regulatory-radar

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 mentions return values (compliance level, percentage, gaps, remediation priorities) but does not disclose side effects, authentication needs, or prerequisites like the payment_ref parameter implying a paid service. The description is too minimal for full 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 extremely concise at two sentences, with the first sentence clearly stating the purpose and the second listing the outputs. It is front-loaded and free of 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 complexity (6 parameters, including payment_ref and disclosures), the description is incomplete. It lacks parameter explanations, usage context, and does not clarify how inputs like sector and jurisdiction affect the assessment. The presence of an output schema is not leveraged in the description.

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 0%, yet the description adds no information about any of the 6 parameters, including required ones like company_name, sector, and jurisdiction. The agent must infer their meaning from names alone, which is insufficient for correct invocation.

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: assess a company's compliance posture against regulations. It specifies the resource (company's compliance posture) and the verb (assess), making it distinct from sibling tools like scan_regulations, which focus on regulations themselves.

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 its siblings, such as scan_regulations or describe_agent. There are no explicit when-to-use or when-not-to-use instructions, leaving the agent without context for selection.

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

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

With no annotations, the description carries full burden. It transparently states that the tool returns capabilities, inputs, and outputs. For a simple read-only self-description, this is adequate and does not require more behavioral disclosure.

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 redundancy. Every word adds value, and it is efficiently structured for quick comprehension.

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

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

Given zero parameters and the presence of an output schema, the description fully covers the tool's purpose. It tells the agent exactly what the tool provides, and the output schema will detail the 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?

There are zero parameters, so the baseline is 4. The description does not need to add parameter-level detail, and it meaningfully explains the tool's purpose beyond the empty 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 is a self-description tool that outputs capabilities, inputs, and outputs. It uses specific verbs and resources, and the hyphenated 'Fleet-standard' helps distinguish it from sibling tools like assess_compliance and scan_regulations.

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 introspection but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is provided, 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, so the description must carry the full burden. It only says 'monitor', which suggests read-only but is not explicit. No disclosure of side effects, authentication needs, rate limits, or idempotency. For a monitoring tool, agents need to know if it's safe to call repeatedly.

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 with no fluff, but it achieves conciseness at the expense of completeness. It could be restructured to include parameter hints or usage notes without becoming 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?

With 4 parameters, 0% parameter description coverage, no annotations, and an existing output schema, the description provides insufficient context for correct invocation. It does not explain the trailing window behavior, parameter defaults, or 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 0%, yet the description only mentions 'jurisdiction'. It does not explain 'since_days' (likely the trailing window length), 'request_id', or 'payment_ref'. The description fails to add meaning beyond the parameter names.

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 monitors recent regulatory changes in a jurisdiction over a trailing window, using a specific verb and resource. It distinguishes from siblings like 'assess_compliance' (evaluation) and 'scan_regulations' (broader 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 ongoing monitoring via 'trailing window', but lacks explicit guidance on when to use this tool vs alternatives or any exclusion criteria. No context about prerequisites or limitations.

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 covers pricing ($0.25/call after 10 free calls), payment method (Base USDC, payment_ref), and endpoint path. However, it does not disclose rate limits, idempotency, or authentication requirements beyond payment 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?

The description is relatively short (two sentences plus pricing) and front-loaded with the core purpose. However, the pricing and payment details add clutter that could be moved to annotations or separate documentation, reducing overall conciseness.

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 return values (regulations with urgency flags and effective dates), and the output schema exists. Yet, it lacks details on parameter meanings for request_id and payment_ref, and does not reference the output schema to agents, making it moderately 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 description clarifies 'jurisdiction' and 'sector' parameters by giving examples (EU, US, etc.) and mentioning optional sector filtering. However, 'request_id' and 'payment_ref' are not explained; payment_ref is only referenced in payment instructions without defining its role as a 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 verb 'scan' and the resource 'regulations' with a specific jurisdiction, and optionally filtered by sector. It distinguishes from siblings like 'assess_compliance' and 'monitor_changes' by focusing on raw regulatory scanning.

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 scanning regulations by jurisdiction and sector, but does not explicitly state when to use this tool versus alternatives or provide exclusions. The sibling tools offer different functionalities, but no direct comparison is made.

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