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

No annotations provided, so the description carries the full burden. It discloses that the tool returns metadata, statistics, freshness, and provenance. This is transparent and consistent with a read-only information 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 concise sentences front-load key terms and provide actionable guidance. Every sentence 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 is fully complete. It explains what the tool returns and when to use 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?

No parameters exist, so schema coverage is trivially 100%. The description adds meaning by explaining what the tool returns, exceeding the baseline of 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 specifies 'Server metadata, dataset statistics, freshness, and provenance' and explicitly states the action 'verify data coverage, currency, and content basis'. This clearly distinguishes it from sibling tools that perform specific legal research functions.

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 explicitly states 'Call this to verify data coverage, currency, and content basis before relying on results', providing clear context for when to use it. It does not explicitly mention when not to use, but the usage guidance is strong.

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 cover behavioral traits. It states the tool aggregates results from statutes, case law, and preparatory works simultaneously, but does not disclose if it is read-only, any required permissions, or output format. Adequate but not rich.

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 sentences long, front-loaded with the main purpose, and contains no extraneous information. Every sentence is essential and clear.

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 6 parameters and no output schema, the description covers the main purpose and usage. It does not describe the return format or how results are structured, which would be helpful, but it is mostly complete for a tool that aggregates search results.

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 parameter descriptions. The description adds context that it searches across multiple sources, aligning with the include_* parameters. However, it does not provide additional meaning beyond what the schema already offers, so a baseline 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 builds a comprehensive set of citations for a legal question by searching across multiple sources simultaneously. It distinguishes from siblings like search_case_law or search_legislation, which are more specific, by emphasizing the aggregation across statutes, case law, and preparatory works.

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 advises using this tool for 'broad legal research questions', implying comprehensive searches are appropriate. While it doesn't explicitly mention when not to use it or specify alternatives, the context is clear about its intended use case.

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 and adequately discloses that it returns document status (in_force, amended, repealed, not_yet_in_force), dates, and warnings, and that providing as_of_date enables historical evaluation. It does not reveal potential edge cases or limitations.

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. The first establishes the purpose, and the second lists outputs and a usage hint. 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?

The description lists return fields (status, dates, warnings) and explains the as_of_date parameter, which is sufficient given no output schema. However, it lacks details on error handling or the exact response format.

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 schema already describes all parameters. The description adds only that 'as_of_date' is for historical evaluation, which is similar to the schema description. Minimal added 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 the tool checks if a Danish statute or provision is in force, using a specific verb and resource. It distinguishes from siblings like 'get_provision' by focusing on currency status rather than full text.

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 explains when to provide the optional 'as_of_date' for historical evaluation, offering clear usage guidance. However, it does not explicitly state when not to use this tool or mention alternatives among siblings.

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 description carries full burden. It describes three output formats with examples, making behavior clear for a formatting tool. No destructive behavior expected.

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 of purpose plus a bullet list of formats. No wasted words, front-loaded with verb and resource.

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 low complexity (2 params, no output schema), the description is sufficient. It explains purpose and formats. Could mention return value explicitly, but not necessary for such a simple 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?

Schema coverage is 100%, so baseline is 3. The description adds value by providing examples for each format option, clarifying what the 'format' parameter does beyond the enum values.

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 formats a Danish legal citation per standard conventions. It distinguishes from sibling 'validate_citation' and other tools. The verb 'format' and resource 'citation' are specific.

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 formatting legal citations but does not explicitly state when to use or not use this tool versus alternatives like 'validate_citation'. No exclusions or conditions provided.

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 explains the tool returns relevant statutes with status and article references. No side effects or auth needs mentioned, but for a read-only retrieval tool this is adequate.

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?

Three short paragraphs with no wasted words. First sentence states purpose clearly, example follows, and a concluding sentence emphasizes value.

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?

Without an output schema, the description outlines return content (statutes, status, article references) but lacks specifics on structure, pagination, or error handling. Adequate for a moderate-complexity tool but not exhaustive.

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 baseline is 3. The description reiterates the 'eu_document_id' parameter with an example but does not add significant meaning 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 the tool finds Danish statutes implementing EU directives/regulations, with a specific example and details on return content. It distinguishes from siblings like 'search_eu_implementations' by focusing on Danish law.

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?

Provides context for when to use ('essential for finding Danish law corresponding to EU requirements') but does not explicitly exclude alternatives or mention when not to use it. Still clear enough for an agent.

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 full burden. It describes the return content (reference types, article citations, primary implementation flag) but does not disclose potential large response size, error handling, or read-only nature. Some behavioral context is present, but not comprehensive.

