site

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 provides concrete calculation details: CPP rates and brackets, CPP2 thresholds, EI multiplier and cap, and 'true annual cost'. It also discloses default-value fallback behavior, which is useful beyond the schema. It does not describe the output format, but for a calculation tool this is reasonably 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 a single sentence that conveys the essential calculation inputs and fallback behavior without excessive verbosity. It loses a point for the redundant phrase 'calculator calculator', which is a minor clarity defect but not a structural problem.

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 two optional parameters and no annotations, the description provides the main calculation rules, thresholds, and default behavior, which is sufficient for basic invocation. It does not explicitly state what the return value looks like or define 'true annual cost' precisely, but the core usage context is present.

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 both parameters (salary and extras) with descriptions and defaults, and schema coverage is 100%. The description adds no new parameter-specific semantics beyond restating the default fallback behavior, so a baseline score of 3 is appropriate.

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 action ('Run') and resource ('Employer payroll cost calculator'), and specifies exactly what it computes: Employer CPP, CPP2, EI, and true annual cost. This distinguishes it from sibling tools like calculator_describe or submit_enquiry, even if not explicitly named.

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 the tool should be used when employer payroll costs need to be calculated, and mentions that missing inputs fall back to defaults. However, it does not explicitly state when to prefer this over sibling tools like calculator_describe or submit_enquiry, nor does it provide any exclusions or alternative routing.

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, and it clearly indicates the tool provides informational content about inputs, outputs, assumptions, and tables. This implies a read-only, non-destructive operation, though it does not explicitly state that no calculation is performed.

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 sentence efficiently enumerates exactly what the tool describes, with no filler. The most important detail (inputs) 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 informational tool, the description covers the essential return content. Without an output schema it could be slightly more explicit about the delivery format, but nothing an agent needs to invoke the tool correctly 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 tool has zero parameters, so there are no parameter schemas to document; the 0-param baseline of 4 applies. The description's mention of units, ranges, and defaults refers to the calculator's conceptual inputs, not tool parameters, and is a helpful extra.

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 make clear this tool explains the employer payroll cost calculator's inputs, outputs, assumptions, and backing tables. It is distinct from the sibling calculate tool because it describes the calculator rather than executing it, though it lacks an explicit verb like 'returns'.

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?

Usage is implied by the describe-style name: an agent would call this when it needs to understand the calculator before using calculate. However, the description never explicitly says when to prefer this over siblings or states any preconditions.

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 present, the description carries the full disclosure burden and meets it: it explicitly says nothing is bought, ordered, or paid, no quote is guaranteed, and the action is free, and it names exactly what the tool returns (recipients of details, consent wording, confirmation method). This goes well beyond a generic 'describes submit_enquiry' statement.

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 sentences and front-loads the action with 'Read first.' Each sentence adds distinct information—purpose, safety/no-cost facts, and return contents—so there is little waste, though it is slightly more verbose than a single-sentence definition could be.

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 reasonably covers what the tool returns and the key caveats of submit_enquiry. It does not specify output formatting or how the returned text should be used, but for a zero-parameter documentation tool the missing detail is minor.

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 schema coverage is 100%, so the baseline of 4 applies; there are no parameter meanings for the description to add. The description's focus on behavior and return contents is appropriate for a parameterless informational 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 opens with 'Read first' and states the tool 'States plainly what submit_enquiry does' on the Canada Payroll Calculator, giving a specific verb and resource. It also distinguishes itself from the sibling submit_enquiry by framing itself as the explaining/meta tool rather than the 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?

'Read first' is explicit guidance to call this tool before engaging with submit_enquiry, and the overall wording positions it as the prerequisite explanation. It does not spell out when to use calculator_describe or enquiry_fields instead, but the clarity of the purpose makes the main usage context obvious.

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 behavioral disclosure burden. It does disclose the returned data contents and implies a read-only discovery operation, but it does not explicitly state that invoking the tool has no side effects or describe any access constraints. This is adequate but largely implicit.

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 concise sentences: the first front-loads the tool's output content in a compact list, and the second provides actionable next-step guidance. Every sentence earns its place, and there is no redundant repetition of schema 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?

With zero parameters and no output schema, the description's enumeration of returned attributes plus its routing to submit_enquiry gives an agent the core knowledge needed to call and use the tool correctly. An explicit statement of the output shape would be slightly better, but it is not essential for this simple metadata-discovery 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?

The tool has zero parameters and schema description coverage is 100%, so there is no parameter documentation gap for the description to fill. The description adds useful forward guidance by instructing that the returned field keys should be used when calling 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 identifies the resource as the fields of the Canada Payroll Calculator enquiry and enumerates exactly what those fields contain: key, label, type, required flag, help text, and allowed options. It lacks an explicit verb like 'list' or 'get', but the meaning is unambiguous and distinct from submit_enquiry.

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 tells the agent to pass answers to submit_enquiry keyed by the field key, effectively positioning this tool as a prerequisite discovery step for submitting an enquiry. It does not explicitly contrast with enquiry_describe or calculator_describe, but the intended usage context is clear.

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: it discloses the two-call validation/submission split, that nothing reaches providers until an email link is clicked, who receives the contact data (up to three Canadian firms chosen by the service), and the exact consent semantics. Side effects and the human-confirmation gate are unambiguous.

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-loaded with the purpose and non-purchase caveat, then sequenced as Step 1 / Step 2, which matches the calling order. It loses a point because the full consent sentence is repeated verbatim from the consent parameter description, which is redundant text rather than new 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?

Despite having no output schema, the description spells out what step 1 returns (a summary, the consent line, a confirmation token) and what happens after step 2 (an email with a click-through link before providers see anything). Nothing an agent needs to drive this multi-call mutation correctly 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?

Schema coverage is 100%, so the baseline is 3; the description earns above baseline by explaining the role each parameter plays in the flow — answers must be keyed by enquiry_fields keys, consent=true is required at both steps, and confirmation is the token returned by step 1 and only sent on step 2.

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 verb and resource ('Submits an enquiry to Canada Payroll Calculator') and immediately negates the two most likely misreadings: 'NOT a purchase, NOT a guaranteed quote'. That framing lets an agent distinguish it from calculate and calculator_describe without opening any schema.

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?

Gives an explicit two-step protocol: step 1 with answers + consent=true to validate and obtain a token, step 2 only after the person agrees, with the token. It also names the sibling that supplies input shape ('keyed by field key from enquiry_fields') and states the gate condition for the second call.

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