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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 behavioral disclosure. It states the subject matter—criteria and filters—but does not disclose whether the tool is read-only, what the response shape is, whether it returns a list or a detailed narrative, or whether any side effects exist. For a tool with no annotation safety hints, this is a meaningful gap.

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 with no filler words, making it concise and easy to parse. It front-loads the core resource before the qualifying context. It loses a point because the wording is slightly awkward and spends no effort clarifying the action or usage.

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 tool with no output schema and no annotations, the description minimally explains what the tool is about. It is enough to understand the subject matter but does not fully equip an agent with the expected return behavior or the relationship to sibling tools. Given the low complexity, this is acceptable but not 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 description coverage is 100%, so there are no parameter semantics to document. The description adds useful context by clarifying that the tool concerns the criteria and filters of the 409A valuation comparison, which helps the agent understand what the empty-parameter call will provide.

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 the 409A valuation providers comparison for US startups. It also distinguishes this tool from siblings like compare_options and compare_table by indicating this is about the underlying criteria rather than the comparison output itself. However, it is phrased as a noun phrase rather than a verb phrase, so it does not explicitly state an action such as 'returns' or 'describes'.

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 call this tool versus its siblings. The description does not mention using it before compare_options/compare_table, nor does it exclude cases where another tool would be more appropriate. An agent must infer the intended usage from the tool name and title alone.

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 does reveal the output fields and the optional tag filter, which is useful, but it never explicitly states that the tool returns a list or how the filter behaves when omitted. There is no mention of ordering, default behavior, or error cases.

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 with no filler words, which is efficient. However, it reads more like a noun phrase than a functional tool description, and important behavioral information is missing. It is concise but at the cost of completeness.

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 fully explain what the tool returns, how filtering works, and what each parameter means. It partially covers return fields and optional tag filtering, but it does not explain filterKey, the exact return shape, or the distinction from sibling comparison tools. This is inadequate for an agent to invoke the tool with confidence.

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 by explaining filterKey and filterValue. It only mentions filtering 'by a tag value,' which partially explains filterValue but leaves filterKey entirely unclear. The relationship between the two parameters and acceptable values is not specified.

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 options in the 409A valuation providers for US startups comparison') and lists the returned fields (name, what it is best for, tags), so it is not a pure tautology. However, it lacks an explicit verb such as 'list', 'return', or 'get', making the tool's action ambiguous. The title 'The options' reinforces the noun-phrase style without clarifying behavior.

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 implies the tool is used to view options, optionally filtered by tag, but it gives no explicit guidance on when to choose this tool over its siblings like compare_criteria or compare_table. There are no exclusions, prerequisites, or decision rules. An agent would have to infer usage context from the tool name and siblings.

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 of behavior disclosure. It conveys that the result is a full table covering every option and criterion, which is useful. However, it does not describe the table layout, output format, or how the optional 'option' parameter affects behavior beyond what the schema already states.

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 no filler or redundant content. The minor weakness is that it is phrased as a noun phrase rather than an explicit verb-led instruction.

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 query tool, the description conveys the core output and scope. However, it omits any guidance on how this tool relates to its siblings, and with no annotations it provides no behavioral or safety context beyond the basic content of the 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?

Schema coverage is 100%, and the parameter description 'one option's name, else all' fully documents the meaning. The description adds no additional parameter semantics, but none are needed given the schema's clarity.

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 clearly: a full comparison table of 409A valuation providers for US startups, covering each option's value on every criterion. However, it lacks an explicit verb and does not directly distinguish this tool from the sibling compare_criteria or compare_options 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 guidance is given about when to use compare_table versus compare_criteria or compare_options. The phrase 'full table' implies broad use, but there is no explicit context, alternative, or condition for selecting this 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 burden. It discloses meaningful behavioral context: nothing is bought or paid for, no quote is guaranteed, it is free, and it returns who receives details, consent wording, and confirmation method. This goes beyond a simple 'returns summary' statement and helps the agent set user expectations.

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, front-loaded with 'Read first,' and every sentence contributes meaning. It efficiently covers purpose, scope, exclusions, cost, and return content without redundancy.

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-input, no-output-schema documentation tool, the description is complete: it explains what the tool does, what it returns, and the key behavioral caveats. An agent would know exactly what to expect and how to use the 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 and 100% schema coverage, so the baseline of 4 applies. There are no parameters for the description to explain, and nothing in the description is misleading or missing regarding inputs.

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 role: it 'States plainly what submit_enquiry does' on 409A Providers and returns the details of that enquiry process. It distinguishes itself from the action-oriented submit_enquiry sibling by explicitly positioning itself as the pre-action explainer, and clarifies what it is not ('not a purchase, not a guaranteed quote').

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 instruction 'Read first' gives clear usage context: this should be used before acting on submit_enquiry. It implies when to use the tool, but it does not explicitly name alternatives or state when not to use comparably named siblings like enquiry_fields or compare_options. This is a clear but not fully explicit 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 behavioral disclosure burden. It communicates that the tool is a read-only metadata listing and details the returned field attributes, which is the relevant behavior for a zero-parameter query. It could have been more explicit about the operation being a retrieval with no side effects, but nothing in the text contradicts or obscures that.

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 compact sentences carry all the essential information: the field inventory and the relationship to submit_enquiry. The content is front-loaded and every clause contributes value.

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 parameterless metadata tool, the description covers the return content and how to consume it, which is sufficient to call it correctly. It leaves the distinction from enquiry_describe implicit, but the title and tool name already hint at the difference, so this is a minor gap.

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 an empty input schema, so there are no parameter semantics for the description to clarify. The description correctly avoids inventing parameter details and instead focuses on the output fields.

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 as exposing every field of the 409A Providers enquiry, enumerating the exact contents (key, label, type, required, help text, allowed options). It lacks an explicit verb like 'lists' or 'returns,' but the meaning is unambiguous and distinguishable from the sibling submit_enquiry by naming the field metadata.

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 clear context for use: answers should be passed to submit_enquiry keyed by the field key, which tells an agent why this metadata matters. It does not explicitly mention when-not-to-use it or name alternatives such as enquiry_describe, so it falls just 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 burden and covers it well: it discloses validation, the step-1 return values, the email link requirement before providers see the enquiry, the exact consent wording, and the consequence of proceeding. No annotation contradiction exists.

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?

Although longer than typical descriptions, every sentence carries operational weight, and the most important caveat ('NOT a purchase') is front-loaded. The step numbering keeps the two-phase contract scannable, and the consent quote is necessary verbatim text.

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 two-step mutation tool with no annotations and no output schema, the description explains return values of step 1, the required user consent step, and the post-submission email-link behavior. The only omitted details (e.g., step 2 return value, error handling) are minor against this coverage.

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 critical protocol semantics: answers must be keyed from enquiry_fields, consent=true is the agreement, and confirmation is the token produced in step 1 for use in step 2. This goes beyond the schema's bare property definitions.

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 opens with a specific verb and resource ('Submits an enquiry to 409A Providers') and immediately adds exclusions ('NOT a purchase, NOT a guaranteed quote'). This makes it unambiguous against sibling tools like compare_options or enquiry_describe, and the two-step nature is stated clearly.

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?

It gives a complete step-by-step protocol: call with answers and consent first, show the summary and consent line, then call again with the confirmation token only if the person agrees. It also states when not to use it ('NOT a purchase') and references enquiry_fields for answer keys, giving the agent enough routing information.

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