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 a front-loaded first sentence stating the purpose. It uses three sentences to convey purpose, return details, and importance without 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 no output schema and no annotations, the description adequately explains the return value (EU directives/regulations with reference types and article citations). However, it does not address edge cases, error scenarios, or distinguish between related siblings, leaving some gaps for complete decision-making.

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%, with clear descriptions for each parameter. The main description adds no additional parameter semantics beyond the schema, meeting the baseline expectation for full schema 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 description clearly states it retrieves EU legal basis for a Danish statute, with specifics on returned data (directives, regulations, reference types, article citations). It distinguishes from siblings like 'get_provision_eu_basis' by focusing on statutes rather than provisions, but does not explicitly differentiate.

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 when needing EU legal basis for a Danish statute, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., 'get_provision_eu_basis' or 'search_eu_implementations'). No exclusions or when-not-to-use instructions are given.

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 provided, so the description must compensate. It states it returns linked documents with summaries but does not mention error handling, rate limits, or whether it is read-only. The behavior is implicitly safe but not fully disclosed.

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 short sentences. However, the first sentence partially repeats the tool name. It is well-structured and 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 simple tool with one parameter and no output schema, the description sufficiently explains what it returns (linked documents with summaries) and its value. Lacking details on edge cases like empty results.

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%, and the description adds minimal extra meaning beyond the schema. It reiterates the parameter's purpose but does not enrich it significantly.

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 preparatory works for a Danish statute and explains its purpose for understanding legislative intent. It distinguishes itself from sibling tools like get_provision and search_legislation.

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 context on when to use the tool (to understand legislative intent) but does not explicitly state when not to use it or compare with 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?

With no annotations, the description carries full burden. It explains that omitting optional parameters returns all provisions, supports historical dates, and shows different formats for flat vs. chaptered statutes. This adds significant behavioral context despite some missing details on error handling.

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, well-structured with front-loaded purpose and examples. Every sentence adds value, and there is no redundant or empty text.

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 adequately explains the tool's behavior for all parameter combinations. It covers what the tool returns (provision text) and how to get all provisions. It is complete enough for an agent to use correctly.

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 baseline is 3. The description adds value by showing examples and clarifying the relationship between chapter/section and provision_ref, going beyond the schema parameter descriptions.

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 provision from a Danish statute. It uses a specific verb ('Retrieve') and resource ('a specific provision from a Danish statute'), and distinguishes itself from sibling tools like search_legislation and build_legal_stance.

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 clear examples of how to use different parameter combinations (chapter+section vs provision_ref) and mentions when to omit them. While it doesn't explicitly exclude sibling tools, the usage context for retrieving a specific provision is well defined.

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 states the tool returns EU directives/regulations with article-level precision, which is adequate for a read operation. However, it does not disclose specifics like error handling, authentication needs, or whether results are always 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 three sentences, each serving a distinct purpose: stating the tool's function, clarifying return content, and giving usage guidance. No fluff or redundant 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?

Given the tool has two well-documented parameters, no output schema, and no annotations, the description covers the essential aspects: purpose, return type, and a usage example. It is complete enough for the tool's simplicity.

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 a baseline of 3 is appropriate. The description does not add additional meaning beyond what the schema already provides for the two 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 the verb 'Get' and the resource 'EU legal basis for a specific provision within a Danish statute'. It provides a concrete example and distinguishes from siblings like 'get_eu_basis' by focusing on provision-level precision.

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 explicitly advises using this tool for 'pinpoint EU compliance checks at the provision level', which provides clear when-to-use guidance. It does not explicitly mention when not to use or alternatives, but the context of sibling tools implies differentiation.

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 discloses that the tool returns source metadata and mentions its purpose (transparency and audit), which conveys it is safe and read-only. No annotations exist, but the description is sufficient for this simple list 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?

The description is a single, concise sentence that leads with the action and then specifies return details. Every word earns its place, 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 parameterless list tool with no output schema, the description fully conveys the purpose, return data, and use case. It is complete for an agent to understand and invoke correctly.

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?

With zero parameters, the input schema is fully covered. The description adds value by explaining what the output contains (URLs, licenses, coverage), which is relevant for parameter selection (none needed). Baseline 4 applies.

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 specifies the verb 'List' and the resource 'all data sources and their provenance'. It also details the returned information (source URLs, licenses, coverage), distinguishing it from sibling tools that search or validate specific legal content.

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 use for transparency and audit compliance but does not explicitly state when to use this tool versus alternatives like search_legislation or validate_citation. No when-not guidance is provided.

