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

There are no annotations, so the description must carry the transparency burden. It does disclose one useful behavior: missing inputs fall back to documented defaults, and it lists the values the calculator produces. However, it does not explicitly state that the operation is read-only, nor describe what happens on invalid inputs, so some behavioral context is missing.

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 and front-loads the command, but it contains a redundancy ('calculator, 2026/27 calculator') and uses a choppy semicolon list. The content is useful, but the phrasing is not polished enough for a higher score.

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 calculator with three optional parameters, the description covers the main purpose and default behavior. But since there is no output schema, it only names the output concepts without describing the response format or edge-case behavior, leaving some ambiguity for an agent invoking the tool.

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 parameters are already documented in the input schema (payDay, payMonth, payMethod). The description adds only a general default-fallback note and no parameter-specific insight, which matches the baseline of 3.

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 action ('Run the PAYE deadline calculator') and names the concrete outputs: HMRC payment date, FPS submission, tax month, and EPS deadline. This clearly states what the tool does, though it never explicitly distinguishes it from sibling tools like calculator_describe.

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 given for when to choose this tool over the sibling tools; calculator_describe and the enquiry tools are never mentioned. The only usage-adjacent note is about fallback defaults, which does not help an agent decide between alternatives.

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 behavioral burden. It discloses what the tool offers: inputs with units/ranges/defaults, outputs, assumptions, and underlying tables. This effectively communicates that it is a descriptive/documentation tool with no visible mutation or external side effects, though it does not explicitly state 'read-only' or 'does not calculate'.

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 focused sentence that lists exactly what the tool covers without redundant wording. It front-loads the inputs, then outputs, then assumptions/tables, and every phrase adds useful information. The title supplies the specific calculator context, keeping the description tight.

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 describe tool with no output schema, the description gives a solid outline of what the agent receives: inputs, outputs, assumptions, and tables. It could be slightly more explicit that the result is a descriptive text/documentation rather than a computed result, but given the tool name and siblings, this is not a major 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, so the schema provides no parameter meaning and the baseline is 4. The description adds context by noting that the subject calculator's inputs include units, ranges, and defaults, which is helpful for an agent deciding what to learn from the describe output. It does not need to document invocation parameters since there are none.

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 title and description clearly identify the resource: the PAYE deadline calculator 2026/27. The description states it covers the calculator's inputs, outputs, assumptions, and tables, which distinguishes it from the sibling calculate tool. However, the description itself is a noun phrase rather than an explicit action statement like 'returns' or 'describes', so it is clear but slightly implicit.

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 makes clear that this tool provides explanatory information about a calculator's behavior, so an agent can see it is for understanding the calculator rather than performing a calculation. It does not explicitly say 'use calculate for actual computation' or list exclusions, but the context and sibling tool names make the intended use reasonably apparent.

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 disclosure burden and does so well. It states that no purchase or payment occurs, no quote is guaranteed, the service is free, and it explicitly lists what the tool returns: recipient details, consent wording, and confirmation method.

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 front-loaded with 'Read first' and delivers all key information in a few compact sentences. It has no filler, avoids repeating the title, and every sentence adds useful context.

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 tool with no output schema, the description fully covers what an agent needs: what the tool explains, what it does not do, and what it returns. No important invocation or selection detail is missing.

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 zero parameters, so no parameter-level documentation is needed. The description appropriately focuses on purpose and output rather than parameter details, matching the baseline for a parameterless tool.

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 job: it 'States plainly what submit_enquiry does on Payroll Dates' and 'returns' supporting details. It also distinguishes itself from the action-oriented sibling submit_enquiry by emphasizing that nothing is bought, ordered, or paid and no quote is guaranteed.

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 'Read first' is an explicit usage directive, and the description makes clear this tool should be used to understand submit_enquiry before acting. It does not explicitly name alternatives or exclusions, but the context is sufficient for a zero-parameter informational 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?

No annotations are provided, so the description carries the burden of disclosing behavior. It describes the output content (key, label, type, required, help text, options) but does not explicitly state that this is a read-only operation or mention whether any authentication or prerequisites exist. The content strongly implies a safe metadata query, but the lack of explicit safety disclosure keeps this at a minimum viable level.

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 that lists the exact output attributes and then gives a practical cross-reference to submit_enquiry. Every phrase earns its place; there is 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?

For a zero-parameter metadata tool, the description is nearly complete: it names the enquiry, enumerates the returned attributes, and connects to the follow-up submission action. Since there is no output schema, the description appropriately explains the return shape. It could have explicitly stated that no submission occurs via this tool, but the sentence about passing answers to submit_enquiry makes that practically clear.

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 schema is trivially fully covered and the baseline is 4. The description adds useful downstream context about using field keys with submit_enquiry, but there are no input parameters for the description to clarify.

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 ('Every field of the Payroll Dates enquiry') and enumerates what the field metadata contains. It lacks an explicit verb like 'returns' or 'lists', but the meaning is unambiguous and it distinguishes itself from submit_enquiry by explaining where answers should go.

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 clear usage context: it supplies the field keys that must be used when calling submit_enquiry. This implicitly tells the agent to fetch the fields before submitting answers. It does not explicitly address alternatives like enquiry_describe, but the downstream relationship 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?

With no annotations provided, the description fully carries the behavioral disclosure burden. It explains that the first call only validates and returns a summary, the second call actually submits, consent is required, and the enquiry is not visible to providers until the person clicks an email link. This is unusually 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 front-loaded with the critical 'not a purchase' caveat and clearly separates step 1 and step 2. It is longer than average, but the two-step protocol and consent details justify the length. The exact consent phrase is repeated from the schema, which is slightly redundant but harmless.

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 two-step human-submission flow with no annotations and no output schema, the description is remarkably complete. It tells the agent what to do in each step, what the first return contains, when to make the second call, what consent means, and what happens after submission.

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 already documents all parameters with 100% coverage, so the baseline is 3. The description adds meaningful workflow semantics: answers must be keyed by enquiry_fields keys, consent must reflect agreement to the exact privacy line, and confirmation is the token from step 1 used only after approval. This goes beyond the schema's static 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 states the tool submits an enquiry to human providers, explicitly distinguishes it from a purchase or guaranteed quote, and explains it is a two-step process. This gives an agent a precise understanding of the operation and its boundaries.

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 step-by-step usage protocol: first call with answers and consent, then a second call with the confirmation token only if the person agrees. It also references enquiry_fields for field keys, giving useful context. However, it does not explicitly name alternative sibling tools or state when not to use this tool beyond saying it is not a purchase.

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