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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 does disclose useful behavior: missing inputs fall back to documented defaults, and it outlines the calculation outputs. It does not state whether the tool is side-effect free or describe error/validation behavior, leaving some behavioral uncertainty for a pure calculator.

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 with no filler; the action is front-loaded and the output list is compact. The semicolon-separated list is slightly dense but every element contributes useful information.

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 calculation tool with fully described optional parameters and no output schema, the description names the key computed outputs and the default-fallback behavior, which is enough to invoke it. It does not specify the exact response shape or calculation rules for statutory leave beyond the 12.07% formula, but the schema covers input 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 100%, so the schema already documents all 7 parameters. The description only adds a general 'missing inputs fall back to defaults' note and references hours worked and bank holidays; it does not add material meaning beyond the parameter descriptions.

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 resource (Statutory leave tracker calculator) and the action (Run), and enumerates what it computes: statutory leave, accrued hours at 12.07%, bank-holiday fill, and remaining days. It does not explicitly contrast with sibling calculator_describe, but the intended calculation role is unmistakable.

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 instruction to run the calculator implies use when a statutory-leave calculation is needed, and the mention of defaults gives practical context. However, it never states when not to use it or points to alternatives such as calculator_describe, so the guidance is only 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?

There are no annotations, so the description carries the burden. It tells the agent what content is available (inputs with units/ranges/defaults, outputs, assumptions/tables) but does not explicitly state that the tool is read-only, returns documentation text, or performs no calculation. Still, the name and empty schema make this low-risk.

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?

One compact noun phrase with no filler, front-loading the inputs and then listing outputs and assumptions. Every element 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 description tool with no parameters and no output schema, the definition covers the key content areas. It could be more explicit that this tool returns documentation rather than performing a calculation, but nothing critical is missing at this complexity.

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 is empty with 0 parameters, so the baseline is 4. The description adds value by stating that input units, ranges, and defaults are covered, which orients the agent to lookup purposes, even though those inputs are not this tool's own parameters.

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 identifies the artifact as covering the calculator's inputs, outputs, assumptions, and tables, and the title frames it as 'what the Statutory leave tracker computes.' This distinguishes it from the sibling calculate tool, though it lacks an explicit operational verb such as 'returns' or 'describes.'

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 when-to-use or when-not-to-use guidance is stated. It is only implied that this tool should be consulted before calling calculate to understand the calculator's inputs and outputs; it does not name alternatives or exclusions.

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 and meets it well. It explicitly states what does NOT happen ('nothing is bought, ordered or paid'), clarifies cost ('it is free'), and reveals the return contents (who receives details, consent wording, confirmation method). This is strong 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 three focused sentences with no wasted words. It front-loads the 'Read first' instruction, then quickly covers what the tool does, what it does not do, and what it returns. Every sentence 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?

Given the tool's low complexity (zero parameters, no output schema), the description provides enough context: it explains its purpose, its subject (submit_enquiry), its safety profile ('free', 'nothing is bought'), and the categories of information returned. It could be slightly more explicit about its own return format, but this is not a significant 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 tool has zero parameters and an empty input schema, so there are no parameter semantics to document. The baseline for zero-parameter tools is 4, and the description appropriately focuses on behavior and return value instead.

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 a specific action ('states plainly what submit_enquiry does') and names the exact resource and scope. It clearly distinguishes this from the related 'submit_enquiry' tool by explaining this is the read-first explanation, not the submission action itself.

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 contextual guidance to use this tool before taking action. It also identifies the target behavior (submit_enquiry) and what the tool will clarify. However, it does not explicitly discuss alternatives like enquiry_fields or when not to use this tool.

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 describes the content returned and implies a read-only listing, but it does not explicitly state that the tool has no side effects or that it only returns static field definitions. This is adequate but not fully explicit.

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 pack all essential information: what is returned and how to use it. There is no filler, redundancy, or unnecessary detail. The most useful information is front-loaded.

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 zero-parameter, no-output-schema tool, the description is complete. It enumerates the output fields and gives explicit downstream usage instructions. An agent knows exactly what to expect and how to act on it without needing more 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 has zero parameters and 100% schema coverage, so the baseline is 4. The description adds no parameter details because there are none, but it does explain how the output should be used to construct parameter keys for submit_enquiry.

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 what the tool provides: every field of the Leave Tracker enquiry with its key, label, type, required flag, help text, and allowed options. The title 'The questions the enquiry asks' reinforces the resource, and the phrase 'Pass answers to submit_enquiry keyed by field key' differentiates it from the submit_enquiry sibling.

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?

It gives explicit workflow guidance: after retrieving fields, pass answers to submit_enquiry keyed by field key. This tells the agent how to use the output in relation to a specific sibling. It does not mention when to use it versus enquiry_describe or calculate, but the primary alternative is addressed.

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 and does so richly: it discloses that step 1 only validates and returns a summary/consent line/token, that nothing is sent to providers until the person clicks an emailed link, that details go to up to three providers chosen by Leave Tracker, and that the person can halt further distribution. It also spells out the exact consent text, which is essential for knowing what consent=true actually attests to.

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 critical constraints ('NOT a purchase') are front-loaded and the two steps are sequenced clearly. The consent text is fully duplicated in the consent parameter's schema description, which is mild redundancy, and the final sentence is long, but each sentence still carries load-bearing information.

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?

There is no output schema, and the description compensates by describing what each call returns (a validated summary, the consent line, a confirmation token) and what happens after successful submission (email link the person must click before any provider sees the enquiry). For a two-phase, consent-sensitive workflow this is 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 coverage is 100%, so the baseline would be 3, but the description adds real meaning: answers are keyed by field key from enquiry_fields, consent must be true only after the quoted agreement, and confirmation is a token returned by step 1 and required only on the second call. That is operational guidance the schema alone does not supply.

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 names a specific verb and resource (submits an enquiry to Leave Tracker) and immediately scopes it with 'NOT a purchase, NOT a guaranteed quote', which prevents the most likely misclassification. It also names the sibling enquiry_fields as the source of the answer keys, so an agent can tell it apart from the calculator tools.

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?

It lays out an explicit two-call protocol: step 1 with answers + consent=true, then step 2 only 'if the person agrees', with the same answers plus the confirmation token. The gate condition (person approval of the summary) and the exclusion (not a purchase) are both stated outright.

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