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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose one useful behavior—missing inputs fall back to documented defaults—and the calculator framing implies a non-mutating computation, but side-effect status, prerequisites, and return format are left unspecified.

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: it states the action first, follows with a tight output list, and closes with a single behavioral note. No phrase is wasted, though the output list is somewhat dense.

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

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

Given no output schema and no annotations, the description lists the computed result areas but does not define domain terms like 'fixed week' or 'two-week window', nor explain the output format or return shape. It is adequate for simple calls with defaults but leaves an agent guessing on 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%, with each of the five parameters having its own default, range, and explanation, so the baseline is 3. The description adds only a generic statement about default fallback, which is already visible in 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 ('Run') and names the exact resource ('Driver capacity planner calculator'), then enumerates four distinct capacity outputs. This clearly places the tool as the computation entry point relative to the describe/enquiry siblings, though it does not explicitly contrast it with them.

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?

There is no explicit guidance on when to use this tool versus alternatives like calculator_describe or enquiry tools. The output list implies a capacity-planning use case, but selection context and exclusions are left to inference.

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 describes the calculator's behavior but does not disclose the tool's own output format (e.g., plain text, JSON) or that it is a read-only operation. The tool's side effects and return structure are unmentioned.

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 purpose and enumerates the covered topics (inputs, outputs, assumptions, tables). Every word contributes to the meaning without 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 no-parameter describe tool with no output schema, the description is largely complete: it tells the agent what the tool does. The only missing detail is the return format, but given the trivial nature of the tool, this is a minor gap. Annotations could have added safety hints but are absent.

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

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

The input schema has zero parameters, and schema description coverage is 100% (trivially). The description does not need to add parameter details since none exist. The baseline for 0 parameters is 4, and the description adds no extra meaning 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 explicitly states that the tool describes the calculator's inputs, outputs, assumptions, and tables. It clearly identifies the resource (Driver capacity planner calculator) and the verb (describe) is implied by the name and context. It distinguishes from siblings like 'calculate' and 'enquiry_describe' by naming the specific calculator.

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 is given on when to use this tool versus alternatives such as 'calculate' or 'enquiry_describe'. The usage is implied by the name, but the description does not state exclusions or conditions for choosing this tool over others.

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

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

With no annotations provided, the description carries the full burden of disclosing behavior. It clearly states that this tool returns information about who receives the details, consent wording, and confirmation method, and clarifies that nothing is bought or paid for. This transparently sets expectations for a read-only, informational tool without 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 concise and well-structured. It opens with 'Read first' to signal priority, then states the purpose, clarifies what it does not do, and lists the returned information. Every sentence contributes to understanding the tool's function and output, 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 tool with no parameters and no output schema, the description fully covers what the tool does and what it returns. It explains the context of submit_enquiry and specifies the output items (who receives details, consent wording, confirmation method). This is complete for an agent to understand and call the tool appropriately.

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 coverage is 100% (since the schema is empty). The description correctly omits any parameter information, and the baseline for 0 params is 4. The description doesn't need to compensate for any parameter gaps.

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

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

The description clearly states that this tool describes what submit_enquiry does on the Drivers' Hours Calculator, specifying the verb 'states' and the resource. It differentiates from siblings like submit_enquiry by explicitly positioning itself as the descriptive counterpart.

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 opening 'Read first' gives clear usage context, implying that this tool should be consulted before using submit_enquiry. It also clarifies what the underlying tool does (not a purchase, no guaranteed quote), which helps the agent decide if this is the right tool to understand the process. However, it does not explicitly name alternative tools like enquiry_fields or calculator_describe, so it relies on implicit context.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It precisely lists the returned attributes (key, label, type, required, help, options) and implies a read-only operation, though it never states 'read-only' explicitly. For a metadata retrieval tool, this is adequate 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 with zero fluff. The core behavior is front-loaded, and the note about submit_enquiry adds value without redundancy. Highly efficient.

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

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

Given no parameters and no output schema, the description fully specifies what the tool returns and how to use the result. It covers the output structure (list of fields with attributes) and the downstream usage, making it complete for the tool's simple purpose.

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

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

The tool has zero parameters, so the description correctly omits parameter explanations. Baseline for 0 params is 4, and no additional parameter semantics are needed.

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

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

The description clearly states the tool returns every field of the Drivers' Hours Calculator enquiry, enumerating key, label, type, required flag, help text, and allowed options. This is specific and distinct from siblings like calculate or submit_enquiry, leaving no ambiguity about the tool's function.

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 connects the tool to submit_enquiry by instructing to pass answers keyed by field key, which signals when to use it (as a prerequisite). However, it does not mention alternatives or when not to use it, so it stops short of full routing 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, so description carries full burden. It discloses the two-step validation, returned summary/consent line/token, and email confirmation before provider visibility. However, it instructs consent=true in step 1 before agreement, contradicting its own stated meaning of consent, creating behavioral ambiguity.

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?

Front-loads purpose and steps, but repeats the full consent text already present in the schema's consent description, and includes the contradictory consent instruction. Still dense with little 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?

No output schema, so description must explain returns; it does (summary, consent line, token, email link). Covers the full flow, though the consent contradiction leaves a gap in correct invocation.

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 fully documents the three parameters. The description adds procedural context (token from step 1, answers from enquiry_fields) but critically instructs consent=true in step 1, contradicting the schema's 'true only when the person has agreed,' which could cause misuse.

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?

States a specific action (submits an enquiry) and explicitly rules out being a purchase or guaranteed quote, making it distinct from purchase-related siblings. The two-step nature is clear from both title and description.

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?

Provides detailed step-by-step invocation: step 1 with answers and consent, step 2 only after approval with token. It references enquiry_fields for field keys, but doesn't explicitly compare to alternatives like calculate.

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