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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. The description only names the question; it doesn't disclose whether the tool is read-only, whether it mutates anything, whether it returns the question text, or whether it advances a state machine. For an agent selecting among sibling tools, this provides almost no behavioral 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?

The description is one short sentence and mentions the decision-guide name, which is contextually useful. It wastes no words, though it could have added a front-loaded verb such as 'presents the first question...' with no meaningful length cost.

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 annotations, no output schema, and no parameter schema details, the description is nearly all the agent has. It doesn't explain what 'start' returns, how it connects to checker_answer, or whether the tool requires prior state. For a flow-starting tool in a sibling group, this is under-specified.

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 the description needs to explain. The absence of parameters is already fully visible in the schema, making this dimension minimally demanding; a baseline of 4 is appropriate for a no-parameter 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 identifies the tool as the first question of a named decision guide, which gives the agent some sense of a specific resource. However, it doesn't state what action the tool actually performs (does it present the question, initialize a session, or start a flow?), so it's still somewhat vague about its function relative to 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?

There is no guidance about when to call this tool versus checker_answer, checker_tree, or the enquiry tools. The sibling list suggests this is part of a guided flow, but the description doesn't say that calling it first is required or what state it puts the conversation into.

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 burden. It reveals the tool's output scope: the entire tree with all questions, options, and verdicts. It does not explicitly confirm side-effect-free behavior, but for a parameterless content-providing tool this is a reasonable implication.

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 sentence and conveys the essential scope without padding. The phrasing is slightly awkward and somewhat redundant with the title, but it remains compact and readable.

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 tool with no output schema and no annotations, the description provides enough context: the whole decision tree is returned for end-to-end reasoning. It could mention the format or size, but the omission is acceptable given the tool's simplicity.

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?

There are zero parameters and the input schema is empty, so no parameter documentation is needed. The baseline of 4 applies because the description cannot meaningfully add parameter semantics where 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 clearly identifies the resource as the complete decision tree for the 'Find the fund that fits your club' guide, naming its contents: every question, option, and verdict. It is distinguishable from sibling tools like checker_start or checker_answer, which likely handle individual steps, though it never states 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?

The phrase 'for reasoning end to end' implies the tool is for getting the full tree at once rather than stepping through it. However, it does not explicitly state when to prefer this over checker_answer or checker_start, nor any exclusions or prerequisites.

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 behavioral disclosure burden. It does this well by stating that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and by listing exactly what the tool returns: who receives the details, the consent wording, and how confirmation happens. It could be even more explicit that the tool itself has no side effects, but the existing disclosure is strong.

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 three sentences with no wasted words. 'Read first' is an effective front-loaded call to action, and each sentence earns its place by covering purpose, exclusions, and return contents.

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 is largely complete: it explains what the tool does, what it does not do, and what information it returns. The only minor gap is not explicitly stating that invoking this tool has no side effects, but the framing as a description makes that reasonably clear.

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 is empty, so the baseline is 4. The description adds meaningful context about the tool's purpose and return value, which is more than necessary for a parameterless informational 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 states the tool's role: it 'states plainly what submit_enquiry does' on Club Grants, which is a specific informational purpose tied to a named resource. It also distinguishes itself from the sibling submit_enquiry by describing rather than performing the action, though it does not position itself against 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?

'Read first' gives a clear contextual cue that this tool should be consulted before using submit_enquiry, and the description clarifies that it is not a submission or purchase. However, it does not explicitly state when not to use it or name alternative tools, so guidance is implied rather than fully specified.

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 clearly indicates this is an inspection/listing tool and describes the data it provides, but it does not explicitly state that it is read-only, side-effect-free, or what happens if no enquiry context exists. This is a moderate gap for an unannotated tool.

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 dense, front-loaded sentence provides the full output contract and the integration point with submit_enquiry. There is no filler or redundant restatement of the title.

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 introspection tool with no output schema, the description is quite complete: it enumerates all returned attributes and explains how to use them with a sibling tool. The only notable omission is the exact structure of 'allowed options,' but this is a minor gap given the overall clarity.

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. The description does not need to add parameter-level detail. It does add a useful semantic link by saying answers should be keyed by field key when calling 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 states exactly what the tool exposes—every field of the Club Grants enquiry—and lists the attributes included: key, label, type, required, help text, and allowed options. It also distinguishes itself from submit_enquiry by explaining that the field keys are used to pass answers. However, the operation is implicitly 'list/return' rather than stated with a strong 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?

The final sentence gives clear usage context: agents should pass answers to submit_enquiry keyed by field key, implying this tool should be consulted before submitting. It does not explicitly mention when not to use it or compare it to siblings like enquiry_describe or checker_*.

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 richly: it is a two-step call, step 1 only validates and returns a summary/consent line/token, submission only happens on step 2, the person must click an email link before any provider sees it, and at most three advisers receive details. This is exactly the behavioral context an agent needs for a mutating, consent-gated tool.

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 key disambiguation ('NOT a purchase') and organized as Step 1/Step 2, so every clause does work. It is long and repeats the consent text verbatim from the schema, but the length is justified by the two-step protocol and consent semantics.

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 3-param nested-object tool with no output schema and no annotations, the description supplies what is returned in step 1, what the token is for, and the full downstream email/consent flow. Nothing an agent needs to call this 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?

Schema coverage is 100%, so the baseline is 3, but the description adds sequencing meaning the schema cannot: 'answers' must be keyed by enquiry_fields keys and 'confirmation' is the token returned by step 1 after approval. Consent is fully spelled out (though largely duplicated in 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?

States a specific verb+resource (submits an enquiry to Club Grants) and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote'. It also ties itself to the sibling enquiry_fields by referencing 'field key from enquiry_fields', so an agent can slot it into 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?

Gives explicit sequencing: Step 1 with answers + consent=true, Step 2 only if the person agrees, with the token. It names the precondition (answers keyed by field key from enquiry_fields) and the gating condition for the second 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.