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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden; it does disclose the primary outcome (returning the next question or final verdict). However, it does not mention whether the answer is recorded, whether the call has side effects, or how invalid inputs are handled, leaving some behavioral gaps.

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; it front-loads the inputs and outcome. Every phrase earns its place, making it efficiently scannable for an agent.

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 tool is simple with two parameters, and the description states the core return value. However, without an output schema, it does not clarify the structure of the returned question or final verdict, nor that the returned question should be fed back into this tool, so some inference is required.

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 description coverage is 0%, and the description compensates by clarifying that 'question' is a question id and 'choice' is the chosen option's index. The mismatch between the parameter name 'question' and the phrase 'question id', plus the lack of format details, leaves some ambiguity, but the core semantics are conveyed.

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 uses a specific verb ('return') and identifies the resource (next question or final verdict) along with the required inputs (question id and chosen option). It clearly states the tool's behavior, though it does not explicitly distinguish it from sibling tools like checker_start or checker_tree.

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 conditional 'Given a question id and the chosen option' clearly communicates when this tool should be invoked. It lacks explicit exclusions or named alternatives, but for a linear question-answer flow the usage context is clear enough.

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 explaining behavior. It only states a structural role and does not disclose what happens when called, what the agent receives, whether any state is initialized, or how progression to the next step works.

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 that immediately identifies the tool's position in the guide. There is no filler or redundant wording; every word contributes meaning.

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 entry point, the description is minimally viable, but because there is no output schema and no annotations, it should at least indicate what the agent will receive from calling the tool or what starting the guide entails. It stops just short of being fully actionable.

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 input schema fully defines the invocation contract. The description adds no parameter-specific meaning, but none is needed 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 identifies the tool as the entry point to the 'Which council handles it?' decision guide and specifies that it is the first question, which helps separate it from siblings like checker_answer and checker_tree. It lacks an explicit verb such as 'returns' or 'starts,' but the intent is clear.

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 by the phrase 'first question': an agent can infer this is the starting step of the guide. However, the description gives no explicit guidance about when to choose this over checker_answer, checker_tree, or the enquiry tools, and does not mention exclusions.

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 alone must disclose behavioral traits. It describes the content (every question, option, verdict) but does not state whether the tool is read-only, what the output format is, whether it may be large, or any side effects. The description carries minimal behavioral information beyond the static nature of a decision tree.

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 that front-loads the core content and purpose. It contains no filler and every phrase earns its place, effectively communicating scope and intent in very few words.

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 conveys the main point: the complete decision tree for end-to-end reasoning. However, it does not describe the return structure, the form of questions/options/verdicts, or how the output maps to the guide. This is adequate but leaves some ambiguity for an agent needing to interpret the result.

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 with 100% coverage, so there are no parameter semantics to explain. The baseline for zero-parameter tools is 4, and the description does not need to compensate for missing parameter docs.

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 complete decision tree of the 'Which council handles it?' guide, containing every question, option and verdict. It distinguishes itself from step-oriented siblings like checker_answer and checker_start by emphasizing the full tree. However, it lacks an explicit action verb such as 'returns' or 'provides', relying on the title and phrasing to imply retrieval.

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 intended when the agent needs the full decision tree rather than a single step. However, the description does not explicitly contrast with any sibling tool, nor does it state when not to use it. The usage guidance is present but only implied, not 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 behavioral burden. It discloses that nothing is bought, ordered, or paid for, that no quote is guaranteed, and that it is free. The word 'states' also conveys that this is an informational/read-only tool rather than one that submits anything.

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 front-loaded with 'Read first' and the core purpose, then adds expectation-setting and return details. It is slightly redundant with the title ('not a purchase, not a guaranteed quote' vs 'Nothing is bought, ordered or paid; no quote is guaranteed'), but each sentence still contributes useful context.

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 covers what the tool does, what the user should expect, and what information it returns. It could more explicitly mention alternatives like enquiry_fields or checker tools, but the 'Read first' instruction and submit_enquiry reference make the intended context sufficiently 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 input schema is empty with zero parameters, so the baseline is 4. There are no parameters for the description to explain, and it appropriately focuses on what the tool returns instead.

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 uses a specific verb and resource: it 'states plainly what submit_enquiry does' and spells out the returned content (who receives details, consent wording, confirmation method). This clearly separates it from the sibling submit_enquiry, which actually performs the submission.

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' explicitly positions this as the upfront explanatory tool before an enquiry is submitted. It doesn't exhaustively list when-not-to-use alternatives, but the direct reference to submit_enquiry and the 'Read first' instruction provide clear context for when to call it.

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 burden of behavioral disclosure. It specifies exactly what information the tool exposes and notes that allowed options are included only 'where there are any', which adds useful nuance. It does not state return formatting or error behavior, but for a metadata/read-style tool this is reasonably transparent.

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: the first sentence states exactly what the tool returns, and the second sentence explains the practical next step. No words are wasted, and the structure makes the tool's purpose immediately discoverable.

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 metadata tool, this is nearly complete: it describes the returned fields, the domain, and the relationship to submit_enquiry. It does not explicitly state that the tool is read-only or describe the output envelope, but there is no output schema and the tool's nature makes these omissions minor.

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 schema provides no parameter-level meaning. The description nonetheless orients the agent by explaining the concept of 'field key' and how it should be used with submit_enquiry, which is helpful in a parameter-free context.

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 exposing the field definitions of the Postcode Council enquiry (key, label, type, required, help text, allowed options). It lacks an explicit verb like 'list' or 'get', but 'Every field of the Postcode Council enquiry' makes the resource and scope unambiguous and distinguishes it from submission-oriented siblings like 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 description gives practical guidance: use this tool to discover field keys, then pass answers to submit_enquiry keyed by those field keys. This implies a clear usage context, although it does not explicitly enumerate when not to use this tool or name other sibling alternatives such as enquiry_describe.

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 present, the description carries the full disclosure burden and meets it well. It reveals that Step 1 is validation-only, Step 2 actually submits the enquiry and triggers an email with a link that the person must click before providers see anything, and it quotes the exact required consent text. This goes far beyond what a schema typically conveys.

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 dense but well-structured, using 'Step 1' and 'Step 2' to convey a sequential flow without wasted words. The title reinforces the key caveats ('two steps; not a purchase'), and every sentence in the description earns its place by adding necessary behavioral or sequencing 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?

There is no output schema, so the description appropriately explains what Step 1 returns (summary, consent line, confirmation token) and what happens after Step 2 (submission, email link, provider visibility only after link click). It also ties into enquiry_fields for answer keying, giving an agent the full call sequence needed to use the tool 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 description coverage is 100%, so the schema already documents each parameter at a basic level. The description adds meaningful orchestration context: answers must be keyed by field keys from enquiry_fields, confirmation is the token returned in Step 1 and used only in Step 2, and consent must remain true only after the person approves the summary. This enriches the parameters beyond their schema definitions.

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 opens with a specific verb and resource: 'Submits an enquiry to Postcode Council' and immediately distinguishes the tool from a purchase or guaranteed quote. It then explains the two-step nature, making the tool's purpose and scope unambiguous even without opening the 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?

The description gives explicit when-to-call instructions: Step 1 uses answers and consent=true to validate and get a token; Step 2 is only invoked 'if the person agrees' with the same answers, consent, and token. It also states what the tool is not for ('NOT a purchase, NOT a guaranteed quote'), providing clear usage boundaries.

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