0 params, 100% schema coverage). The description does not need to add parameter details, and the baseline for zero parameters is 4.

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 verb 'List' and the resource 'all covered data protection topics', with specific output of 'Swedish and English names'. This distinguishes the tool from siblings which deal with decisions and guidelines.

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 second sentence explicitly instructs to use topic IDs to filter decisions and guidelines, providing clear context of when to invoke this tool. However, it does not explicitly state when not to use it or list alternative tools.

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 it performs a 'full-text search' and returns specific fields, which implies a read operation. However, it does not disclose pagination behavior, rate limits, error handling, or the effect of missing parameters. The description adds moderate transparency but misses key details.

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 concise with two sentences, front-loading the action and listing key return fields. It efficiently communicates the core functionality without redundancy. A slightly more structured format (e.g., bullet points) could improve scannability, but current form is adequate.

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 no output schema, the description briefly mentions return fields but does not explain the result structure, error handling, or default behaviors (e.g., limit default of 20 is only in schema). For a search tool, it is moderately complete but lacks details on pagination and filtering of empty queries.

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 has 100% description coverage, so the baseline is 3. The description adds context about the query language (Swedish) and mentions returned fields, but does not provide additional semantics for the 'type' or 'topic' parameters beyond the schema. The added value is marginal.

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 explicitly states 'Full-text search across IMY decisions' and lists the returned fields (reference, entity name, fine amount, GDPR articles). This clearly identifies the tool's purpose and distinguishes it from sibling tools like se_dp_get_decision (single decision retrieval) and se_dp_search_guidelines (different resource).

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 indicates use for searching decisions but does not provide guidance on when to use this tool versus alternatives like se_dp_get_decision or se_dp_search_guidelines. No exclusion criteria or prerequisites are mentioned. The context with sibling tool names implies differentiation, but the description itself lacks explicit usage instructions.

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 exist, so the description alone must convey behavioral traits. It mentions document types and topics but lacks details on read-only nature, authorization, rate limits, error handling, or result behavior (e.g., pagination). This leaves significant gaps for an agent.

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 using a colon to list document types and topics. It is front-loaded with the core action ('Search IMY guidance documents') and contains no unnecessary words.

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 absence of an output schema and annotations, the description covers the tool's subject but omits key execution details like result format, pagination, required authentication, or how to use filters effectively. It is adequate but not comprehensive.

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% with descriptions for all 4 parameters. The description adds examples of search topics (e.g., 'kamerabevakning', 'cookies') and guidance types, which provides context beyond the schema but does not substantially augment parameter understanding.

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 searches IMY guidance documents (vägledningar, riktlinjer, ställningstaganden) covering GDPR implementation, DPIA methodology, etc. It distinguishes this from sibling tools like se_dp_search_decisions (legal decisions) and se_dp_get_guideline (single document retrieval).

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 usage for searching guidance documents but does not provide explicit guidance on when to choose this tool over alternatives. No exclusions or context for when-not-to-use is given, though sibling tool names offer some implicit differentiation.

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