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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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It does not describe what the tool returns, whether it initiates a flow, asks a question, or changes state—leaving the agent with no behavioral information beyond the title.

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 concise sentence with no waste, but it is under-specified rather than efficiently informative. It is short without adding meaningful behavioral or usage detail.

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 no annotations, no output schema, and only a positional description, an agent cannot determine what invoking this tool will do, what to expect in response, or how to proceed afterward. Low parameter complexity reduces the burden, but the behavioral vacuum remains significant.

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 with an empty properties object, so there is no parameter ambiguity for the description to resolve. Baseline 4 applies for parameterless tools.

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 this as the first question of a decision guide, which conveys a clear entry-point role. However, it is a noun phrase rather than a verb+resource statement, and it does not say what actually happens when invoked beyond that positional role.

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 'first question' implies that this tool starts the guide, but there is no explicit statement of when to use it versus checker_answer or enquiry_* siblings. No conditions, exclusions, or alternative routing are provided.

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?

Annotations are absent, so the description carries the full burden of behavioral disclosure. It only lists the content contained (questions, options, verdicts) but does not state whether this is a static read-only dump, whether it has side effects, or what the agent should do with the returned information. The lack of any safety or mutation hints is a notable 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 very short and front-loads the key content coverage. The phrase 'Check an agent in four questions guide' is slightly awkward, but the sentence is otherwise compact 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?

For a zero-parameter, static-content tool, the description gives a reasonable idea of the payload, but it does not explain how this tree relates to the sibling tools or when an agent should consult it. With no output schema and no annotations, a bit more context (e.g., 'use this to understand all branches before invoking checker_start') would make it 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, so the baseline is 4. There is nothing for the description to add about parameters; the description correctly focuses on content rather than input semantics.

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 the tool provides every question, option, and verdict of the decision guide, which clearly identifies the resource and scope. It is distinguishable from siblings like checker_answer and checker_start by being the complete tree, though it lacks an explicit verb like 'retrieve' or 'return'.

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 when-to-use guidance is provided. The description does not mention when an agent should call this tool instead of siblings such as checker_answer or checker_start, nor does it specify whether it is meant for initial orientation, debugging, or end-to-end traceability.

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 safety burden. It clearly frames the tool as descriptive/read-only ('States', 'returns') rather than performing the enquiry, and it surfaces key facts about the enquiry (no purchase, no guaranteed quote, free). It does not explicitly say 'no side effects,' but the wording makes that evident.

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?

Three short sentences, front-loaded with the 'Read first' directive, and every clause adds either scope, a caveat, or a return detail. 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?

For a parameterless, read-only explainer with no output schema, the description covers purpose, when to call, and what it returns (who receives details, consent wording, confirmation process). Nothing important is missing for an agent to call it 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 an empty schema, so there is no parameter meaning to add. The description focuses on the return content, which is the only input-free behavior an agent needs; baseline 4 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 description names the exact action ('states plainly what submit_enquiry does') and the resource (Football Agent Index enquiry flow), making clear this is an informational read, not the submission tool itself. It also lists concrete output contents, so an agent will not confuse it with the sibling submit_enquiry.

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' is an explicit instruction to invoke this before acting, and the description ties it directly to submit_enquiry. It does not spell out when to avoid it or compare with checker_* siblings, so it stops short of full alternative-based 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 provided, the description carries the full behavioral burden. It discloses that the tool returns field metadata rather than performing a mutation, and it enumerates what information is available. It does not explicitly state that the tool is read-only, but the metadata-listing nature makes that sufficiently 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?

The description is two sentences with no filler. It front-loads the key metadata attributes, then ends with a concise, actionable usage note. Every sentence 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 tool with no parameters, no annotations, and no output schema, the description provides exactly what an agent needs: what the tool returns, the structure of that return, and how to use the returned keys. It is complete for this low-complexity tool.

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 no parameters, which earns a baseline of 4. The description adds useful semantic context by indicating that the returned field keys are the exact keys to use for submit_enquiry, which helps the agent connect this tool's output to the next step.

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 this tool exposes every field of the Football Agent Index enquiry along with metadata such as key, label, type, required status, help text, and allowed options. It differentiates itself from submit_enquiry by explaining that answers should be passed using these field keys, though it does not explicitly contrast with 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 second sentence gives actionable usage guidance: call this tool to discover field keys, then use those keys when calling submit_enquiry. This establishes clear context for when to use the tool, though it does not explicitly discuss when not to use it or name 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 full burden and does so: it discloses the validation-and-summary behaviour of step 1, the exact return values (summary, consent line, confirmation token), that step 2 is what actually submits, and the downstream email-verification gate before any provider sees the details. It also spells out the consent semantics, the 'up to three' firm limit, and the right to stop further firms.

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 critical distinction and then ordered by step, so an agent can act on the first sentence alone. The full verbatim consent text is duplicated from the schema's consent description, which is the one portion that does not earn its place here.

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 no output schema and a nested answers object, the description explains both what is returned at each step and what happens after submission (email link, provider visibility gate, contact rights). An agent has everything needed to drive the two-call flow 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: answers must be keyed by field key from enquiry_fields, consent must be true only on genuine agreement, and confirmation is only supplied on the second call. The confirmation token's step-2-only usage is genuinely beyond what the schema states.

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 (submits) and resource (an enquiry to human providers), and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote'. It also cross-references the sibling tool enquiry_fields as the source of the answer keys, so an agent can place it against checker_* and enquiry_describe without opening a 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 to validate and get a token, step 2 only after the person agrees, re-sending answers, consent and the token. It states the precondition (person approval) and the consequence of each call, leaving nothing to inference.

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