law

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions returns but does not describe the structure, error behavior, authentication needs, or whether it is read-only. This is insufficient for a tool without annotations.

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 immediately conveys the tool's purpose and scope. No wasted 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 lacks detail on the output format or structure, which is important since there is no output schema. It also does not clarify what 'deep extraction' entails, leaving some ambiguity.

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%; the description does not add extra meaning to the parameters beyond what the schema provides. It contextualizes the parameters within EU regulations but does not explain syntax or constraints.

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 performs deep article-level extraction from specific EU regulations (DORA, MiCA, AMLR) and lists returned items (obligations, delegated acts, cross-jurisdiction equivalents). It distinguishes itself from sibling tools that focus on US, UK, or general legislation searches.

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 extracting from EU regulations, but does not provide explicit guidance on when to use this tool versus alternatives like eurlex_search or obligation_search. No 'when not to use' or comparative context is 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 are provided, placing full burden on the description. The description does not disclose behavioral traits such as authentication requirements, rate limits, data freshness, or side effects beyond stating it retrieves information. This is a significant gap for a read 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?

The description is a single, front-loaded sentence of 10 words that efficiently communicates the tool's purpose without extraneous text. 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?

With no output schema and minimal description, the definition lacks details on return format, potential null fields, error handling, and parameter dependencies (e.g., 'number' may be required despite not being marked as such). The description is insufficient for comprehensive understanding.

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?

Input schema has 100% coverage with basic descriptions for each parameter. The description adds output context but no additional parameter-specific semantics beyond what the schema provides, resulting in a baseline score.

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 'Get' and the resource 'detailed bill information', listing key components like sponsors, status, committees, and text. It distinguishes from sibling tools such as congress_bill_search, which focuses on search rather than detail.

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 detailed bill info but provides no explicit guidance on when to use this tool versus alternatives like congress_bill_search or when not to use it. No prerequisites or exclusions 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, and the description does not disclose behavioral traits such as default limit, pagination, authentication, or handling of no results. The description 'Search US Congressional bills' is too vague for a search 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 the purpose and provide concrete examples. Could be slightly more structured but is efficient and to the point.

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 only basic parameters, the description lacks details on return format, pagination, or error handling. A search tool would benefit from more behavioral context.

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 both parameters (limit, query) are defined in the input schema. The description adds example terms but does not provide additional semantic 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 it searches US Congressional bills, with specific examples like stablecoin and crypto, effectively distinguishing from sibling tools such as congress_bill_detail (detail retrieval) and federal_register_search (different source).

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 through example search terms but lacks explicit guidance on when to use this tool vs alternatives, such as when to use congress_bill_detail or other search 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?

Without annotations, the description bears full responsibility for behavioral disclosure. It implies a read-only search operation but omits details on side effects, authentication, rate limits, or pagination behavior. The statement 'Search 1.1 million+ opinions' does not address what the tool actually returns or 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 extremely concise with two sentences, no filler, and directly communicates the tool's scope and data source. It is front-loaded with the key action 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?

For a search tool with no output schema and no annotations, the description is insufficiently complete. It does not explain what the response contains (e.g., search results list, metadata), pagination, error handling, or any limitations beyond the count of opinions. The agent lacks information to effectively handle the tool's output.

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 already provides descriptions for all three parameters (type, limit, query) with 100% coverage. The description adds no additional semantic meaning beyond stating the tool searches opinions, which is already clear from the schema's type parameter with 'o=opinions (default)'.

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 US federal and state court opinions via CourtListener, specifying coverage of 1.1 million+ opinions including Supreme Court, Circuit, and District Courts. It is distinct from sibling tools that focus on legislation, regulations, or other legal searches.

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 like multi_jurisdiction_search or other legal search tools. The description lacks explicit context for appropriate usage or exclusions.

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 lacks details on side effects, authorization needs, or read-only behavior. It only states the tool 'lists' laws, which is minimally informative.

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 conveys the tool's purpose efficiently with no 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?

For a parameterless tool, the description is fairly complete but lacks information about the output format (e.g., what fields are returned for each law). Given no output schema, this gap reduces 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?

Since the input schema has no parameters, the description is not required to add parameter details. The baseline for 0 parameters is 4, and the description fulfills this by not adding unnecessary information.

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 identifies the tool as listing German federal laws relevant to financial regulation, with specific examples. It distinguishes from siblings like de_law_lookup (which likely retrieves details on a specific law) and other jurisdiction-specific 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?

The description implies the tool is used to list indexed German financial laws, but it does not explicitly state when to use this tool vs alternatives or mention any exclusions or prerequisites.

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 it retrieves 'metadata and links' but does not specify what metadata fields are included, the nature of the links, or any side effects (e.g., read-only). This is minimal disclosure for a lookup 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?

