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

With no annotations, the description must carry the behavioral transparency burden, and it does add useful details: missing inputs fall back to documented defaults, and the year-one total is excluding VAT. However, it does not state whether the tool has side effects, what the output structure is, or how the fee components are combined, leaving some 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?

The description is a single compact sentence that front-loads the action and the output categories. It loses a point for the duplicated 'calculator calculator' wording, but otherwise there is no 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?

For a calculator with eight optional parameters and no output schema, the description covers the important aspects: what is computed, that defaults apply, and that VAT is excluded. It leaves the output representation unspecified, but the listed output categories are sufficient for an agent to invoke it and interpret high-level results.

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% and every parameter has type, range, default, and a one-line description. The description's default-fallback sentence reinforces schema defaults rather than adding new meaning, so the baseline 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?

States verb 'Run' and identifies the resource as the IT support cost calculator, then lists the four computed outputs: monthly support fee, annual support fee, out-of-scope project work, and year-one total excluding VAT. This is clear, though it does not explicitly distinguish itself from sibling tools like calculator_describe or 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 provides no guidance on when to choose this tool over calculator_describe, enquiry_describe, or submit_enquiry. The only usage-related note is that missing inputs fall back to defaults, which is behavioral information rather than a selection criterion.

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. It discloses the informational content the tool returns and implies a read-only describe operation, but it does not explicitly state that no calculation is performed, there are no side effects, or what format the response takes.

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?

A single sentence covers all major content areas without filler. It is front-loaded with inputs and remains compact; it could be slightly more structured by using an explicit 'Describes...' verb, but it is appropriately sized.

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 introspection tool with no output schema, the description adequately enumerates what the returned documentation will cover. The only meaningful omission is an explicit link to the workflow of calling 'calculate' after learning the inputs, but sibling names and the simple scope keep it complete enough.

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 description adds useful semantic context by clarifying that the 'inputs' are the calculator's parameters, not arguments to this function. This meets the baseline for no-parameter tools and prevents confusion.

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 tool's purpose: it presents the calculator's input parameters (with units, ranges, defaults), outputs, assumptions, and underlying tables. The title reinforces this. It does not explicitly contrast with the sibling 'calculate', but the descriptive intent 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 description implies this tool should be used when an agent needs to know the calculator's inputs, outputs, assumptions, or underlying tables. However, it never explicitly says to use 'calculate' for actual computation or gives when-not-to-use conditions, so routing must be inferred from sibling names.

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, and it does so well. It explicitly states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and what the tool returns: recipient details, consent wording, and confirmation method. This gives an agent an accurate model of side effects and outcomes.

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 with the 'Read first' directive. Both sentences carry meaningful content: the first establishes what the tool explains, and the second clarifies the non-transactional nature and return information. No wasted words.

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 descriptive tool with no output schema, the description is complete. It explains what the tool does, what it does not do, what the user can expect, and what information the underlying submit_enquiry process returns. An agent can decide correctly whether to invoke this tool before submit_enquiry.

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 already reflects that, so there are no parameter semantics for the description to clarify. The description appropriately adds no parameter-related noise; the baseline for zero-parameter tools applies.

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 ('states'), a specific resource ('submit_enquiry on IT Support Cost Calculator'), and clearly frames the tool as the explanatory counterpart to submit_enquiry. It distinguishes itself from the actual submission tool by emphasizing 'Read first' and describing rather than performing the 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 instruction 'Read first' clearly signals when to use this tool: before interacting with submit_enquiry. It does not explicitly name alternatives or state when not to use it, but the context is clear enough given the sibling tools and the description's meta-purpose.

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 transparency burden. It discloses what data the tool exposes and strongly implies a read-only metadata lookup, but it never explicitly states that it returns data without side effects or describes the response format. This is adequate but not fully 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?

One dense sentence front-loads the resource and its contents, then closes with a practical pointer to submit_enquiry. Every word adds value and there is no 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?

For a zero-parameter metadata tool with no output schema, the description covers the essential return information: field identity, type, requiredness, help text, options, and how to key answers for submit_enquiry. It does not explicitly state the container format of the returned fields, a minor but non-blocking 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 input schema has zero parameters, so there are no parameter meanings to document. A baseline score of 4 is appropriate because there is nothing missing at the parameter level.

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 ('IT Support Cost Calculator enquiry') and enumerates the exact contents: key, label, type, required status, help text, and options. It does not use an explicit verb like 'returns' or 'lists', and it does not directly contrast with sibling enquiry_describe, so it falls just short of a 5.

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 a clear practical usage cue: pass answers to submit_enquiry keyed by field key, implying this tool should be consulted before submitting. It does not explicitly state when not to use it or compare it with alternatives like enquiry_describe.

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 burden and successfully discloses the two-step behavior, validation return values (summary, consent line, confirmation token), the email link requirement, and the exact meaning of consent. It also flags that the enquiry is not immediately visible to providers until the person clicks the email link, preventing a realistic misuse.

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 contributes: scope, exclusions, step 1, step 2, consent definition. It is front-loaded with the most important caveat and organized by step, though the consent line could be trimmed to avoid repeating the schema text.

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?

The description is complete for a complex two-step submission tool with no output schema. It covers what the person must be shown, the exact consent text, the token handoff, and the email link behavior, leaving no material gap for an agent to invoke it correctly.

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, but the description adds workflow semantics: answers must be keyed by field key from enquiry_fields, consent must equal the quoted agreement, and the confirmation token bridges step 1 to step 2. This meaningfully enriches the raw schema definitions.

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 ('submits') and resource ('IT Support Cost Calculator') and sharply distinguishes itself from a purchase or guaranteed quote. The title and first sentence make the tool's function unmistakable relative to siblings like calculate and enquiry_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?

The description gives explicit step-by-step usage: first call with answers and consent, show the summary and consent line, then call again only if the person agrees with the confirmation token. It does not explicitly name alternative tools or state when not to use it beyond 'not a purchase', but the procedural guidance makes the intended invocation clear.

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