site

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it discloses nothing: no return format, no read/write nature, no filtering behavior, no error conditions. The phrase 'any filters' hints at filter handling but does not clarify whether filters are inputs, outputs, or display constraints.

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 short clause with zero filler and the key term 'criteria' front-loaded. It earns conciseness credit, though the under-specification noted in other dimensions prevents a 5.

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?

Complexity is low (0 parameters, no output schema, no annotations), so little is required for completeness, but the description still fails to state what invoking the tool returns and how it differs from compare_options and compare_table. A minimal action statement plus one line of sibling differentiation would have sufficed.

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 0 parameters and an empty input schema, so there is nothing to document and the baseline of 4 applies. The description adds no parameter meaning, but none is needed; the only wrinkle is that 'filters' could imply inputs that do not exist in the schema.

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 is a noun phrase with no action verb, so an agent cannot tell whether this tool lists criteria, accepts them, or compares them. It largely restates the title 'What is compared' ("the criteria ... of the ... comparison"), adding only the scope 'US field service management platforms.' This is closer to a tautology than a functional statement.

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 about when to use this tool versus siblings like compare_options, compare_table, or the enquiry_* tools. There are no exclusions, conditions, or alternative routing hints anywhere in the description.

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 and it does disclose the optional tag-value filter and the fields returned. However, it omits behavioral details such as whether this is a read-only operation, how filtering behaves when filterKey is absent, or what the output structure looks 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 resource and then presents the returned fields and the optional filter. It wastes no words, though the title 'The options' adds no value.

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 listing tool with two optional parameters, the description is minimally viable, but the lack of an output schema and annotations raises the burden. It does not explain filterKey semantics, possible filter values, or how results are ordered/returned, leaving some ambiguity for an agent selecting and 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 0%, so the description must compensate for the undocumented filterKey and filterValue parameters. It explains that filtering is by a 'tag value', but it does not clarify what filterKey should be, whether both parameters are needed together, or what values are accepted.

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 specific resource ('the options in the US field service management platforms comparison') and names the fields included (name, what it is best for, tags). It is clear enough to distinguish from siblings like compare_criteria and compare_table, though it is phrased as a noun phrase rather than an explicit action verb like 'retrieves' or 'lists'.

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 guidance about when to use compare_options versus the sibling tools compare_criteria, compare_table, or the enquiry tools. The only usage hint is that filtering is optional, but no context or alternative-selection criteria is provided.

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 of explaining behavioral traits, but it only describes the content scope of the table. It does not state that the operation is read-only, describe the response format, or disclose any filtering behavior beyond what the parameter schema already implies.

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 one compact sentence with no filler and clearly scopes the table to US field service management platforms. The dash construction is slightly informal but efficient and easy to parse.

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 one-optional-parameter table lookup, the description conveys the core content adequately, but it leaves the actual return format and default behavior implicit. With no output schema and no annotations, the definition is minimally sufficient rather than fully self-contained.

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 already documents the single optional parameter clearly with 'one option's name, else all', so the description adds no new parameter meaning. With 100% schema coverage, 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?

The description clearly identifies the resource as the full comparison table showing each option's value on every criterion, which helps distinguish it from sibling tools focused on criteria or options. However, it lacks an explicit verb such as 'returns' or 'lists,' relying on the tool name and title to convey the action.

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 'the full table' and 'every criterion' imply this tool is for retrieving the complete cross-comparison rather than the narrower compare_criteria or compare_options tools. It does not explicitly name alternatives or state when not to use it, so the guidance is implied rather than direct.

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 behavioral disclosure burden. It does this thoroughly by stating that nothing is purchased, ordered, or paid, that no quote is guaranteed, that the service is free, and that it returns who receives 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?

Three sentences with no filler. The critical usage cue 'Read first' is front-loaded, and every subsequent sentence adds meaningful behavioral or output information. The title also provides a concise summary of the user-facing outcome.

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 zero parameters, no annotations, and no output schema, the description is remarkably complete. It explains what the tool does, what the user should not expect, what the user will receive in return, and when it should be read. Nothing essential is missing 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?

The tool has zero parameters and the schema is empty, so there is no parameter information to add. The description goes beyond the schema by explaining the tool's output and non-transactional nature, which is more relevant than parameter semantics for this 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 names a specific verb ('states plainly what submit_enquiry does') and resource ('submit_enquiry on Which Field Software'), and the title reinforces the scope. It clearly distinguishes itself from the sibling tools by being the explanatory precursor to submit_enquiry, not an action or comparison tool.

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 that this tool should be consulted before using submit_enquiry. It does not explicitly enumerate when not to use it or mention alternatives, but the intended placement relative to the submit action 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 disclosure burden. It clarifies that this is a metadata/schema lookup tied to submit_enquiry and scopes the returned fields, but it does not explicitly state that calling it has no side effects or describe response behavior beyond the field list.

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 first states the full scope of the payload, and the second connects it to the submission tool. 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?

For a parameterless metadata tool, the description covers what is returned and how to use it. It could be more explicit about the return shape or mention when to prefer the compare_* siblings, but those are minor gaps given the tool's simplicity.

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. The description adds useful context by noting that answers must be keyed by field key, which informs how the returned data will be used with 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 (Which Field Software enquiry fields) and enumerates what is returned: key, label, type, whether required, help text, and allowed options. It lacks an explicit verb like 'gets' or 'lists' and does not explicitly contrast with sibling comparison tools, 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 line 'Pass answers to submit_enquiry keyed by field key' places the tool in a clear workflow: call it to discover field keys before submitting answers. It does not state when not to use it or mention the compare_* siblings, but the intended context is evident.

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 behavioral burden and does so thoroughly. It discloses the two-step validation/submission behavior, the return values from step 1, the email side effect, the link-click requirement before providers see the enquiry, and the exact consent wording.

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 dense but each sentence earns its place: it front-loads the core purpose and exclusions, then clearly sequences the two steps and consent requirement. The verbatim consent line is included because it is legally/operationally necessary, not 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 multi-step, consent-sensitive, nested-object tool with no annotations and no output schema, the description is remarkably complete. It covers the full call sequence, required parameters, expected step-1 response, user consent handling, email notification, and the provider-visibility condition tied to link click.

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 already 100%, but the description adds meaningful semantics beyond the schema: that answers are keyed by field keys from enquiry_fields, that confirmation is the token returned in step 1, and that the same answers plus consent=true must accompany the token in step 2. This links each parameter to a concrete stage of the workflow.

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, 'Submits an enquiry to Which Field Software,' and immediately clarifies what it is not ('NOT a purchase, NOT a guaranteed quote'). It clearly distinguishes itself from sibling tools that compare or describe options by framing this as the submission endpoint.

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 conditions: when to make the first call, when to make the second, and that the second call must happen only after the person agrees. It also tells the agent to show the person the summary and consent line, leaving no ambiguity about the required interaction flow.

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