The description is a single, short sentence that is front-loaded and efficient. However, it could include additional context without becoming verbose, such as mentioning the required abbreviation format.

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 lack of annotations and output schema, the description is insufficient. It does not explain what 'metadata' entails (e.g., full title, date, citation) or the format of links. For a tool with one parameter, a more complete description would clarify the return value expectations.

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% because the single parameter 'law' includes a list of valid abbreviations in its description. The tool description adds no further meaning beyond the schema, so the baseline score 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?

Description includes a specific verb ('Get') and resource ('metadata and links for a specific German federal law'), clearly stating what the tool does. However, it does not differentiate from the sibling tool de_law_list, which likely lists all available laws, so the unique scope is implied but not explicit.

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 de_law_list (to find the abbreviation) or when not to use it. It does not mention prerequisites or context, leaving the agent to infer usage solely from the tool 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?

No annotations provided. The description does not disclose behavioral traits such as API limits, rate limiting, or that it is a read-only operation. The mention of SPARQL hints at the query method but does not add meaningful behavioral context.

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 clear front-loading. However, the first sentence includes 'via EUR-Lex SPARQL' which may be unnecessary for an agent; slightly less concise than ideal.

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 with no output schema and no annotations, the description covers core functionality and return values (CELEX numbers, links). Missing details about pagination, sorting, or possible empty results, but adequate for basic usage.

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?

Input schema covers 100% of parameters with descriptions. The description adds minimal value beyond the schema (e.g., stating 'Search term' and 'Max results') but does not provide additional semantic clarification or examples.

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 EU legislation via EUR-Lex SPARQL and returns CELEX numbers and EUR-Lex links. It identifies the verb (search) and resource (EU legislation), but does not explicitly differentiate from sibling tools like uk_legislation_search or congress_bill_search.

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 on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or scenarios where other tools would be more appropriate.

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 does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or what 'full document' entails. The description carries the full burden but adds minimal 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?

Single sentence, front-loaded, no extraneous information. Efficient 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?

For a simple ID-based retrieval with one well-described parameter, the description is minimally sufficient. However, it lacks detail on return format, error responses, or what constitutes a 'full' document, leaving some gaps for an AI agent.

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 the parameter description already provided. The tool description adds no extra meaning beyond 'by document number', so 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?

Description clearly states the action (Get) and resource (full Federal Register document) with the identifying parameter. It is specific but does not explicitly differentiate from sibling tools like federal_register_search, though the verb 'Get' implies retrieval by ID.

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 on when to use this tool versus alternatives. Siblings include search and detail tools, but the description does not clarify when to choose this over federal_register_search or others.

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 carries the burden. It implies a read-only search operation but does not disclose additional behavioral traits like pagination, sorting, or error handling. Adequate for a simple search 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 efficient sentences with no fluff. First sentence states action and resource, second adds scope. 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 two-parameter search tool with full schema coverage, the description provides adequate context on purpose and scope. No output schema, but return structure is implicitly understood. Slight deduction for not mentioning return 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?

Input schema covers 100% of parameters with descriptions. The tool description adds no extra meaning beyond the schema, so baseline 3 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?

Clearly states it searches the US Federal Register for rules, proposed rules, and notices, and specifies it covers all federal agencies. Distinguishes from sibling tools like regulations_gov_search.

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 on when to use this tool versus alternatives. Does not mention any exclusions or prerequisites, leaving the agent 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, the description carries the burden. It lists returned items (cache stats, API key status, source count) but does not explicitly state it is a safe, read-only operation with no side effects.

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 of 8 words that is fully front-loaded and contains 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 simple health check tool with no parameters and no output schema, the description adequately covers what the tool returns. It could mention that the operation has no side effects, but it is sufficient for an agent to understand its 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?

The input schema has zero parameters, so no additional meaning is needed. The description does not add parameter info, but it is irrelevant as there are none.

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 that the tool provides server status including cache stats, API key status, and source count. It implies a health check verb, distinguishing it from sibling tools like 'ping' which likely offers a simpler connectivity test.

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 on when to use this tool versus alternatives like 'ping'. It does not specify troubleshooting contexts or mention any prerequisites.

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 a read-only listing, which is transparent, but lacks details on output structure, pagination, or potential limitations. The description is adequate but minimal.

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, highly concise, and front-loaded with the key action and resource. Every word is meaningful and contributes to the 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?

Given no parameters, no output schema, and no annotations, the description is complete enough for the core purpose but lacks details about output format and what 'capabilities' entail. It is adequate but not rich.

