law

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

With no annotations, the description carries the burden of disclosing behavior. It states that the tool returns certain types of information, implying a read-only operation, but does not explicitly mention read-only status, required parameters, or limitations. It adds some value beyond a bare name but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence of 14 words that front-loads the primary action and scope. Every phrase adds meaning. No filler or duplication.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, and the description lists return types but not structure. It also does not address the fact that both parameters are optional (required params = 0) or explain how to use them together. Given the tool's narrow scope, the description is adequate but incomplete for edge cases.

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%; both parameters ('article', 'regulation') are already documented with examples. The tool description adds no additional parameter context, so the schema handles semantics fully.

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 ('extraction') with a clear resource ('EU regulations') and scope (DORA, MiCA, AMLR). It states what is returned (obligations, delegated acts, cross-jurisdiction equivalents), which distinguishes it from sibling tools like eurlex_search (search) and de_law_lookup.

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 article-level extraction from EU regulations but provides no explicit guidance on when to use it versus alternatives or when not to use it. No sibling tool is mentioned for comparison.

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

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

With no annotations provided, the description carries the full burden. It discloses what the tool returns (sponsors, status, committees, text) but does not mention potential side effects, authentication requirements, or behavior with invalid/absent parameters. It is a minimal but not misleading description.

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 front-loads the core action ('Get detailed bill information') and then lists key content categories. 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 detail-retrieval tool with 3 parameters and no output schema, the description adequately communicates what to expect (bill details including the listed fields). However, it omits guidance on how to specify a bill beyond the schema and does not reference the search sibling, leaving minor gaps in operational 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?

The input schema provides 100% coverage for the three parameters (number, congress, bill_type) with descriptions including defaults. The tool description adds no additional parameter semantics 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?

The description clearly states the tool's function ('Get detailed bill information') and enumerates the specific content (sponsors, status, committees, text). This distinguishes it from sibling tools like congress_bill_search, which is for searching bills.

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 this tool is for retrieving details about a specific bill, but it does not explicitly state when to use it versus congress_bill_search. There is no mention of prerequisites or alternatives, leaving usage context 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 carries the full burden of behavioral disclosure. It only states 'Search' which is already in the tool name, and offers no information about result format, pagination, rate limits, or any access requirements. The phrase 'Track...' could imply ongoing monitoring rather than a one-time search, which is potentially misleading.

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 short sentences, immediately stating the purpose and a use case. There is no filler or redundant information, making it easy 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?

For a simple search tool with only 2 parameters and no output schema, the description gives the core purpose and a relevant use case. However, it lacks detail about what results look like, any default behavior (e.g., query required), or limitations, which is a notable gap given the absence of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers 100% of the parameters with descriptions, so the baseline is 3. The description adds example topics like 'stablecoin' and 'digital asset' which indirectly enrich the query parameter, but it does not provide any additional parameter-level detail 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 'Search US Congressional bills', which is a specific verb and resource. It distinguishes from sibling tools like court_opinion_search, eurlex_search, and uk_legislation_search by identifying US Congressional bills as the target. Adding 'stablecoin, crypto, financial regulation bills' further narrows the use case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The second sentence 'Track stablecoin, crypto, financial regulation bills' provides clear context for when the tool is relevant. However, it does not explicitly state when not to use it or mention alternative tools, so it stops short of a full usage guideline.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about the data source and court coverage, but does not explicitly state that the operation is read-only, nor does it mention pagination, result limits, or any side effects. The description is adequate for a search tool but lacks deeper behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the primary action, and consists of two sentences with no redundant information. Every phrase contributes value: 'Search 1.1 million+ US federal and state court opinions via CourtListener' and the coverage note.

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 provides the essential context (source, scope, coverage) but omits the fact that the tool also supports docket search via the 'type' parameter, and it does not describe the response format (no output schema exists). These gaps make it incomplete for a tool with optional parameters and no return value documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all three parameters (type, limit, query), so the baseline is 3. The description adds context regarding the scope and source of the search, which indirectly informs the 'query' parameter, but it does not add new parameter-specific 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 uses a specific verb ('Search') and clearly identifies the resource ('US federal and state court opinions') with a distinct scope ('1.1 million+', 'Covers Supreme Court, Circuit Courts, District Courts'). It also names the data source (CourtListener/Free Law Project), which differentiates it from sibling tools that may cover different jurisdictions or 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 clearly implies when to use this tool: when searching for US court opinions. It provides context about the coverage and source, but does not explicitly mention alternatives or when not to use it. Nonetheless, the context is clear enough for an agent to select this tool over unrelated 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?

