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

With no annotations, the description carries the full burden of explaining behavior, but it only states a noun phrase rather than describing what the tool does or returns. It does not disclose whether this is a read-only reference operation, what the response looks like, or what filters refer to.

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 with no filler. It front-loads the key content ('criteria and any filters') and is appropriately short for a zero-parameter tool.

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 reference tool, the description conveys the essential subject matter, but with no output schema or annotations it leaves ambiguity about what result the agent will receive and how to interpret 'criteria and any filters'. It is minimally adequate but 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?

The tool has zero parameters and the schema has no properties, so parameter documentation is not needed. The description adds no parameter semantics, but the baseline of 4 applies because there is nothing to elaborate.

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 (criteria and filters of the UK telephone answering and virtual receptionist services comparison) but lacks a clear verb such as 'returns' or 'describes'. It is not a tautology, but it does not explicitly distinguish itself 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?

No guidance is given on when to use this tool versus compare_options, compare_table, or the enquiry tools. The description implies it is about comparison criteria but offers no context for selecting it.

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 behavioral disclosure. It discloses that results can be filtered by tag and what data fields are returned, which is useful. However, it never explicitly states that this is a read/retrieval operation, and it does not describe behavior for invalid filter keys or no-match scenarios. No contradiction exists since annotations are absent.

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 packs in the subject, domain scope, returned fields, and filtering behavior without filler. The parenthetical list '(name, what it is best for, tags)' is slightly awkward mid-sentence, but every clause earns its place and the core message lands 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 2-parameter tool with no output schema and 0% parameter coverage, the description leaves material gaps: no explicit operation verb, no clear parameter mapping, and no differentiation from sibling comparison tools. An agent could guess the filter semantics, but guessing is exactly what a complete definition should prevent.

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, but it only partially does. The phrase 'optionally filtered by a tag value' hints that filterValue holds a tag value, yet it never maps filterKey and filterValue to their roles, defines valid values, or clarifies whether filterKey is always the tag field. The two bare string parameters remain largely ambiguous.

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 a UK telephone answering services comparison) and its contents (name, best-for, tags), plus the filtering capability. However, it lacks an explicit action verb — it describes what the options are rather than what the tool does with them (list? get?). The title 'The options' matches the opening words of the description, edging toward tautology, though the added domain context saves it from a lower score.

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 on when to use this tool versus its siblings compare_criteria or compare_table. The only usage hint is 'optionally filtered by a tag value,' which conveys capability but not selection criteria, prerequisites, or exclusions. An agent must infer when this tool is the right choice.

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?

The description does add behavioral context beyond the tool name by stating the table covers 'every criterion' and is 'the full table.' However, there are no annotations, so the description carries the full burden for disclosing side effects, read-only status, filtering behavior, or output format; none of these are explicitly addressed.

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 table's content and ends with a clarifying 'the full table.' The em-dash restatement is slightly redundant but not wasteful, and the 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?

Given only one optional parameter and no output schema, the description plus schema is adequate for making a basic call. However, it does not explain how compare_table relates to sibling tools such as compare_criteria and compare_options, and it lacks any output-shape or safety details that would compensate for the missing annotations.

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 sole parameter 'option' is already fully described in the schema with 'one option's name, else all' and schema description coverage is 100%. The description adds no extra meaning to the parameter, 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 clearly identifies the resource as the comparison table and specifies its content: 'Each option's value on every criterion.' It also signals comprehensiveness through 'the full table,' which helps distinguish it from compare_criteria and compare_options. However, it lacks an explicit verb such as 'returns' or 'lists,' so the action is only implied.

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' weakly implies that this tool is for retrieving the complete comparison rather than a subset, but the description does not explicitly say when to use it versus compare_criteria or compare_options. No alternatives or exclusions are mentioned, so routing guidance is mostly inferred.

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. It discloses that the tool returns explanatory content—including who receives details, consent wording, and confirmation process—and clarifies the described action is not a purchase or guaranteed quote. This is transparent for a zero-parameter description tool.

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 deliver the core message efficiently, front-loaded with 'Read first'. The structure is clear, though there is slight redundancy between 'States plainly what submit_enquiry does' and the subsequent explanatory content.

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 no-parameter, no-output-schema tool, the description is complete. It explains the tool's purpose, what it returns, and its relationship to submit_enquiry. An agent has everything needed to invoke it correctly without ambiguity.

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 no parameters, so the baseline is 4. The description adds context about what the tool returns, which is meaningful for an agent deciding whether to call it.

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 explicitly states the tool's function: 'States plainly what submit_enquiry does on Answering Service Compare' and enumerates key facts (no purchase, no guaranteed quote, free). This clearly distinguishes it from siblings like submit_enquiry and compare_* tools, which perform actions or comparisons rather than explaining them.

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' provides explicit guidance to use this tool before engaging with submit_enquiry. It implies the appropriate timing and context, though it does not explicitly name alternatives or state when not to use other sibling tools.

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 what the tool does. It discloses the exact categories of information returned and implies a read-only, metadata-retrieval behavior. It does not explicitly state 'no side effects', but nothing suggests mutation and the downstream instruction is consistent with a safe listing operation.

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 concise sentences, front-loaded with the core purpose and followed by a practical usage note. Every sentence earns its place, and there is no redundant or filler content.

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 no-parameter, no-output-schema tool, the description is complete: it explains what data will be in the response and how to use that data in the related workflow. An agent can confidently invoke this tool and 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?

The tool has zero parameters, so the baseline is 4. The description adds useful meaning by explaining that the returned field keys are intended to be used as answer keys for submit_enquiry, which is more than the empty schema provides.

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 precisely what the tool provides: every field of the Answering Service Compare enquiry, including key, label, type, required status, help text, and options. This clearly distinguishes it from the sibling tools that compare or submit, and it also explains the relationship to 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 gives concrete usage guidance by telling the agent to pass answers to submit_enquiry keyed by the field keys returned here. It does not explicitly list when not to use this tool or compare it to enquiry_describe, but the intended workflow 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 full burden and handles it well. It discloses the two-step validation flow, the confirmation token handoff, the consent requirement, the post-submission email, and the click-before-provider-visible behavior, giving the agent a clear model of side effects and sequencing.

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 every sentence earns its place, covering workflow, consent text, and email behavior. It is front-loaded with the key caveat (not a purchase/quote) and structured as clear numbered steps, making it easy for an agent to follow.

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-gated submission tool with no output schema, the description is complete: it explains what each step returns, what the agent must show the user, when to proceed, and what happens after submission. Nothing critical is missing for correct invocation.

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%, but the description adds crucial semantics beyond the schema: answers are keyed by field key from enquiry_fields, consent must match the exact consent statement, and confirmation is the token returned from step 1. This turns otherwise generic parameters into a coherent 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') and clearly differentiates the tool from a purchase or guaranteed quote. It also conveys the two-step nature in the title and description, making its role distinct from the sibling comparison and enquiry-description 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 gives explicit step-by-step usage conditions: call once with answers and consent to get a summary and token, then call again only after the person agrees. It also states when not to use this tool ('NOT a purchase, NOT a guaranteed quote'), which is strong usage guidance.

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