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, and the schema is empty. The description adds no parameter info, but with zero parameters, the baseline is 4. No additional meaning 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 specifies the exact verb 'list' and the resource 'jurisdictions, data sources, and their capabilities'. It clearly distinguishes from sibling tools that are search or retrieval oriented.

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 discovering available jurisdictions and data sources before using other tools, but it does not explicitly state when to use it or provide alternatives. Usage 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.

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

No annotations are provided, so the description must carry the full burden. It states the scope (4 jurisdictions, 7 databases) but does not disclose behavioral traits such as pagination, rate limits, authentication requirements, or how results are structured. This is minimal for a search 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?

The description is concise (two sentences) and front-loaded with purpose. However, the second sentence is promotional ('killer feature') rather than purely informative, slightly reducing clarity. Still 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?

For a search tool with 3 parameters and no output schema, the description provides adequate context about scope but lacks details on result format, pagination, or database specifics. It is sufficient enough for an agent to invoke 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?

Input schema has 100% coverage with clear parameter descriptions. The description adds no new parameter-level details beyond the schema; it only promotes the tool's scope. Baseline 3 is appropriate since schema already explains each parameter.

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 ('Search across ALL jurisdictions') and the resource ('US, EU, UK'), distinguishing it from sibling tools that are jurisdiction-specific (e.g., 'uk_legislation_search'). The phrase 'single call' and '7 legal databases, 4 jurisdictions' reinforces its unique value.

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 when broad multi-jurisdiction search is needed, contrasting with sibling tools that focus on single sources. However, it does not explicitly state when not to use or provide alternatives, so it is clear but lacks exclusions.

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 disclose behavioral traits such as read-only nature, authentication requirements, or side effects. It only mentions returning 'stable obligation IDs', but does not explicitly state it is a read-only operation or any other constraints, leaving gaps in 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 sentence that covers purpose, filters, and output without any wasted words. It is front-loaded with the main verb and resource, making it highly concise and efficient for an agent to parse.

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 mentions that the tool returns 'stable obligation IDs', which is helpful but minimal. Without an output schema, more detail on the result structure (e.g., if it includes metadata, pagination) would improve completeness. For a simple search tool, the description is adequate but not rich.

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 each parameter (topic, article, regulation) already having clear descriptions and allowed values in the input schema. The description adds no new information about parameters beyond what the schema provides, resulting in a baseline score.

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 searches regulatory obligations across specific regulations (DORA, MiCA, AMLR) and mentions filtering options. This distinguishes it from siblings like article_extract and obligation_trace, which handle different aspects of regulatory data.

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 searching for obligations under the named regulations, but it does not explicitly provide guidance on when to use this tool versus alternatives (e.g., obligation_trace for tracing relationships) or when not to use it. The context is clear but lacks explicit exclusions.

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 describes the trace output but does not state whether the operation is read-only, whether it has side effects, or any prerequisites (e.g., required permissions). The absence of safety or mutability information leaves transparency 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 extremely concise, using two succinct sentences to convey the tool's purpose, connections, and an optional parameter usage. Every sentence adds essential value without redundancy or verbose explanations.

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 complexity (tracing multiple entities) and lack of output schema, the description covers the trace components and system connections but does not describe the return format or data structure. It provides a reasonable overview but leaves some contextual gaps regarding the output.

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 context for 'entity_id' ('live Ampel status') but does not enhance understanding of 'obligation_id' beyond the schema. The value added is minimal, keeping the score at the baseline.

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: 'Full regulatory trace: Obligation → Control → Evidence → Finding.' It identifies the specific resource (regulatory chain) and the action (trace), and distinguishes itself from sibling tools like 'obligation_search' by focusing on the full chain rather than just searching obligations. The connection to LawOracle and DORA OS further defines its scope.

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 by noting 'Pass entity_id for live Ampel status,' but it does not explicitly state when to use this tool versus alternatives. There is no mention of when not to use it or comparisons to sibling tools like 'obligation_search.' While the context is clear, the lack of explicit exclusions or alternative guidance prevents a higher score.

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 offers minimal behavioral information beyond its purpose. For a simple ping, a brief description is acceptable but does not disclose any response expectations or side effects.

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 extremely concise, consisting of three words. It is front-loaded and contains no superfluous 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 no parameters, no output schema, and a trivial purpose ('connectivity test'), the description is fully adequate. No additional information 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?

The tool has zero parameters with 100% schema coverage. The description adds no parameter information, which is appropriate as there are no parameters to document.

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 'Quick connectivity test' is a specific verb+resource definition. It clearly states the tool is for testing connectivity, which is distinct from sibling tools that focus on document retrieval and searches.

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?

While no explicit when-to-use or alternatives are given, the sibling tools are all data retrieval operations, making it clear that ping is for connectivity testing. The context is implicitly clear.