With no annotations, the description carries the full burden. It discloses that the tool lists 'indexed' laws, indicating a read-only operation and a constraint on which laws are returned. However, it does not mention output format, exhaustiveness, pagination, or any side effects. For a simple list tool, this is adequate but lacks rich behavioral detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the action ('List') and resource with examples. Every word earns its place, and there is no redundancy or filler.

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 no-parameter, no-output-schema listing tool, the description provides the essential information: what is listed and the relevant domain. It could optionally mention output details (e.g., alphabetical order or list format), but the tool's simplicity makes the description sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the description does not need to explain parameter semantics. The baseline for 0 parameters is 4, and the description adds context about what is being listed, which is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'List indexed German federal laws relevant to financial regulation' with specific examples (KWG, WpHG, GwG, ZAG). The verb 'List' and resource 'German federal laws' are specific, and the scope distinguishes it from siblings like de_law_lookup or 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?

The description implies the use case (listing German financial regulation laws) but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions. The context is clear, but there is no guidance on when not to use it, unlike the high-calibration example which explicitly named an alternative.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only says 'get metadata and links', implying a read operation, but does not explain behavior for invalid abbreviations, whether the law must be exactly one of the supported abbreviations, or any other operational nuances. This is minimal disclosure for an unannotated 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, clear, front-loaded sentence. Every word earns its place; there is no extraneous verbiage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema and no annotations, so the description must provide fuller context. It identifies the basic purpose but omits how the agent should obtain the law abbreviation, when to prefer sibling tools (like de_law_list), and what kind of metadata/links to expect. This is insufficient for seamless tool selection.

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%: the 'law' parameter lists all valid abbreviations. The description adds no information about the parameter beyond the schema, so the baseline of 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?

The description clearly states the tool fetches metadata and links for a specific German federal law, using a specific verb ('get') and resource. It distinguishes from sibling tools like de_law_list, which lists laws, but doesn't explicitly name that alternative.

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. The description does not mention that de_law_list should be used to enumerate laws or that this tool is for known abbreviations. Usage context is only implied by the word 'specific'.

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

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

With no annotations provided, the description carries the burden of disclosure. It adds that the search is via SPARQL, explicitly lists what it returns (CELEX numbers and links), and implies read-only behavior through 'search.' This goes beyond the bare schema, though it does not discuss potential pagination or filtering nuances.

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 the core purpose and followed by scope and output details. Every sentence contributes meaningful information with no redundancy or filler.

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 covers the main purpose, document types, and return values, which is sufficient for a simple search tool with only two optional parameters. It does not explain sorting or error handling, but these are not critical for basic invocation. The absence of an output schema makes the explicit mention of CELEX numbers and links particularly useful.

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 both parameters described, but the description adds value by providing concrete search-term examples ('Markets in Crypto', 'Digital Operational Resilience') that illustrate expected query formats. This exceeds the baseline of 3 for fully documented schemas.

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 tool searches EU legislation via EUR-Lex SPARQL, specifies relevant document types (regulations, directives, decisions), and notes the output (CELEX numbers and links). This distinguishes it from sibling tools like court_opinion_search or federal_register_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 keyword-based EU legislation searches and gives concrete query examples, but it does not explicitly state when to prefer this over alternatives or mention exclusions. It provides clear context but no direct comparison with 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?

With no annotations provided, the description carries the full burden of disclosing behavior. It states that it returns the 'full' document, implying a read-only operation, but does not elaborate on return format, error handling, or other details. This is adequate for a simple retrieval tool 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 a single, front-loaded sentence with no filler. It conveys the essential information efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and no output schema, the description is sufficiently complete: it identifies the input and the nature of the output ('full document'). It could mention that the number comes from federal_register_search, but this is not essential 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?

The schema already provides 100% coverage for the single parameter, including an example. The description merely restates 'by document number' without adding additional meaning, so it aligns with the baseline 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 the tool's function: retrieving a full Federal Register document by its document number. The verb 'Get' is specific and the resource is identified, distinguishing it from sibling tools like federal_register_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 context of use is evident: this tool is used when you have a document number and need the full document. While it does not explicitly mention alternatives, the input requirement makes the usage scenario 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?

