StructureClerk

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 what the tool returns (frameworks, obligations, dimensions) but does not disclose any behavioral traits such as whether it uses external data, requires specific inputs beyond jurisdiction (which is in schema), or how the maturity assessment is computed. It also does not mention any limitations or side effects, leaving the agent underinformed about the tool's operation.

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

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

The description is a single sentence that efficiently packs the core purpose and output. It is front-loaded with the action and subject, and the listing of frameworks adds specificity without excess verbosity. It earns a 4 because it is clear and concise, though it could be slightly more structured (e.g., separating output from purpose) without adding length.

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 moderate complexity (2 parameters, no output schema, no annotations), the description provides a reasonable overview of outputs but lacks depth on the assessment process, the meaning of 'maturity,' and how to interpret the returned frameworks. It also does not clarify how this tool complements or differs from neighboring tools like compliance_roadmap. The presence of full schema coverage partially compensates, but the description alone is not fully comprehensive for an agent to know all practical usage scenarios.

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 covers both parameters (sector and jurisdiction) with descriptions, so the baseline is 3. The tool description does not add any additional meaning to the parameters; it does not explain how sector or jurisdiction affect the output beyond the schema's basic examples. The description is silent on parameter interactions, so no extra 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 action ('Assess algorithmic compliance maturity') and the specific subject ('AI systems'), and it lists concrete outputs (frameworks, sector-specific obligations, dimensions). It distinguishes itself from siblings like compliance_check (which likely checks specific compliance) and jurisdiction_map (which maps jurisdictions) by focusing on maturity assessment.

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 (when assessing compliance maturity for AI systems in a given jurisdiction) but does not explicitly state when not to use it or how it differs from sibling tools like compliance_check or compliance_roadmap. It gives context but no exclusions or alternative 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 burden of behavioral disclosure. It explicitly states that this is a deterministic, rule-based, non-LLM advisory tool, outlines the four possible decision outcomes, mentions that it cites applicable frameworks, and clarifies that it does not enforce. This is strong contextual disclosure beyond simply describing the action.

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 and front-loaded with the core purpose and possible verdicts. Each sentence adds unique information: decision type and outcomes, return content, and advisory vs. enforcement boundary. There is no unnecessary 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 tool is complex due to nested inputs and absence of an output schema and annotations. The description nonetheless provides a clear mental model of the decision output, the advisory role, the deterministic nature, and the evidence record. It could go further on details like how the verdicts map to specific input conditions, but it covers the most essential operational boundaries.

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 low, but the description does add meaning by framing the tool around an agent executing an action, with decisions based on jurisdictions and sector, and by referencing the evidence record. However, it stops short of explaining how specific inputs like autonomy_level or data_categories affect the output, so the description only partially compensates for the 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 identifies the tool as a decision function for whether an AI agent may perform an action, enumerating the exact verdicts (ALLOW, APPROVE, DENY, ESCALATE) and noting what it returns (framework citations, evidence record). It is specific about the resource and behavior, though it does not explicitly differentiate itself from the sibling tools by name.

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 this tool: whenever a deterministic, rule-based, advisory authority decision is needed with jurisdiction and sector input. It also states that it is advisory only and that enforcement is the infrastructure's job, but it does not provide explicit when-to-use/when-not-to-use guidance or name alternatives among the 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, the description must disclose behavioral traits. It states that it returns results but does not mention whether the operation is read-only, if it has side effects, requires permissions, or handles errors. The description lacks transparency about its behavior beyond the return value.

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, consisting of two sentences that directly state the purpose and outputs without unnecessary fluff. It is well-structured and easy to understand.

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 there is no output schema, the description lists the outputs (frameworks, risk level, priority actions), which is helpful. However, it does not explain the nature of these outputs, any limitations, or error conditions. It also does not specify input constraints beyond 'jurisdiction, size, sector'. The description is adequate but not fully 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?

The description mentions jurisdiction, size, and sector, which covers three of the five parameters (jurisdiction, company_size, sector). It does not explain the parameters 'uses_ai' or 'processes_personal_data'. The schema provides only examples for some, not full semantics. The description adds some meaning for the mentioned parameters but fails to cover all.

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 analyzes regulatory obligations based on jurisdiction, size, and sector, and lists the outputs (frameworks, risk level, priority actions). This differentiates it from sibling tools like compliance_roadmap or jurisdiction_map, which likely have different purposes.

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. It does not mention any conditions, prerequisites, or scenarios where this tool is preferred over the sibling tools. No explicit or implicit when-to-use information 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?

With no annotations, the description carries the full behavioral disclosure burden. It reveals that the output is a phased plan with cost estimates, but it does not explain how the plan is generated, what assumptions are made, whether it depends on jurisdiction, what output format is returned, or any limitations 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 a single, front-loaded sentence with no filler. Every phrase adds meaning: phased, compliance action plan, cost estimates, SME budgets. It is concise without sacrificing core 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?

For a tool with 5 parameters, no output schema, and no annotations, the description is too thin. It does not explain what kind of deliverable the user receives, how the plan is structured across phases, how cost estimates are derived, or what happens when required or optional parameters are missing. The one-sentence description leaves significant operational 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 80%, so the schema already documents most parameters. The description adds value by clarifying that 'budget' is interpreted in SME terms ('adapted to SME budgets'), but it does not elaborate on how sector, company_size, timeline_months, or jurisdiction influence the plan beyond what the schema states.

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 and resource: 'Generate a phased compliance action plan with cost estimates adapted to SME budgets.' It clearly conveys the tool's purpose and implies differentiation from the sibling tools like compliance_check and algorithmic_compliance_assessment, though it does not explicitly name an 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?

The description implies usage: you invoke this tool when you need a phased compliance action plan, especially for SMEs with budget constraints. However, it gives no explicit when-to-use/when-not-to-use guidance or references to sibling tools, leaving the decision boundary somewhat inferred.

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 of disclosure. It does mention the default behavior of returning all 192 jurisdictions when the parameter is omitted, but does not disclose the output format, rate limits, or any potential side effects. This 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 only two sentences, front-loaded with the primary purpose, and contains no 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 tool with one optional parameter, the description covers the essential behavior and the default case. However, since there is no output schema, it would benefit from a brief note on the structure of the returned regulatory frameworks, but this is a minor gap.

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 with ISO code examples and the omit-for-full-list instruction. The description repeats this behavior without adding additional meaning or clarification, so it offers no value beyond the schema.

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

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

The description states 'Get applicable regulatory frameworks for a jurisdiction' with a clear verb and resource. It also explains the behavior when the parameter is omitted, which distinguishes it from sibling tools like compliance_check or authority_decide that likely serve different purposes.

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 regulatory frameworks but does not explicitly mention when to use this tool versus alternatives or provide exclusions. It gives no guidance on prerequisites or when not to use it.

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