site

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 provided, the description carries the full burden and does so: it discloses that step 1 validates and returns a summary, consent line and token; that the enquiry is only submitted at step 2; and critically that no provider sees the data until the person clicks an emailed confirmation link. It also spells out the downstream data flow (contact details to up to three firms chosen by the checker, email notice per firm, ability to stop further sharing).

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 purpose and the two steps in order, and most sentences carry operational weight. The only cost is duplication: the full consent sentence is reproduced verbatim both here and in the schema's consent description, which is redundant bulk.

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?

There is no output schema, and the description compensates by describing what step 1 returns (summary, consent line, confirmation token) and what happens after step 2 (email with a link the person must click). Given a 3-parameter, nested-object tool with two distinct call modes, an agent has everything needed to invoke 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?

Schema coverage is 100%, so the baseline would be 3, but the description goes well beyond it by tying 'answers' to field keys from enquiry_fields, defining the exact meaning of consent with the full quoted agreement text, and explaining the confirmation token's timing (only after the summary is approved). That flow-level semantics is not derivable from the schema alone.

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 and resource ('Submits an enquiry to Bin Rules Checker') and immediately scopes what it is NOT ('NOT a purchase, NOT a guaranteed quote'), which is the most likely confusion point for an agent scanning this tool family. It also carefully enumerates the two-step protocol so the agent knows exactly what the call accomplishes at each invocation.

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 ordered procedure: Step 1 with answers + consent=true, present the summary and consent line to the person, then Step 2 only if the person agrees, with the same answers plus the confirmation token. The precondition for the second call ('only if the person agrees') and the dependency on enquiry_fields for field keys leave nothing to inference.

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