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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 explaining behavior. It merely names the content ('criteria and any filters') and does not disclose whether the tool performs a read operation, returns data, requires authentication, has side effects, or provides any output format. This is a significant gap for a tool with no annotation support.

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 front-loaded with domain context, but it is a grammatically incomplete noun phrase rather than a clear instructional statement. It earns no extra credit for efficiency because it sacrifices clarity for brevity.

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 the absence of annotations and an output schema, the description should provide more operational context. It leaves unclear what the tool actually returns, how an agent should use the result, and how it fits alongside sibling tools. The description is too thin for reliable tool selection and 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?

The tool has zero parameters and the schema coverage is 100%, so there are no parameter semantics that the description needs to explain. The baseline of 4 is appropriate because the description is not required to compensate for missing 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 identifies a specific resource—the criteria and filters of a US 409A valuation providers and cap table platforms comparison—so the subject is clear enough. However, it lacks a verb and does not explicitly state what the tool does with these criteria (e.g., returns, displays, exports), leaving the operation implied rather than stated.

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 its siblings like compare_options or compare_table. The description does not state conditions, exclusions, or how to choose between the comparison-related 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, the description carries the burden for behavioral disclosure. It reveals the output content and an optional tag-filtering behavior, but does not describe the return shape, pagination, sorting, or whether filterKey is fixed to a specific value. These are meaningful gaps for a tool with no annotation coverage.

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 with the resource and filter behavior front-loaded. It wastes no words, though the title 'The options' adds nothing.

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 undocumented optional parameters, no annotations, and no output schema, the description is too thin. It does not explain parameter mapping or valid filter values, nor does it reference sibling tools to prevent misuse.

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 vaguely mentions filtering 'by a tag value.' It does not explain what filterKey/filterValue mean, how they interact, or what valid tag values are, leaving the two parameters effectively undocumented.

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—options in the US 409A valuation providers and cap table platforms comparison—and lists their fields (name, best-for, tags), which lets an agent distinguish this from sibling tools like compare_table. It lacks an explicit verb such as 'list' or 'get', but the intent is clear enough.

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 'in the US 409A valuation providers and cap table platforms comparison' phrase provides context for when this tool is relevant, and the optional filtering behavior is noted. However, it never states when to prefer this over siblings like compare_criteria or compare_table, nor gives any when-not 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 must carry behavioral disclosure. It states the output is the full comparison table with no hidden filtering, but it does not describe output format, pagination, size, or any other invocation-relevant 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?

A single sentence that conveys content, scope, and domain context without repeating the title. Every phrase 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 simple one-parameter tool the description is mostly adequate, but with no output schema and no annotations, an agent still lacks detail about the return shape and has no guidance for selecting among compare_table, compare_criteria, and compare_options.

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%, so the schema already documents the only parameter, 'option'. The description adds no parameter-specific meaning, which matches the baseline of 3; no compensation is 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 clearly identifies what the tool returns: every option's value on every criterion, presented as the full table. It distinguishes itself from sibling tools like compare_options and compare_criteria by emphasizing the complete matrix, though it lacks an explicit verb.

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 the sibling tools. The phrase 'full table' implies use when a complete view is needed, but there are no explicit conditions, exclusions, or alternative routing.

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 clearly states this is an informational description, that no purchase or payment occurs, and that the tool returns details about recipients, consent wording, and confirmation. It does not explicitly say 'read-only', but the content strongly implies it.

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 about 50 words, opens with a clear directive, and every sentence adds either scope, caveats, or return content. The title also front-loads the core contract in a memorable way.

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 informational tool with no output schema, the description fully covers purpose, what the associated submit_enquiry does, and what the tool returns. Nothing essential for an agent to call it correctly 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?

The schema has zero parameters, so the baseline is 4. The description reinforces the no-input nature with 'Read first' and there is no parameter detail to compensate for because none exist.

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 verb and resource: it 'States plainly what submit_enquiry does on Cheap 409A' and enumerates the content it returns. This clearly distinguishes it from the sibling submit_enquiry by describing the action rather than performing it.

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 imperative 'Read first' explicitly tells the agent to use this tool before submit_enquiry, and the caveats about nothing being bought or guaranteed prevent misuse. It does not explicitly contrast with other siblings like enquiry_fields or compare_options, but the primary alternative is addressed.

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 does a good job: it enumerates exactly what data is returned and the conditional presence of allowed options. It does not explicitly state that the call is read-only with no side effects, but the passive phrasing 'Every field of...' makes the metadata-listing nature clear.

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 carry all the essential information with no fluff. The first sentence front-loads the purpose and content, and the second adds a direct usage pointer to submit_enquiry. Every word 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 no-parameter, no-output-schema tool, the description covers the returned field attributes and the connection to submit_enquiry. It could be slightly more explicit about the return container (list vs. object) and how this relates to enquiry_describe, but it is sufficiently complete for an agent to understand what it will get and how to use it.

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 a vacuous 100% schema coverage, so the baseline is 4. The description adds no parameter-specific detail because there are none, which is appropriate; it does not need to compensate for any schema gaps.

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 what the tool returns: every field of the Cheap 409A enquiry with its attributes (key, label, type, required, help text, allowed options). It distinguishes itself from submit_enquiry by explicitly mentioning that answers should be passed keyed by field key, though it does not use an explicit verb like 'list' or 'get'.

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, 'Pass answers to submit_enquiry keyed by field key,' implies the tool should be used before submitting an enquiry to discover valid field keys. However, it does not explicitly state when to use this tool versus siblings like enquiry_describe or the compare_* tools, leaving the routing partly to inference.

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 present, the description carries the full burden of behavioral disclosure. It explains validation, return values (summary, consent line, confirmation token), the required confirmation step, email delivery, and the click-link requirement before providers see the enquiry. It even quotes the exact consent line. This is exceptionally transparent.

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 every sentence earns its place: it front-loads the core purpose and exclusions, then organizes the two-step process in a clear, numbered structure. No fluff or redundant filler exists, despite the length being justified by the complexity of the flow.

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 the complexity of a two-step consent-based submission, the description covers everything an agent needs: preconditions, step behaviors, return values, user interaction required between steps, and post-submission effects. There is no output schema, but the description compensates by explaining what step 1 returns and what the person experiences.

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 has 100% coverage with clear descriptions for all three parameters, so the baseline is 3. The description adds value by clarifying that answers should be keyed by field keys from enquiry_fields and by explaining the temporal relationship of the confirmation token across the two steps. It could have added more detail about expected answer structures, but it does improve on 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 states a specific verb ('submits an enquiry'), a specific resource ('Cheap 409A'), and explicitly distinguishes itself from a purchase or guaranteed quote. It also clearly outlines the two-step nature of the operation, which differentiates it from sibling tools like compare_options or enquiry_describe.

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 explicit step-by-step usage instructions: when to call first with answers and consent, what to do with the returned summary and token, and when to call again with confirmation. It also gives an explicit when-not condition ('NOT a purchase, NOT a guaranteed quote'), leaving no ambiguity about how and when the tool should be used.

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