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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 behavioral disclosure. It fails to state what comparison is performed, what inputs it considers, what side effects exist, or what result is produced.

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 its malformed grammar and unclear phrase 'Arrangements for getting a formulation made comparison' undermine the structure. It is under-specified rather than genuinely concise.

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?

Without output schema, annotations, or usable behavioral description, an agent has no way to know what compare_criteria does, what it returns, or why it exists alongside compare_options and compare_table.

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 already fully documents the parameter surface. The baseline for 0-parameter tools is 4; no parameter semantics are needed.

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 essentially a garbled restatement of the title: it mentions 'criteria' and 'comparison' but contains no clear verb or action. It does not distinguish compare_criteria 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 any alternative. The sibling tool names suggest related compare/enquiry operations, but the description gives no context for choosing among them.

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 of behavioral disclosure. It does not state whether the operation is read-only, what side effects exist, or the format of the response. The only behavioral hint is optional filtering, which is insufficient.

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 convoluted sentence that is not front-loaded. Key information like 'optionally filtered' appears at the end, and the phrasing 'Arrangements for getting a formulation made comparison' is unclear. It is short but not concise in meaning.

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 2 parameters, no output schema, and no annotations, the description is inadequate. It does not explain what 'Arrangements' refers to, what the options represent, or the expected return structure. An agent would struggle to call this tool correctly without additional context.

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 two parameters, filterKey and filterValue. It only hints that filtering is by tag value, but does not explicitly map filterKey to a tag name or explain how they interact. This adds minimal value beyond the raw 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 states what data is returned (name, what it is best for, tags) but lacks a clear verb like 'list' or 'get'. It does not distinguish this tool from siblings like compare_criteria or compare_table, and the phrase 'Arrangements for getting a formulation made comparison' is confusing. The purpose is vague and not actionable.

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 mentions optional filtering by tag value, but provides no guidance on when to use this tool versus alternatives such as compare_criteria or compare_table. There are no exclusions or conditions, so an agent gets no direction on 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only names the result content ('full table') and never states whether the call is read-only, what the output structure is, or whether any side effects or permissions are involved.

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 long, grammatically convoluted sentence ending with a dash clause. It is short but not concise in effect, because the awkward phrasing requires more parsing effort than a plain 'Returns the full comparison table of each option on every criterion.'

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 needs to state what is returned and how the optional option parameter changes the result. It gestures at the full table but never clarifies the return shape, the default 'all options' behavior, or the filtering effect, leaving an agent 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?

Schema description coverage is 100%: the schema already documents the single optional parameter as 'one option's name, else all'. The description adds no parameter-level meaning, so the baseline of 3 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 phrase 'Each option's value on every criterion' identifies the comparison content and implies a full cross-comparison, which broadly distinguishes it from siblings like compare_criteria and compare_options. However, there is no operative verb such as 'returns' or 'shows', and the sentence 'Arrangements for getting a formulation made comparison' is grammatically tangled, making the intended action only inferable.

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 this tool is for getting the complete comparison rather than a partial one. But it gives no explicit when-to-use guidance, no exclusions, and does not name or contrast any sibling tools, so the routing signal is minimal.

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 transparently states that the tool 'returns who receives the details, the consent wording, and how the person confirms,' indicating it produces informational output. It also clarifies that the described process involves no purchase, no guaranteed quote, and is free, giving the agent a clear picture of what to expect. The description does not reveal any side effects because the tool itself is purely descriptive, which is appropriately disclosed.

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 paragraph that is well-structured, front-loading the key instruction 'Read first' and then succinctly summarizing the tool's purpose and output. It is efficient, covering the essential points without extraneous detail. It earns a 4 rather than 5 because it could be slightly tightened (e.g., merging the first and second sentences), but it remains clear and scannable.

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 fully covers what an agent needs: the purpose (explaining submit_enquiry), the scope (what is and isn't included), and the return content (who receives details, consent wording, confirmation process). There is no ambiguity about how to invoke it or what to expect, making it complete for the agent's decision-making.

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 coverage is trivially 100% and there is no parameter documentation to supplement. The baseline for 0 parameters is 4, and the description correctly avoids inventing parameter details. It focuses on the tool's output and context rather than inputs, which is appropriate since there are none.

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: it describes what submit_enquiry does on Toll Blenders, distinguishing it from actually submitting an enquiry. It clearly separates this descriptive tool from sibling tools like submit_enquiry and enquiry_fields by framing it as a 'read first' guide. The verb 'describes' plus the specific resource (submit_enquiry behavior) makes the purpose unambiguous.

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 opens with 'Read first,' which directly instructs when to use this tool: before using submit_enquiry. It further explains what the tool provides (clarifications about the enquiry process, what is not included, and what the user will receive), making the context clear. While it doesn't explicitly name alternatives or say when not to use it, the 'read first' directive and the contrast with submit_enquiry imply it should be used as a precursor, which is sufficient guidance for this passive informational tool.

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 disclosure burden. It usefully describes the response content and the conditional nature of allowed options ('where there are any'), but it never explicitly states that this is a read-only introspection call, nor does it disclose ordering, caching, or failure 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?

Two dense sentences with zero filler. The first states what is returned; the second adds the downstream usage payload. Both earn their 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 zero-parameter metadata-listing tool with no output schema, the description explains what the return carries and how it feeds into submit_enquiry. It could add an example or enumerate the 'type' values, but nothing essential is missing for invoking 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?

The tool has zero parameters and 100% (vacuously) schema coverage, so there are no input semantics to clarify. The description's 'Every field' phrasing correctly implies an unfiltered, all-fields response, which is consistent with an empty input 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 ('Every field of the Toll Blenders enquiry') and enumerates its contents (key, label, type, required, help text, allowed options). The verb is only implied by the tool name rather than stated, and it doesn't differentiate from enquiry_describe, but the overall purpose is unambiguous.

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 provides concrete usage guidance: obtain field keys here, then pass answers to submit_enquiry keyed by those keys. This tells the agent when this tool is needed in the workflow, though it does not explicitly exclude alternatives or name when not to use 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, and it delivers: it discloses validation behavior, the two-step confirmation-token flow, the email-with-link requirement, and that providers only see the enquiry after the link is clicked.

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 lengthy but purposeful, opening with the key caveat 'not a purchase/quote,' then structuring step 1 and step 2 clearly. The exact consent wording is necessary and all sentences earn their place, though it is somewhat dense.

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?

Explains what step 1 returns (summary, consent line, confirmation token), how to proceed to step 2, and what happens after submission (email link, provider visibility). This is complete enough for an agent to invoke the tool correctly even without an output schema or 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?

Though schema coverage is 100%, the description adds significant meaning beyond the schema: answers must be keyed by field key from enquiry_fields, confirmation is the token from step 1, and consent is the exact quoted agreement text that must be true.

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?

Clearly states it submits an enquiry to Toll Blenders, explicitly negates that it is a purchase or guaranteed quote, and outlines a two-step submission process. This differentiates it from sibling tools like compare_* and enquiry_fields.

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 usage guidance: step 1 validates and returns a confirmation token; step 2 submits only after the person agrees. References enquiry_fields for answer keys and specifies consent=true requirements, though it does not explicitly name alternative tools.

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