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, and the description discloses only basic search and filter capabilities. It omits important behavioral details like rate limits, result ordering, pagination, or error behavior, leaving significant gaps for the 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, front-loaded sentence that is concise and covers the core action. It could benefit from a bit more structure but is not overly verbose.

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 search tool with 4 parameters and no output schema, the description provides minimal context. It lacks details on return values, pagination, or default behavior, making it barely adequate for agent 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 coverage is 100% so baseline is 3. The description mentions agency filtering and document types, which aligns with schema parameters but adds no new meaning beyond the schema 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 the tool searches Regulations.gov for proposed rules, final rules, and public comments, with agency filtering. This distinguishes it from sibling tools like federal_register_search and congress_bill_search, which target different sources.

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 Regulations.gov searches but does not explicitly guide when to use this tool over alternatives such as federal_register_search or provide criteria for exclusion.

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 discloses key behaviors: returns only recent 20 filings, accepts name or CIK. However, it omits details like error handling or result ordering, but for a read-only 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?

Two sentences, front-loaded with purpose, no redundancy. Every word adds 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?

The description specifies return fields (form type, date, description) and limit (20). Lacks mention of sorting or error states, but given low complexity and no output schema, it is reasonably 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?

Schema coverage is 100%, and the description adds concrete examples (e.g., 'Circle', '0001876042') that clarify parameter format beyond the schema 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 tool retrieves SEC filings for a company, specifies the input (name or CIK number), and notes it returns recent 20 filings. It distinguishes from sibling tools like sec_filing_search by focusing on a specific company.

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 versus alternatives (e.g., sec_filing_search). The description implies usage for company-specific filings but lacks when-not or comparative advice.

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 must disclose behavioral traits but only mentions full-text search and covered filing types. It omits details on authentication, rate limits, pagination, or response format (e.g., snippets or metadata). The phrase '4,000+ stablecoin results' is a specific data point but doesn't clarify general 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?

The description is short and front-loaded with the primary action and resource. However, the inclusion of '4,000+ stablecoin results' is a specific, possibly outdated detail that adds little general value, slightly reducing conciseness. Overall, it is efficient but not perfectly focused.

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 (2 optional parameters, no output schema), the description adequately states the scope and basic purpose. However, it lacks information on the output structure (e.g., relevance scores, snippets) and does not note any limitations or prerequisites, making it only minimally complete for an agent to 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?

The input schema provides 100% coverage for the two parameters (query and limit), including descriptions and default/max values. The description adds no additional semantic or format details beyond 'Full-text search', which is already implied by the 'query' parameter. Thus, it meets the baseline but doesn't enhance 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 'Full-text search across all SEC EDGAR filings', specifying the resource (SEC EDGAR) and action (search). It lists example filing types (10-K, 8-K, S-1, CORRESP) which helps distinguish it from sibling tools like sec_company_filings (which is company-specific) or court_opinion_search.

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 specific SEC filing types but provides no explicit guidance on when to use this tool versus siblings such as sec_company_filings or federal_register_search. No when-not or alternative references are included, leaving the agent to infer based on tool 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 are provided, so the description must fully disclose behavioral traits. It mentions the output (provisions count, XML/HTML links) but does not cover error handling, authentication needs, or what happens with invalid paths.

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, front-loaded with the main purpose, 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 tool's simplicity (one parameter, no output schema), the description covers the key return types. However, it could be slightly more detailed about the response structure or error behavior.

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 already describes the parameter thoroughly (path and URL example). The description adds no additional semantic value beyond what the schema provides, resulting in a baseline score.

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 ('Get') and resource ('UK act metadata and content URL') and states what it returns (provisions count, XML/HTML links). This clearly distinguishes it from the sibling search tool uk_legislation_search.

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 versus alternatives like uk_legislation_search. The description implies usage when an act path is known, but it lacks when-not or alternative recommendations.

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, and the description does not disclose behavioral traits like rate limits, authentication needs, or result format. It only says 'search' without indicating what is returned or how pagination works.

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 with no wasted words. It is appropriately sized and front-loaded with the core action.

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 and no annotations. The description does not explain what the search returns (e.g., list of titles, dates, links). For a tool with only two parameters, additional context on results is needed for 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 coverage is 100% with descriptions for both parameters (query and limit). The tool description adds no extra meaning beyond the schema, so baseline score 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 searches UK Acts of Parliament and Statutory Instruments via a specific source. It identifies the resource (UK legislation) and action (search), distinguishing it from siblings like eurlex_search (EU law) or regulations_gov_search (US).

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 on when to use vs when not. With siblings like eurlex_search and regulations_gov_search, explicit context such as 'For UK primary legislation only, not EU law' would help. The description only implies the source via 'legislation.gov.uk'.

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