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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 disclosing behavior. It only says this is the first question; it does not state whether calling the tool resets guide state, returns a question payload, requires prior setup, or is idempotent. An agent cannot predict side effects or the nature of 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 a single sentence with no filler, and it places the actionable role ('first question') right at the start. It is as concise as it could be while still conveying purpose.

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 must explain what the caller receives or what happens after invocation. It only identifies the step position in a guide, leaving the return value, state effects, and relationship to subsequent tools unexplained.

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 schema coverage is 100%, so there is nothing for the description to add about parameter meaning. The baseline of 4 is appropriate for a parameterless tool.

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 the entry point to the 'What can your business apply for?' decision guide, using 'first question' to convey a specific role. It is distinguishable from siblings like checker_answer and submit_enquiry, though it could more explicitly state that it initializes or fetches the starting question.

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 phrasing 'first question' implies the tool should be called when beginning the decision guide, but it does not explicitly state when not to use it or mention any alternative flow. The sibling names suggest checker_answer or checker_tree might be used after starting, but this routing is not spelled out.

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 communicates that the tool exposes all questions, options, and verdicts, which conveys a read-only, complete-content behavior. It does not describe the structure, size, or any potential caveats, but for a static reference tree this is a moderate 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, well-formed sentence that front-loads the core idea ('Every question, option and verdict') and adds only the relevant purpose. No filler or 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 zero-parameter tool with no output schema, the description is reasonably complete: it states the contents and suggests a use case. It could mention the return format or that it is a static dataset, but the simplicity of the tool makes the existing description adequate.

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 with 100% coverage. Per baseline, a 4 is appropriate since there are no parameter meanings to clarify, and the description correctly implies no input 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 the resource (the entire decision tree) and its content (every question, option, verdict). The phrase 'whole decision tree' differentiates it from sibling tools like checker_start and checker_answer without needing to name them, though it stops short of explicitly stating a verb like 'retrieves'.

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' implies this tool is appropriate when an agent needs the complete tree in one shot, rather than stepping through it one node at a time. However, it does not explicitly state when to use it over checker_start or checker_answer, nor does it provide exclusion criteria.

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 disclosure. It explains what the tool returns: who receives the details, the consent wording, and how the person confirms. It also clarifies that the underlying enquiry involves no purchase, no guaranteed quote, and is free. It does not explicitly state that enquiry_describe itself is read-only and side-effect-free, but the non-mutating verb 'states' and the 'Read first' framing strongly imply 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 compact and front-loaded with the most important instruction ('Read first'). Every clause adds relevant information about the enquiry flow and the tool's output, with no filler or repetition.

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 describe tool with no output schema, the description is complete. It tells the agent what the tool does, what behavioral context matters (free, no purchase, no guaranteed quote), and what the returned information covers (recipients, consent wording, confirmation process).

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 description coverage, so there are no parameter semantics to clarify. The baseline of 4 applies because the description does not need to compensate for any undocumented parameters.

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 function: it explains what submit_enquiry does on Business Grants Finder, including the fact that it starts an enquiry with human providers. It distinguishes itself from submit_enquiry by describing rather than performing the action, though it does not explicitly differentiate from the checker_* siblings.

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 'Read first' provides clear context that this tool should be consulted before submitting an enquiry. It implies the agent should use this tool to understand the flow before calling submit_enquiry, but does not explicitly list when not to use it or compare it with sibling 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?

With no annotations, the description carries the burden of behavioral disclosure. It clearly describes what the tool returns, but it does not explicitly state that it is a read-only operation with no side effects, nor does it mention any limitations or error behavior. The content is accurate and useful, but the absence of an explicit read-only statement is a small 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 two sentences long with no wasted words. The first sentence defines the return value precisely, and the second sentence connects it to the submission workflow. The most actionable information 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?

The description is complete enough for a simple metadata-retrieval tool, especially since there is no input schema and no output schema to lean on. It explains the contents of the response and how to use it. It could benefit from a small example or an explicit note that it performs no submission, but the prose already covers the essential 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?

The tool has zero parameters, so there is nothing for the description to clarify. The baseline of 4 applies because no parameter documentation is needed, and the description meaningfully explains how the output relates to submit_enquiry.

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 returning metadata about every field in the Business Grants Finder enquiry, listing the specific attributes (key, label, type, required, help text, options). The title reinforces this. It does not use an explicit verb like 'retrieve' or 'list', and it does not explicitly contrast itself with sibling enquiry_describe, so it stops short of 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?

The description gives practical usage guidance by telling the agent to pass answers to submit_enquiry keyed by field key. This implies the tool should be consulted before submitting answers. It does not explicitly state when not to use it or how it differs from enquiry_describe, but the guidance is sufficient for the common workflow.

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, and it does: it discloses validation behavior, what step 1 returns (summary, consent line, token), the human-approval gate between steps, and the post-submission email-verification requirement before any provider sees the data. It also spells out exactly what consent means, which is a real side effect on the person's contact details.

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?

Front-loaded with the disambiguation, then the two steps in order, so an agent can act on the first sentence alone. The verbatim consent sentence duplicates the schema's consent description, which is mild redundancy, but it is arguably necessary since the agent must show that text to the person.

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?

Despite having no output schema, the description explains what each step returns (summary, consent line, confirmation token) and what happens after submission (email link, click required, then providers see details). Nothing an agent needs to call this correctly or to explain it to the person 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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema: answers are keyed by field keys obtained from enquiry_fields, consent must be true, and confirmation is specifically 'the confirmation token from step 1, after the person has approved the summary'. That ties the parameters to the workflow state, which the schema alone does not.

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?

States a specific verb (submit) and resource (enquiry to Business Grants Finder) and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote'. An agent can distinguish it from enquiry_fields/enquiry_describe/checker_* siblings without opening any schema.

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?

Gives an explicit two-step protocol: step 1 with answers+consent=true, then step 2 'only if the person agrees' with the same answers plus the confirmation token. The gating condition for each call is spelled out rather than implied.

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