site

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says the comparison is based on what actually differs, but it does not clarify whether the tool returns a full comparison, only differences, or any additional behavioral details like output format, read-only nature, or limitations.

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 short, but it is poorly structured and contains a confusing, redundant trailing phrase ('what actually differs comparison'). It is under-specified rather than cleanly concise, and the wording does not effectively front-load a clear purpose.

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 zero-parameter comparison tool, the description should still clearly state what is compared and what result to expect. It vaguely identifies the subject matter but fails to define 'Four call answering models' or distinguish this tool from siblings, leaving the context incomplete.

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 fully covers parameter semantics. There is nothing for the description to add regarding parameters; the baseline of 4 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 refers to comparing criteria and filters across four call answering models, which indicates a comparison purpose. However, the phrasing 'compared on what actually differs comparison' is grammatically broken and vague, leaving the exact function ambiguous and not clearly distinguishing it from siblings like compare_options or compare_table.

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 on when to use this tool versus alternatives such as compare_options or compare_table. The description implies a comparison scenario but provides no explicit context, prerequisites, or exclusions.

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 present, so the description carries the full burden. It does not disclose whether the operation is read-only, what output shape to expect, whether there are side effects, or how the filtering behaves beyond a vague mention.

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 short but poorly structured and contains a redundant/confusing phrase ('what actually differs comparison'). It is not front-loaded effectively and reads like an unedited fragment rather than a clear tool definition.

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 no output schema and no annotations, the description needed to clarify output format, filter semantics, and tool selection. It leaves the filter key unspecified, does not describe return values, and gives no context about the 'Four call answering models'.

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 provides 0% description coverage, and the description only says 'optionally filtered by a tag value.' It does not explain how filterKey and filterValue map to that behavior, what valid tag keys are, or what values they accept.

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 ('options in the Four call answering models') and the comparison dimensions (name, best-for, tags), so the basic purpose is discernible. However, the phrasing is garbled ('what actually differs comparison') and it does not distinguish this tool from sibling comparison tools like compare_criteria or compare_table.

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 only usage hint is that results can optionally be filtered by a tag value. There is no guidance about when to choose this tool over compare_criteria or compare_table, nor any exclusion criteria.

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 behavioral disclosure burden. It conveys that the tool performs a read-style comparison and returns the full table, which is useful. However, it does not mention response shape, whether the table is filtered by the option parameter, or any limitations, and one clause ('compared on what actually differs comparison') is confusing rather than clarifying.

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 short, and the core idea is front-loaded, but the trailing phrase 'compared on what actually differs comparison — the full table' is syntactically broken and confusing. This structural flaw undermines clarity more than it saves space.

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 tool is simple with one optional parameter and high schema coverage, so the description does not need to be extensive. Still, with no output schema and no annotations, the description should more clearly state what the returned table contains and how the optional option parameter affects it; the malformed wording leaves gaps.

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 'option' parameter with 'one option's name, else all' at 100% description coverage. The tool description adds no parameter-level detail beyond the general notion of 'each option,' so the 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 identifies a specific resource — a comparison table covering every option's value on every criterion of the four call answering models — and indicates the tool's job is to compare. It does not explicitly differentiate itself from siblings like compare_criteria or compare_options, so it stops 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?

There is no guidance about when to use compare_table versus the sibling comparison tools, nor any exclusions or alternative routing. The phrase 'the full table' hints at scope but does not tell an agent when this tool is preferred over compare_criteria or compare_options.

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 disclosure burden. It states what the tool returns (who receives details, consent wording, confirmation method) and clarifies key caveats about the underlying submit_enquiry flow: no payment, free, and no guaranteed quote. It does not explicitly assert that this describe tool is side-effect-free, but the descriptive nature and 'Read first' directive sufficiently imply a read-only action.

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: a one-word directive, a purpose statement, key caveats, and a return-content sentence. Every sentence serves a distinct purpose, and there is no filler in the description itself.

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 0-parameter informational tool with no output schema, the description is complete: it explains what the tool does, what important caveats the caller should know, and what information it returns. The 'Read first' instruction also supplies the placement within the tool flow.

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?

This tool has zero parameters, so the schema fully covers parameter semantics; the 0-parameter baseline is 4. The description appropriately adds no redundant parameter details.

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 the exact resource it explains (submit_enquiry) and the specific context (Compare Call Answering), making clear that this tool provides a plain-language explanation rather than performing the enquiry action. The title reinforces the distinction by emphasizing that no purchase or guaranteed quote is involved, separating it from the action-oriented sibling 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 opening directive 'Read first' clearly signals that this tool should be used as a prerequisite before entering the enquiry flow. It does not explicitly enumerate exclusions or contrast with siblings like enquiry_fields or compare_options, but the usage context is clear enough for an agent.

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 behavioral disclosure burden. It does convey that the tool outputs a field list and that submissions happen elsewhere via submit_enquiry, suggesting a read-only metadata role. Still, it does not explicitly state that this tool has no side effects, describe how the field list is returned, or mention any limitations or error behaviors.

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 tight sentences: the first front-loads the tool's output contents, and the second gives a concrete follow-up action. Every sentence earns its place with no redundancy or 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 zero-parameter metadata retrieval tool without an output schema, the description provides enough detail about the returned field properties and the downstream submission mapping. It could be slightly more complete by naming alternatives or explicitly framing itself as the schema look-up tool, but nothing essential is missing for a basic call.

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 and schema description coverage is 100%, so the 0-parameter baseline applies. The description adds relevant semantic context by explaining that the field keys returned here are the same keys to use in submit_enquiry, which is useful beyond the bare 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 clearly identifies the resource—the field definitions of the Compare Call Answering enquiry—and enumerates the content: key, label, type, required flag, help text, and allowed options. It lacks an explicit verb like 'retrieves' or 'lists', and it does not directly compare itself with sibling tools, so it falls just short of full clarity.

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 practical usage pointer: answers should be passed to submit_enquiry keyed by field key, implying this tool is the source for constructing submissions. However, it does not explicitly state when to prefer this tool over siblings like enquiry_describe or compare_table, nor does it provide any when-not-to-use guidance.

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 burden and does so thoroughly: it discloses the two-step statefulness, validation returning a summary and token, the need to show the person the summary and consent line, the email with a click link, the condition that providers only see the enquiry after the click, and the exact consent wording. This is exemplary transparency.

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 long but logically structured into Step 1 and Step 2, with each sentence carrying essential workflow, consent, or side-effect information. A little redundant with the title, but the detail is justified for a two-step sensitive submission.

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 no output schema and no annotations, the description covers the response from step 1 (summary, consent line, confirmation token), the exact condition for step 2, the email side effect, and the provider-visibility rule. Nothing essential for correct invocation 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 description coverage is 100%, so baseline is 3, but the description adds workflow meaning: answers are keyed from enquiry_fields, confirmation is the token returned in step 1, and consent must match the quoted statement. This helps an agent understand how the parameters interact across the two calls.

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?

Description states a specific action ('Submits an enquiry to Compare Call Answering') and immediately clarifies what it is not ('NOT a purchase, NOT a guaranteed quote'). It clearly differentiates from sibling tools like compare_* and enquiry_describe/enquiry_fields by being the actual submission action, reinforced by the title's 'two steps; not a purchase'.

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?

Provides a clear step-by-step usage flow: first call with answers and consent, obtain confirmation token, then call again only if the person agrees. It also references enquiry_fields for keying answers, implying a prerequisite. It does not explicitly name sibling alternatives, but the boundary against purchase/quote is explicit.

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