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 bear the full burden. It describes the search scope (case summaries, keywords) and filters (court, date range) but lacks details on pagination, response format, or side effects. It is adequate but not thorough.

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 wasted words. The first sentence states the purpose, the second adds detail on filtering and search scope. Front-loaded and 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?

Given 5 parameters and no output schema, the description covers the tool's core function and filters. It lacks information on pagination, result format, or sorting, but is generally complete for a basic search tool with clear sibling differentiation.

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 each parameter documented. The description adds 'case summaries and keywords' beyond the schema's 'Search query for case law summaries', indicating that keywords are also searched, providing extra context.

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 Danish court decisions with specific verb 'Search' and resource 'Danish court decisions'. It distinguishes from sibling tools like search_legislation by specifying case law.

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 case law searches but does not explicitly state when to use this tool over alternatives, nor does it provide exclusion criteria or alternative tool suggestions.

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 fully disclose behavior. It states the return type ('matching EU documents with counts'), but lacks details on pagination, error handling, or authentication. The behavioral disclosure is adequate but not comprehensive.

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 at three sentences, with the purpose front-loaded. Every sentence adds value: purpose, filter summary, and usage example. 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 tool has 7 parameters, no output schema, and no annotations, the description covers the basic purpose and usage but fails to specify the output structure (e.g., is it a list? paginated? what fields are returned?). It partially describes return type but lacks full 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 explains each parameter. The description repeats the filter options ('by keyword, type, year range, or community') without adding significant new meaning. Baseline 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 purpose: searching for EU directives and regulations with Danish implementation information. It uses a specific verb ('Search') and resource, and distinguishes from siblings like search_case_law or get_danish_implementations by focusing on EU documents with implementation counts.

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?

Provides a clear usage example ('Use this for exploratory searches like 'data protection' or 'privacy''), indicating appropriate scenarios. However, it does not explicitly state when not to use this tool or mention alternative sibling 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?

Describes search mechanism (FTS5 with BM25 ranking), supported syntax, and output format. Since annotations are absent, the description carries the full burden and does well, though it omits rate limits or auth requirements.

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?

Four sentences, each serving a clear purpose: purpose, technical detail, syntax, output. No wasted words, 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?

Sufficient for a search tool: explains what is returned (snippets, scores, metadata) and all parameters are described. Missing pagination details but not critical.

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%, baseline 3. The description adds value by detailing query syntax (boolean operators, phrases, prefix) beyond the schema's 'FTS5 syntax' note.

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?

Clearly states the tool searches Danish statutes and regulations by keyword, distinguishing it from sibling tools like search_case_law and search_eu_implementations.

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 Danish statutory/regulatory text but does not explicitly state when not to use or mention alternatives. The context is clear enough given sibling names.

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 provided. The description mentions returning warnings and being a 'zero-hallucination enforcer,' but does not disclose read-only nature, auth needs, or rate limits. Adequate but not detailed.

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 and front-loaded with the main purpose. It includes necessary format examples without verbosity. Minor redundancy in 'Parses the citation' is acceptable.

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 one parameter, no nested objects, and no output schema, the description covers purpose, input formats, and outcome (warnings). It is complete for a simple validation tool, though return structure is not specified.

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% for the single 'citation' parameter. The description adds value by listing supported citation formats, which goes beyond the schema's simple string description.

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 'validate' and the resource 'Danish legal citation', distinguishing it from siblings like 'format_citation' and 'check_currency'.

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 explains the tool validates a citation, checks existence, and returns warnings, implying when to use. However, it does not explicitly exclude when not to use or compare 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?

With no annotations, the description explains the tool's behavior: it checks three specific aspects and returns compliance status. It also discloses the Phase 1 limitation, adding transparency about future enhancements. No destructive side effects are implied.

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 well-structured with bullet points and a note, but contains slight redundancy (Phase 1 mentioned twice). It is generally concise and front-loaded with the main purpose.

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?

No output schema exists, so description should detail return structure. It lists possible statuses and mentions warnings/recommendations, but lacks full detail on the response object. Given no annotations and 3 parameters, completeness is adequate but not thorough.

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 parameters are already described. The description adds an example EU directive (95/46/EC) but does not significantly enhance understanding beyond the schema. Baseline 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 validates EU compliance for Danish statute/provision, listing specific checks like references to repealed directives. It distinguishes from sibling tools like validate_citation by focusing on EU compliance.

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 validating EU compliance but does not explicitly state when to use versus alternatives like get_eu_basis or check_currency. No 'when not to use' guidance is provided.

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