ai-compliance-monitor

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

With no annotations, the description carries the behavioral disclosure burden. It discloses that the tool returns deadlines with enforcement dates, penalty information, and related obligations, and implies a read-only operation. It does not cover pagination or response format, but for a query tool the disclosure is reasonably transparent.

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

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

The description is two sentences, front-loaded with the core purpose and immediately followed by useful detail. Every sentence earns its place 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?

Given no output schema, the description explains return content reasonably well (deadlines with enforcement dates, penalties, related obligations). It does not mention default parameter behavior, but those are covered by the schema. Sibling differentiation is implicit but not explicit, slightly reducing completeness.

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

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

Schema description coverage is 100%, so parameters are already well-documented. The description adds context about what the deadlines include (enforcement dates, penalties, related obligations) but does not add parameter-specific semantics beyond the schema. 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 'Returns upcoming and recent compliance deadlines' with specifics like enforcement dates, penalty information, and related obligations. This distinguishes it from sibling tools like check_obligations, which likely focuses on obligations rather than time-sensitive deadlines.

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 'Use this to understand time-sensitive compliance requirements' provides clear context for when the tool is appropriate. It does not explicitly mention alternatives or exclusions, but the temporal focus on deadlines versus other compliance aspects offers reasonable 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?

No annotations are provided, so the description carries the full burden of explaining behavior. It states the inputs (use case, optional jurisdiction) and the outputs (all applicable obligations with evidence requirements, enforcement dates, penalty information). It does not mention potential side effects or limitations, but for a read-only query tool, this is adequate. The description adds context that is not in the schema, such as the nature of the data returned.

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, each earning its place. The first sentence immediately states the function and returns, and the second sentence gives the use case. No unnecessary words or repetition. It is well-structured 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?

Given the tool has only 2 parameters, no output schema, and no annotations, the description effectively covers the purpose, inputs, and output content. It explains the types of information returned (evidence requirements, enforcement dates, penalties), which is essential since there is no output schema. It could mention edge cases like missing data or time requirements, but for a straightforward query tool, it is 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 input schema already describes both parameters thoroughly: use_case has examples, and jurisdiction_code explains it is optional and can be omitted. The description merely repeats 'AI agent use case and optional jurisdiction' without adding new parameter details. With schema coverage at 100%, the baseline is 3, and the description does not elevate it.

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's function: 'Given an AI agent use case and optional jurisdiction, returns all applicable regulatory obligations with evidence requirements, enforcement dates, and penalty information.' It uses a specific verb ('returns') and resource ('regulatory obligations'), and the second sentence clarifies the use case ('understand what compliance requirements apply'). This distinguishes it from sibling tools like check_deadline or compare_jurisdictions, which target different aspects.

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 a clear usage context: 'Use this to understand what compliance requirements apply to a specific type of AI agent.' It implies when to use the tool, though it does not explicitly mention alternatives or exclusions. Since sibling tools exist for related but distinct purposes, the description could have been more explicit about not using this for deadlines or comparisons, but the context is clear enough.

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 that the tool 'Shows equivalent, overlapping, stricter, and weaker mappings between regulations,' giving concrete insight into the output nature. It does not mention safety, but the read-only nature is implied by 'comparison' and 'shows,' which is adequate for this low-risk 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, front-loaded with the primary action and output. Every sentence adds value: the first states the function, the second details the output and use case. 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?

With no output schema and no annotations, the description compensates by explaining the nature of the output ('equivalent, overlapping, stricter, and weaker mappings'). It covers purpose, use case, and output content sufficiently for a simple two-parameter tool, though it could mention default behavior or limitations.

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 both parameters documented (category options and optional jurisdictions with default). The description adds only minimal semantic value by framing category as 'compliance category' and jurisdictions as 'across borders,' so a 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 compares regulatory obligations across jurisdictions for a compliance category, using a specific verb ('compare') and resource ('jurisdictions'). It distinguishes itself from sibling tools (check_deadline, check_obligations, get_regulation_articles) by emphasizing cross-jurisdictional mapping rather than deadline checking or article retrieval.

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

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

The description explicitly says 'Use this to understand how requirements differ across borders,' providing clear usage context. It does not mention when not to use it or explicitly name alternatives, but the context is sufficiently clear for an agent to select it over 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 provided, the description carries the full burden. It indicates a read operation via 'Returns' and enumerates content categories, but it does not disclose potential edge behaviors such as error handling, required permissions, or pagination. This is minimal but not misleading; a score of 3 is appropriate.

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 exactly two sentences, with the first sentence front-loading the core functionality and the second providing usage context. Every word earns its place 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?

For a simple retrieval tool with two parameters and no output schema, the description conveys the purpose, content scope, and usage context. It could be slightly more detailed about the exact structure of the returned data, but it is sufficiently complete for typical 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 description coverage is 100%, with both parameters (category and regulation_id) already described and enumerated in the schema. The tool description adds no extra meaning about parameters, 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 'Returns structured, machine-readable regulation details including specific articles, obligation classifications, risk levels, and evidence requirements.' This names a specific verb (returns) and resource (regulation details), and the mention of articles/obligations/risk levels distinguishes it from sibling tools like check_deadline or compare_jurisdictions.

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

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

The description explicitly says 'Use this to understand the detailed requirements of a specific regulation,' providing a clear context for use. However, it does not explicitly exclude alternatives or state when not to use it, so it lacks the full exclusion criteria of a score 5.

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