With no annotations provided, the description carries the burden of explaining behavioral traits. It states it 'covers all federal agencies' and lists examples, which provides scope context. However, it does not describe output format, pagination behavior, or any side effects (though a search is inherently read-only). The description is 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 with no filler. It front-loads the action and resource, then provides useful detail about covered document types and agencies. 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?

For a simple search tool with two well-described parameters, no output schema, and no annotations, the description is fairly complete. It conveys the core purpose, document scope, and agency coverage. It lacks explicit guidance on result behavior, but that is less critical for a search tool and could be inferred from the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for both parameters (limit and query), and each has a clear schema description. The tool description does not add any parameter-specific detail beyond the schema, so the baseline of 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?

The description uses a specific verb ('Search') and resource ('US Federal Register') with clear scope ('rules, proposed rules, and notices'). It also names covered agencies, which distinguishes it from sibling tools like federal_register_document (likely a document fetcher) and regulations_gov_search (a different registry).

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 clear usage context: searching across the Federal Register for rulemaking documents. It mentions coverage of all federal agencies, which helps the agent know its breadth, but it does not explicitly state when to use this tool versus alternatives like federal_register_document or regulations_gov_search.

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

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

Without annotations, the description carries the full burden of behavioral disclosure. It transparently lists the categories of information returned (cache stats, API key status, source count), giving a clear sense of what the agent can expect. However, it does not explicitly state that the operation is read-only or side-effect-free, though this is strongly 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 a single, concise sentence that front-loads the core purpose ('Server status') and adds specific detail without redundancy. Every word contributes 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?

Given the tool has no parameters and no output schema, the description provides a reasonable level of detail about what the tool returns. It could be slightly more exhaustive by mentioning whether authentication is needed or if the call is rate-limited, but for a simple health check, this is largely 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?

With zero parameters, the schema is empty and the description needs to add no parameter-level detail. The baseline for 0 params is 4, and the description appropriately focuses on the output rather than inputs, which is sufficient here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: checking server status with specific details (cache stats, API key status, source count). It uses a specific verb+resource construction and naturally distinguishes itself from sibling 'ping', which likely only provides a basic liveness check.

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 explicit guidance on when to use this tool versus alternatives like 'ping'. It does not mention any exclusions or conditions, leaving the agent to infer usage solely from the tool name and description.

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 responsibility. It indicates a read-only listing operation but does not disclose return format, pagination, rate limits, or other behavioral traits. For a zero-parameter listing tool, this is adequate but not richly transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single compact sentence that conveys the essential purpose without redundancy. It is well-structured and front-loaded with the action and target.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema, no annotations), the description sufficiently explains what the tool returns. It could be improved by noting that it serves as a reference before using jurisdiction-specific tools, but it is otherwise complete for its scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema fully covers this (100% coverage). The baseline for zero parameters is 4, and the description adds no parameter-specific detail because there is nothing to add.

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 ('List') and the resource ('supported jurisdictions, data sources, and their capabilities'). It distinguishes itself from sibling search tools by explicitly being a listing/reference tool.

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/data sources but provides no explicit guidance on when to use it versus alternatives. No exclusions are given, so it's a minimum viable score for implied usage.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context about the scope (7 databases, 4 jurisdictions) and the 'one query' behavior, but does not confirm whether the operation is read-only, how results are aggregated, or any potential limitations. It is not misleading, but it lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with the primary purpose. The phrase 'The killer feature' is somewhat promotional and adds no technical value, but the text remains concise and readable overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no annotations, the description provides a clear high-level purpose but omits details about the response format, error handling, or any constraints. Given the simplicity of the search tool, it is adequate but not fully complete for an agent to anticipate the exact 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?

Schema description coverage is 100%, with each parameter (query, jurisdictions, max_per_source) documented in the schema. The description adds no parameter-specific meaning beyond what the schema already provides, so the baseline score of 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?

The description states the tool performs a cross-jurisdiction legal search ('Search across ALL jurisdictions (US, EU, UK) in a single call') and highlights its unique scope ('7 legal databases, 4 jurisdictions'). This clearly distinguishes it from siblings like eurlex_search or uk_legislation_search, which are single-jurisdiction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Search across ALL jurisdictions' implies the tool should be used when multi-jurisdiction coverage is needed, and the mention of 'single call' indicates it consolidates multiple sources. However, it does not explicitly state when to prefer this over individual jurisdiction-specific tools or provide exclusions, so it falls short of full guidance.

