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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 must carry the full behavioral burden. It only states that this is the first question in a guide, without disclosing whether calling it mutates state, advances the guide, requires prior context, or returns a question payload. An agent cannot predict the tool's side effects or output.

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 filler or redundancy. It is appropriately sized for a zero-parameter entry-point tool, though it could use slightly more behavioral detail without becoming verbose.

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 there is no output schema and no annotations, the description is incomplete: it does not say what the agent will receive after calling the tool, how to proceed after the first question, or what the decision guide flow looks like. This is minimally viable but lacks enough context for confident invocation and follow-up.

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 takes zero parameters and the schema is empty, so there are no parameter semantics for the description to clarify. The baseline of 4 applies because no parameter information is needed beyond what the empty schema already communicates.

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 the Bin rules checker decision guide, which distinguishes it from the sibling answer/tree tools by position. However, it lacks an explicit verb describing what actually happens when invoked—whether it starts the guide, displays a question, or returns some data—so purpose is only vaguely stated.

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 of the Bin rules checker decision guide' implies this tool is the intended entry point for that workflow. It does not name alternatives or explain when to prefer checker_answer or checker_tree, so the guidance is implicit 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?

With no annotations, the description carries the full burden of behavioral disclosure. It describes the content (questions, options, verdicts) but does not state what happens when called, the output format, size, side effects, or whether it is a read-only operation, leaving behavior to inference.

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 wasted words, and it front-loads the content scope. However, it sacrifices actionable specificity for brevity, so it is concise without being exemplary.

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-parameter tool with no annotations and no output schema, the description is the only source of context. It fails to explain the output format, the relationship to sibling tools, or practical usage, making it insufficient for an agent to invoke it correctly 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?

The input schema declares zero parameters, so the baseline is 4. The description adds no parameter-level details, but none are needed since the tool takes no input.

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 exposes every question, option, and verdict in the Bin rules checker guide, which clarifies the resource's scope beyond the title's 'whole decision tree'. However, it lacks an explicit action verb like 'returns' or 'lists' and does not differentiate it from siblings such as checker_start 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?

The phrase 'for reasoning end to end' hints at a use case but gives no explicit guidance on when to choose checker_tree over checker_start, checker_answer, or the enquiry_* tools. No alternatives, exclusions, or prerequisites are mentioned.

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 responsibility for disclosing behavior. It clearly states that nothing is bought, ordered, or paid, that no quote is guaranteed, that the service is free, and it enumerates the content returned, including who receives details, consent wording, and confirmation method. This is thorough for an informational 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?

The description is compact and front-loaded with 'Read first', followed by a plain statement of purpose and key clarifications. Every sentence adds meaningful information, and there is minimal redundancy with 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, no-output-schema explanatory tool, the description is complete. It tells the agent why the tool exists, what it explains, what it does not do, and what information it returns. An agent can call this tool appropriately without additional 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 the baseline is 4. The description does not need to explain parameters, and it appropriately focuses on the tool's informational purpose 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 clearly states the tool's role: it 'states plainly what submit_enquiry does' in a specific context, Bin Rules Checker, and explicitly distinguishes it from a purchase or guaranteed quote. This makes its purpose distinct from siblings like submit_enquiry, checker_start, and 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?

The opening 'Read first' gives explicit guidance to consult this description before using submit_enquiry. It does not name alternatives or explicitly say when NOT to use it, but the usage context is clear for a no-input explanatory 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, the description carries the full transparency burden. It discloses what the tool provides and the content of that output, including the allowed options where present. It implies a read-only metadata lookup with no side effects, though it does not explicitly state that it is non-mutating.

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. The first sentence front-loads the exact contents of the returned field metadata, and the second sentence gives a concrete next-step instruction for using the output.

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 fully explains what data will be returned and how to use it with submit_enquiry. An agent has enough information to call the tool and correctly apply its results.

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 description coverage is 100%, so there are no parameter semantics the description needs to add. The baseline of 4 applies because there is nothing further required.

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 Bin Rules Checker enquiry—and enumerates what is exposed (key, label, type, required, help text, allowed options). It lacks an explicit verb like 'list' or 'get' and does not directly distinguish itself from enquiry_describe, so it is clear but not fully differentiated from 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 description gives direct practical usage context: it tells the agent to pass answers to submit_enquiry keyed by field key, implying this tool should be consulted to learn the fields before submitting. It does not explicitly state when not to use it or how it differs from similar enquiry tools.

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 it does so thoroughly. It discloses the two-step nature, validation, consent requirement, email link behavior, that providers only see the enquiry after the link is clicked, and the exact consent wording.

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 longer than average but every sentence earns its place. It front-loads the critical 'NOT a purchase, NOT a guaranteed quote' message, then structures the two steps in a logical, readable sequence 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?

Despite having no output schema, the description fully explains what step 1 returns, what step 2 requires, and what the user will experience after submission. It also covers the consent condition and the provider visibility condition, making the tool safe and unambiguous for an agent to invoke.

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 valuable semantics beyond the schema: it explains that answers are keyed by field key from enquiry_fields, that consent has a precise legal meaning, and that the confirmation token comes from step 1. This is clear, actionable parameter guidance.

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'), a resource ('Bin Rules Checker'), and the human enquiry context. It explicitly distinguishes itself from a purchase and a guaranteed quote, and points to enquiry_fields for the answer keys, making its purpose unmistakable 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?

Provides explicit step-by-step usage conditions: step 1 validation, showing the summary, getting consent, step 2 confirmation token, and the requirement to only proceed after the person agrees. It does not explicitly name sibling alternatives or say 'use checker_* instead', so it falls just short of a 5.

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