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

No annotations are present, so the description carries the full burden of explaining behavior. It states that a comparison is made, but does not disclose whether the tool is read-only, what output format or content to expect, what 'capability comparison' means, or any limitations of the comparison. This leaves the agent with insufficient understanding of the tool's actual behavior.

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 redundant tail: 'compared on capability comparison.' It also relies on the unclear title 'What is compared' instead of cleanly stating the tool's action and output. The phrasing is confusing rather than efficiently informative.

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 annotations, no output schema, and no parameters, the description is the only source of context, and it leaves the tool's purpose, output shape, and relationship to sibling tools unclear. An agent cannot reliably know what invoking this tool will do or how to interpret its 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?

This tool has zero parameters and an empty input schema, so there are no parameter meanings that the description needs to clarify. The 'criteria and filters' mentioned in the description appear to be the subject of the comparison, not input parameters, so the no-parameter baseline of 4 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 the subject ('criteria and any filters' around 'Who can prepare a UK crypto tax position') and indicates they are 'compared', so it is not merely a tautology. However, the phrasing is vague and awkward ('compared on capability comparison'), and it does not clarify what the tool returns or how it differs from sibling tools 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?

The description provides no guidance on when to use compare_criteria versus its siblings compare_options, compare_table, enquiry_describe, enquiry_fields, or submit_enquiry. There are no exclusions, alternatives, or conditions given. The phrase 'capability comparison' hints at a use case but is too vague to guide tool selection.

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 does disclose the output fields (name, what it is best for, tags) and the filtering behavior, which implies a non-mutating query. However, it does not state default behavior without a filter, return format, or any access requirements, leaving partial 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 a single sentence of moderate length, but it contains redundant phrasing ('compared on capability comparison') and grammatical awkwardness ('The options in the Who can...'). Key information is present, but the structure is not polished.

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 output schema, the description covers the domain, output fields, and a filter option. It is reasonably adequate but omits filterKey semantics and any guidance on sibling tool selection, so it is not fully complete.

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. It explains filterValue as a 'tag value' and notes filtering is optional, but filterKey is not explained at all. This leaves ambiguity about what filterKey represents and how the two parameters interact.

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 a specific resource—options for 'Who can prepare a UK crypto tax position'—and states what is compared (name, what it is best for, tags). It is not a tautology and conveys the tool's core purpose, though it lacks an explicit verb like 'list' or 'return' and does not differentiate from sibling comparison tools.

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 domain context and mentions an optional tag filter, but it gives no guidance about when to use this tool instead of compare_criteria or compare_table, and no exclusions. An agent would have to infer usage from the tool name and 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?

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only describes the table's content, not how it behaves, what the output looks like, or any side effects. It is not misleading, but it is minimal.

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 mostly front-loaded with 'Each option's value on every criterion', but the phrasing becomes awkward and confusing with 'of the Who can prepare a UK crypto tax position, compared on capability comparison'. It is concise but not cleanly structured.

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 optional-parameter tool, the description gives a basic sense of what is returned, but it does not clarify the phrase 'capability comparison' or why it matters, and the lack of an output schema leaves return-format details unexplained. Adequate but with 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 single parameter 'option' is already fully described in the schema with 'one option's name, else all', so the description adds little beyond that. The description's mention of 'each option' and 'full table' slightly reinforces the filtering behavior, but the schema does the heavy lifting.

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 the tool returns a full comparison table showing each option's value on every criterion, which is a specific and identifiable function. It is clear enough to understand the resource being compared, though it does not explicitly distinguish itself from sibling tools.

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 explicit guidance is given about when to use this tool versus compare_criteria or compare_options. The phrase 'the full table' hints at a complete view, but the description does not state exclusions, alternatives, or selection conditions.

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 transparently explains that the underlying enquiry involves no purchase, no payment, no guaranteed quote, and is free, while noting that the tool returns recipient details, consent wording, and confirmation method. This makes the read-only, informational nature clear, though it could more explicitly state that this tool itself performs no submission.

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 'Read first.' Every sentence earns its place: the core purpose, the key exclusions, and the return contents. It avoids redundancy and is easy for an agent to parse quickly.

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 informational tool, the description is largely complete: it explains what the tool does, clarifies its relationship to submit_enquiry, and summarizes what it returns. It does not provide exhaustive detail about output formatting, but no output schema exists and the tool's purpose is to present human-readable explanatory content.

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 100% covered by the empty properties object, so the baseline is 4. The description correctly contains no parameter information because no parameters exist to document.

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 purpose: it 'States plainly what submit_enquiry does' on the Crypto Accountants Directory and lists the exact content it returns. This sharply distinguishes it from submit_enquiry itself and from the comparison-focused sibling tools.

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 an explicit usage directive: this should be used before submit_enquiry. It gives clear context for when to call it, though it does not explicitly exclude or compare against sibling tools like compare_criteria or compare_table.

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 full burden. It implies a read-only metadata lookup and separates this from submission by referencing submit_enquiry, but it never explicitly states that there are no side effects or that the operation is safe. It also says nothing about errors, rate limits, or other behavioral traits.

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 output contract is front-loaded and the downstream usage hint is placed second. Every sentence contributes meaningful 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?

Even without an output schema, the description enumerates the important return fields and explains how to use them with submit_enquiry. It is complete enough for a zero-parameter field metadata tool, though it does not explicitly state whether the result is an array, a map keyed by field key, or another collection format.

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, so there are no parameters to document. With 0 params, the baseline is 4. The description appropriately focuses on the output shape and downstream use rather than invocation arguments.

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 resource and output contents: every field of the Crypto Accountants Directory enquiry, including key, label, type, required flag, help text, and allowed options. It is not a tautology and is easily distinguished from submit_enquiry, though it lacks an explicit verb like 'list' or 'return'.

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 second sentence gives practical guidance: after retrieving the fields, pass answers to submit_enquiry keyed by field key. This establishes a clear use case and relationship to a sibling tool. It does not explicitly state when not to use this tool or compare against enquiry_describe, so it stops short of full routing 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 the full behavioral burden and does so thoroughly: it discloses validation, the returned summary/consent line/token, the email with a click link, that providers see the enquiry only after the person clicks, 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 well organized with Step 1 and Step 2, front-loads the core action and exclusions, and every sentence contributes essential procedural, consent, or outcome 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 and no annotations, the description fully covers the call sequence, required inputs, returned artifacts, email behavior, and approval gate, leaving no significant gap for an agent to invoke the tool 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%, and the description still adds meaningful semantics: answers are keyed by field key from enquiry_fields, consent is tied to the exact quoted agreement, and confirmation is the step-1 token used only after the person approves the summary.

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 Crypto Accountants Directory'. It also explicitly clarifies what the tool is not ('NOT a purchase, NOT a guaranteed quote') and the two-step flow distinguishes it from enquiry_describe, enquiry_fields, and the comparison 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?

Provides explicit step-by-step guidance: call first with answers and consent=true to get a confirmation token, then call again with the token only if the person agrees. It also states the exclusion (not a purchase/quote) and the requirement that consent must match the quoted agreement.

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