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

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

With no annotations, the description carries the full burden. It discloses the read-only nature via 'Search' and mentions the output ('stable obligation IDs'), but it does not explain pagination, authentication, or any constraints. This is adequate but 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 two concise sentences that cover purpose, filters, and return value. Every sentence adds value and no words are wasted.

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 3-parameter search tool with no output schema, the description covers the key essentials: scope, filters, and output type. It could be enhanced by mentioning how returned IDs can be used with related tools like obligation_trace, but it is otherwise 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 description coverage is 100%, so the parameters are already fully documented in the schema. The description merely paraphrases these filters ('regulation, topic, or article') without adding extra meaning or format details, matching the baseline for high 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 the tool's function: 'Search regulatory obligations across DORA, MiCA, AMLR.' The verb 'search' is specific, and the resource is uniquely defined by the regulation names. It does not explicitly name sibling tools for differentiation, so it misses a perfect score.

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 context for when to use this tool: when needing regulatory obligations from DORA, MiCA, or AMLR, with optional filters. It does not mention exclusions or alternative tools such as obligation_trace, so no when-not-to-use guidance 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, so the description carries the transparency burden. It discloses cross-system connectivity and an optional live status lookup, which provides some behavioral context. However, it does not state whether the tool is read-only, whether permissions are required, or what side effects might occur, so gaps remain.

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 with no filler. It front-loads the core purpose and ends with a practical parameter tip, making it concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has two optional parameters, no output schema, and a cross-system scope, yet the description does not clarify whether at least one parameter is required, what the returned trace looks like, or how to interpret the results. This leaves significant gaps for an agent to use the tool 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%, and the description adds only a brief note about entity_id for 'live Ampel status,' which largely duplicates the schema's own description. The description does not add significant semantic value beyond the schema, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs a 'Full regulatory trace' through a defined chain (Obligation → Control → Evidence → Finding), which distinguishes it from sibling tools like obligation_search. It also specifies the integration between LawOracle and DORA OS, making the tool's purpose specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (for regulatory tracing) but does not explicitly name alternatives or exclusion criteria. The phrase 'Pass entity_id for live Ampel status' is more of a parameter tip than a usage guideline, leaving the tool's selection context largely implicit.

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

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

No annotations are present, so the description carries full burden for behavioral disclosure. 'Quick connectivity test' merely restates the tool's name (ping) without explaining what it returns, whether it makes a network call, or any side effects. This is essentially a tautology.

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 words long, immediately front-loaded with the core purpose. Every word is meaningful, though 'quick' is a minor filler. It is an appropriate size for a tool this simple.

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 that the tool has no parameters, no annotations, and no output schema, the description is minimally viable but lacks details about the return value or behavior beyond 'connectivity test.' It is adequate for a trivial tool but leaves room for ambiguity (e.g., whether it returns status, latency, or just throws errors).

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 0 parameters, so the baseline is 4. The description does not need to add parameter information, and no schema details required elaboration.

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' clearly states the tool's function with a specific verb ('test') and resource ('connectivity'). It distinguishes itself from sibling tools, which are legal/regulatory search utilities, by indicating it is a simple network/API connectivity check.

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 such as 'health_check' or other sibling tools. There is no mention of use cases, exclusions, or prerequisites, leaving the agent to infer 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?

No annotations are provided, and the description is minimal, only stating the search action and filter capability. It does not disclose return format, pagination, authentication requirements, or safe-read nature, which is expected when annotations are absent.

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 clearly states the tool's purpose. 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?

Without an output schema, the description should clarify what the search returns (e.g., list of documents, metadata). It does not, and with no annotations, the description is incomplete for guiding an agent on expected results and 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?

Schema description coverage is 100%, with all four parameters (limit, query, agency, doc_type) already described in the input schema. The description adds no additional parameter meaning, 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?

The description clearly states the tool searches Regulations.gov for specific document types (proposed rules, final rules, public comments) and supports agency filtering. It is specific but does not explicitly differentiate from sibling search tools like federal_register_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—use for searching Regulations.gov—but provides no explicit when-to-use or alternative guidance. It does not mention exclusions or when to prefer 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?

No annotations are provided, so the description carries the full burden. It discloses the return format (recent 20 filings with form type, date, description) but includes an internal contradiction between 'all' and 'recent 20', and does not mention error behavior, pagination, or authentication needs. This undermines 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 two sentences, front-loaded with the primary purpose and followed by the return summary. Every word is informative, with no filler or 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?

