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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 full behavioral disclosure burden. It does add one meaningful trait — missing inputs silently fall back to documented defaults — and implies a pure computation with no side effects. However, it never explicitly states the operation is read-only/non-persistent, nor what happens on invalid input, even though one parameter is an enum and all values have bounded ranges.

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 tight sentences, front-loaded with the imperative verb and resource name. The semicolon-delimited output list is compact and scannable, and the defaults note earns its place as a real behavioral cue. Only minor reorganization (labeling the list as outputs) would improve it.

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 5-parameter calculator with no annotations and no output schema, the description covers the core: what is computed and how missing inputs are handled. But it leaves gaps that matter — the format/structure of the returned calculation results, whether the nightWork enum values materially change the outputs, and any edge-case behavior on out-of-range inputs.

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 baseline is 3. The description adds some meaning beyond the schema by framing the parameters as inputs to four named calculations, which helps an agent anticipate what the numbers produce. This added value is modest, and 'Cycle length in days' could be misread as a requestable input rather than a computed output, slightly muddying the semantics.

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?

Uses a specific verb ('Run') plus a named resource ('Shift pattern generator calculator') and enumerates what it computes: cycle length, average working hours per week, hours under the 48-hour limit, and crews needed. This clearly states the tool's function and avoids tautology. It doesn't explicitly contrast with sibling 'calculator_describe', but the imperative 'Run' versus the sibling's 'describe' verb makes the distinction mostly inferable.

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 when-to-use guidance, no exclusion criteria, and no mention of alternatives — notably 'calculator_describe', which likely relates to the same calculator and would be a candidate for confusion. The only usage-adjacent note is that missing inputs fall back to defaults, which is a parameter behavior, not a tool-selection guideline.

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 burden of explaining behavior. It conveys that the tool is informational, returning a description of inputs, outputs, assumptions, and tables rather than performing a calculation. Still, it does not explicitly state that no calculation is executed, whether the tool is safe/read-only, or what the response format will look like.

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 key value: it tells the agent exactly what information the tool provides. No filler, no repetition of the schema, and every phrase contributes to understanding.

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 metadata tool, the description is sufficient: it names the inputs, outputs, assumptions, and tables the calculator is built around. It could be more complete by clarifying that this is the documentation/specification tool rather than the execution tool, but the sibling list and the 'describe' name make that reasonably inferable.

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, so the baseline is 4. The description does not need to explain tool parameters, and it appropriately focuses on what the described calculator itself takes and returns.

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 name and title clearly indicate this is the 'describe' counterpart to the calculator, and the description enumerates the specific content it provides: inputs with units/ranges/defaults, outputs, assumptions, and tables. It is clear about the tool's scope but does not use an explicit verb like 'returns' or 'describes,' and it does not directly contrast itself with the calculate 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?

Usage is implied: an agent would call this when it needs to understand the calculator's inputs, outputs, or underlying assumptions. However, there is no explicit guidance on when to choose this over the calculate tool or the enquiry_describe tools, leaving the routing decision 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?

With no annotations provided, the description carries the full disclosure burden. It clearly states what happens ('starts an enquiry with human providers who quote directly'), what does not happen ('Nothing is bought, ordered or paid; no quote is guaranteed'), and what the tool returns. This is strong, non-obvious behavioral context beyond the empty schema.

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 with no filler. 'Read first' front-loads the critical instruction, followed by a clear statement of function and key caveats. Every sentence contributes distinct, 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 zero-parameter, no-output-schema describe tool, the description fully covers what the tool does, what it returns, and its relationship to submit_enquiry. The caveats about purchase, quoting, and cost remove likely ambiguities. Nothing essential 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 the baseline is 4 per the rubric. There is no parameter information to provide, and the description makes no misleading parameter claims. The empty schema and empty description are consistent.

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 ('States plainly') and names the exact resource ('what submit_enquiry does on Shift Pattern Generator'). It also clarifies what the tool is not about ('not a purchase, not a guaranteed quote'), distinguishing it from transaction-like sibling tools. This is unambiguous and immediately actionable.

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 a clear directive to consult this tool before acting, and the description positions it as the explanatory companion to submit_enquiry. It does not explicitly name alternatives or exclusion conditions, but the intended context is obvious for a describe-style 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 must carry behavioral disclosure. It does disclose the response contents (field metadata and allowed options), but it does not explicitly state that this is a read-only, side-effect-free operation or describe any error/auth behavior. This is adequate but not rich.

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, no filler. The first sentence front-loads the core content and the second gives a practical usage hint. Both sentences earn their 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 zero-parameter, no-output-schema introspection tool, this is complete: it enumerates the returned field metadata and connects the tool to the next step, submit_enquiry. An agent knows what to expect and how to use the result.

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 baseline is 4 per the rubric. The description adds useful context about how the returned field keys should be used in submit_enquiry, but there are no parameters whose meaning needs elaboration.

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 resource (Shift Pattern Generator enquiry fields) and specifies exactly what is included: key, label, type, required, help text, and allowed options. It lacks an explicit action verb like 'list' or 'return', so it falls short of perfect, but the scope is unmistakable and the link to submit_enquiry helps disambiguate it from siblings.

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 clear context by telling the agent to pass answers to submit_enquiry keyed by field key, effectively showing when this tool is needed: before submitting. It does not explicitly exclude alternatives such as enquiry_describe or state when not to use it, so it earns a 4 rather than 5.

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 behavioral disclosure. It transparently explains the two-step validation flow, the confirmation token, consent semantics, the email link that must be clicked before any provider sees the enquiry, and the exact consent wording. This is unusually complete.

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 longer than average but every sentence earns its place: the purchase disclaimer, step 1, step 2, the email requirement, and the consent text. The step-by-step structure makes the flow easy to follow, and the critical 'NOT a purchase' wording 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?

This is a stateful two-step tool with no output schema, yet the description covers the inputs, the intermediate response, the confirmation token, the human approval requirement, and the email link behavior. The reference to enquiry_fields also connects it to the sibling tool needed to obtain valid answer keys.

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?

All parameters are already described in the schema, giving a baseline of 3. The description adds meaningful context by specifying that answers are keyed by field keys from enquiry_fields, that consent=true is required at both steps, and that confirmation is the token returned from step 1. This goes beyond the schema's 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 states a specific verb and resource: 'submits an enquiry to Shift Pattern Generator', and immediately clarifies that it is NOT a purchase or a guaranteed quote. This clearly distinguishes it from siblings like calculate and enquiry_describe, and the title reinforces the two-step nature.

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 gives explicit step-by-step usage context: call once for validation and a confirmation token, then call again only after person approval. It also ties answers to 'enquiry_fields', implying the sibling tool is used first, but it does not explicitly state when not to use this tool versus alternatives.

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