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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. It does disclose the key behavior—returning either the next question or a final verdict—but it does not mention whether the flow state is mutated, what happens for invalid choices, or any session/state requirements.

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, information-dense sentence. The title and description work together without repetition or filler, and the key input/output behavior is front-loaded.

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?

Adequate for a two-parameter tool: it names both inputs and describes the possible return. However, with no output schema and no annotations, it falls short of fully describing the response shape, error behavior, or what the caller should do with the returned next question/final verdict.

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 0% description coverage, so the description's clarification that `question` is a question id and `choice` is the chosen option's index is essential. It adds meaning beyond the raw property names and types, though it omits details like how to obtain valid question ids or bounds beyond minimum 0.

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 operation: given a question id and a choice index, return the next question or final verdict. This clearly differentiates it from sibling tools like checker_start or checker_tree, which have different roles in the flow.

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?

Usage is implied: use this when a user has answered a question and the flow should advance. However, it does not explicitly state when not to use it, what prerequisites exist (e.g., starting with checker_start), or how it relates to alternatives.

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 revealing call semantics. It only states that this is the first question, without indicating whether invocation is read-only, whether it resets or initializes state, or what the agent should expect in the response.

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 one short sentence with no wasted words. It is efficiently structured, though it partly restates the title and could have used its brevity to add behavioral or output context.

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 entry point, the description gives a minimal but recognizable sense of purpose. However, because there is no output schema, the description should more explicitly describe what is returned, such as the first question text and available answers, or how the agent should proceed afterwards.

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 input schema is empty, so the schema fully documents the parameter surface. With no parameters to explain, the baseline of 4 applies and the description does not need to add parameter-level detail.

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 tool as the first question in a 409A safe harbour decision guide, so an agent can infer it is the entry point. However, it is phrased as a noun phrase rather than an action ('returns', 'starts'), and it does not explicitly differentiate it from sibling tools such as checker_tree or checker_answer.

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 any alternative. It does not state that this is the recommended starting point, nor does it mention sibling tools for continuing the guide, such as checker_answer or checker_tree. Prerequisites and conditions for use are also absent.

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 discloses that the tool returns the entire set of questions, options, and verdicts in the guide, which is the key behavioral trait. However, it does not mention output format, size, or how the tree is structured, leaving some ambiguity about the exact response shape.

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 that immediately communicates the tool's complete scope. It is front-loaded with the most important information and contains no filler.

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 zero-parameter schema and simple resource type (a full decision tree), the description is largely sufficient: it names the content, its purpose, and the scope of coverage. The main gap is the lack of detail about what the returned tree looks like, but this is minor for a tool whose function is straightforward.

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 100% coverage, so there is nothing for the description to add about parameter meaning. The baseline of 4 applies here because the lack of parameters makes parameter documentation trivial.

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 resource ('the whole decision tree' for the 409A safe harbour guide) and its scope: every question, option, and verdict. It is distinct from sibling tools like checker_answer or checker_start because it emphasizes full-tree coverage for end-to-end reasoning, though it does not explicitly name those alternatives.

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 'for reasoning end to end' clearly implies this tool should be used when an agent needs the complete decision tree rather than a single step or answer. It gives clear context for when to invoke it, though it does not explicitly contrast it with checker_answer or checker_start.

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 of behavioral disclosure. It does reveal the informational nature by saying 'States plainly' and 'Also returns', and it sets expectations about free, non-binding enquiries. But it never explicitly says that enquiry_describe itself is read-only and triggers no external action, which is a meaningful omission given the possible confusion with submit_enquiry.

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 concise and front-loads the main purpose, but the structure is somewhat awkward: the fragment 'Read first.' is terse and the clause 'Also returns...' lacks a clear grammatical subject. The sentence flows could be tightened and reorganized for better readability while preserving the same 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?

For a zero-parameter informational tool, the description conveys the core purpose and some return details. However, it does not explicitly state that calling this tool is harmless and does not submit anything, and the relationship to submit_enquiry as a pre-submission explanation is only implied by 'Read first.' This leaves room for an agent to misunderstand the tool's side effects and role.

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% (vacuously), so the baseline is 4. The description adds context about the kind of content returned, which is sufficient for an agent to know what to expect. No parameter explanation 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 states that the tool's role is to 'state plainly what submit_enquiry does on Get 409A Valuation', identifying it as an explanatory resource for the sibling tool. It differentiates itself by naming submit_enquiry and contrasting with purchase/quote. However, the sentence 'Also returns...' has an ambiguous subject, making it slightly unclear whether the tool itself or submit_enquiry returns that information.

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?

'Read first' gives an explicit usage context, implying this should be consulted before taking any enquiry-related action. It also clarifies that no purchase or guaranteed quote is involved. However, it does not reference sibling tools like enquiry_fields or checker_start, nor does it explicitly state when not to use this tool, leaving some usage guidance implied rather than explicit.

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?

There are no annotations, so the description carries the burden of explaining behavior. It discloses the exact return contents and the relationship between field keys and submit_enquiry. It does not explicitly state that the call is read-only or side-effect-free, but the zero-parameter metadata nature makes that clear from context.

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 first sentence states the tool's scope and content, and the second connects it to the next action. Every part 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 zero-parameter tool with no output schema, this is complete. It explains what is returned, the attributes included, and how to use the result with submit_enquiry. Nothing essential for calling this tool 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 input schema has zero parameters and schema description coverage is 100%, so there is nothing for the description to add about parameters. The description appropriately focuses on the output and downstream usage instead.

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 providing every field of the Get 409A Valuation enquiry and enumerates exactly what each entry includes: key, label, type, required status, help text, and allowed options. It stops short of an explicit verb like 'lists' or 'returns', and it does not differentiate itself from the sibling enquiry_describe, so it misses a 5.

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 concrete downstream instruction: pass answers to submit_enquiry keyed by field key. This implies the output should be used to construct a submission, but it never explicitly says when to choose this tool over sibling tools or 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, the description carries full behavioral disclosure: it warns that this is not a purchase or guaranteed quote, explains that step 1 only validates, and discloses that submission triggers a customer email with a mandatory click before providers see the enquiry. It also specifies the exact consent meaning.

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 and step-organized, with the key non-purchase warning front-loaded. It is longer than minimal because it must encode a two-step workflow and exact consent text, but most sentences carry necessary information; a slight redundancy with the title's 'not a purchase' keeps it from a 5.

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 tool with no output schema, the description covers everything needed: what step 1 returns (summary, consent line, confirmation token), what to show the person, when to make the second call, and the post-submission email-link behavior. Nested answers are explained via field keys, leaving no critical gap for an agent.

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 baseline is 3, and the description adds meaningful semantics: answers must be keyed by enquiry_fields keys, consent must match the exact consent statement, and confirmation is the token returned from step 1. This clarifies relationships between parameters beyond the schema field names.

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 Get 409A Valuation') and immediately disambiguates it from a purchase or guaranteed quote. The title reinforces the two-step nature, and the description references enquiry_fields for field keys, making its role in the workflow clear.

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 an explicit two-step invocation sequence: first call with answers and consent=true to obtain a summary/token, second call with the token only after the person agrees. It does not explicitly compare against sibling checker tools, but it clearly states the conditions and decision point for using the tool.

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