The tool is simple (one parameter, no output schema), and the description mentions return fields. However, the 'all' vs 'recent 20' inconsistency and the mismatch between the schema (company not required) and description (implies company is needed) leave important gaps. It is minimally complete but not fully coherent.

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 echoes the schema's 'name or CIK number' but adds no additional format details or constraints beyond the example already in the schema. No extra semantic value is provided.

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 by name or CIK number, but the phrase 'Get all SEC filings' conflicts with 'Returns recent 20 filings', creating ambiguity. It is distinct from sibling tools like sec_filing_search due to the company-focused scope, though not explicitly differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance provided on when to use this tool versus alternatives such as sec_filing_search. The intended use case (getting recent filings for a known company) is implied but not stated, and no exclusions or alternative scenarios 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?

With no annotations, the description carries full responsibility for disclosing behavioral traits. It only describes the scope (full-text, all filings) and lists forms, but does not mention that this is a read-only operation, rate limits, result ordering, or any side effects. The irrelevant '4,000+ stablecoin results' adds confusion rather than 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 only two sentences and front-loaded with the main purpose. However, the second sentence contains '4,000+ stablecoin results,' which is irrelevant to the tool's general function and wastes space, potentially misleading users. It should be removed or replaced with more useful context.

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 2 well-documented parameters and no output schema, the description covers the basic scope. However, it lacks any comparison to sibling tools (especially sec_company_filings), omits expectations about result format, and includes an odd stablecoin stat that introduces 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 description coverage is 100% (both 'query' and 'limit' have clear descriptions). The description adds no new parameter-level meaning beyond the schema; 'full-text search' already implies the query is a text term. Thus 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 performs 'Full-text search across all SEC EDGAR filings' and lists specific form types (10-K, 8-K, S-1, CORRESP). This is a specific verb+resource that distinguishes it from more general search tools, though not explicitly from the sibling sec_company_filings.

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 intended use is implied: use for full-text search across all SEC EDGAR filings. However, there is no explicit guidance about when to use this tool versus alternatives like sec_company_filings, nor any exclusions or prerequisites. The form-type coverage provides some context but no direct comparison to 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 are provided, so the description carries full responsibility. It discloses that the tool returns metadata, a content URL, provision count, and XML/HTML links, which are helpful output details. However, it does not mention potential errors, required permissions, or whether the path must be valid, leaving some behavioral 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 two short sentences, front-loaded with the core purpose and then adding return details. Every word is useful, with no wasted space or 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?

Given its simplicity (one parameter, no output schema), the description is adequate but thin. It explains what it returns and mentions the content URL, but it does not explicitly state that the act_path parameter is needed to identify an act, nor does it mention error cases or navigate the optional-parameter oddity (required: 0). The tool is simple enough that this is a minor gap, but it prevents 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% and the parameter description includes an example ('ukpga/2023/29'), so the schema already carries the semantic weight. The tool description adds no additional parameter guidance beyond what the schema provides, hence the baseline score of 3.

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 clearly distinguishes from sibling tools like uk_legislation_search by focusing on a single act's metadata rather than searching. It also states what is returned (provisions count, XML/HTML links), making the purpose unambiguous.

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 (e.g., uk_legislation_search or other jurisdiction-specific lookups). No context or exclusions are mentioned, leaving the agent to infer appropriate usage from 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?

With no annotations, the description carries the burden of behavioral disclosure. It states this is a search operation via a specific external source, but does not explain response format, pagination, rate limits, or any limitations. The safe read-only nature is implied by 'search' but not explicitly stated.

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 conveys the tool's purpose, scope, and source without any redundant information. 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 search tool with no output schema and no annotations, the description is functional but not complete. It states what is searched and via what source, but does not describe the response content, how to structure queries for best results, or relationship to sibling tools. The absence of an output schema places a heavier burden on the description to explain return values, which it does not.

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?

Both parameters are already fully described in the schema (query as 'Search term' and limit as 'Max results'). The description adds no additional meaning about how to format the query or interpret results, so the baseline score of 3 for 100% schema coverage 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 states the action ('Search'), the resource type ('UK Acts of Parliament and Statutory Instruments'), and the source ('legislation.gov.uk'). This distinguishes it from sibling tools like eurlex_search (EU) and congress_bill_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?

The description provides clear context: this tool is for searching UK primary and secondary legislation. It does not explicitly mention alternatives or when-not-to-use, but the context itself implies suitable usage scenarios. A brief note about using uk_act_content for retrieving specific act content would have earned a 5.

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