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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 behavioral disclosure burden. It only says this is the first question of a guide, offering no detail about whether the call is read-only, starts a session, or what the response contains. This is a significant gap for an agent deciding to invoke it.

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 clear sentence with no wasted words. It is appropriately sized for a tool with no parameters and is easy to parse.

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?

Although the tool is simple, there is no output schema and no description of what the tool returns or how it fits with the sibling decision-guide tools. An agent is left without information on what to expect after calling it or how to proceed, making the description incomplete.

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 input schema, so there are no parameter semantics to clarify. A baseline of 4 is appropriate; the description need not add parameter information.

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 the Employer change checker decision guide, which is a specific resource and role. It is not a tautology, but it does not differentiate from siblings like checker_answer 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 phrase 'first question' implies this tool is the entry point to the decision guide, but there is no explicit statement about when to use it versus the sibling tools. The usage context is only implied, not clearly 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 behavioral disclosure burden. It accurately conveys that the tool exposes the entire guide structure rather than a single step, but it does not describe output format, size, or whether any stateful interaction is involved. This is acceptable for a simple read-only data dump but not richly 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 a single well-structured sentence that front-loads the key content ('Every question, option and verdict') and ends with the intended use case. No filler or redundant restatement of the title is present.

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 static-tree tool with no output schema, the description sufficiently communicates the content and intent. It could be slightly stronger by clarifying that it is a pure lookup with no dependencies, but nothing essential is missing for an agent to understand what it will receive.

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 has zero parameters, so there is nothing to document. The description adds value by explaining what the returned whole-tree content covers, matching the baseline of 4 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 clearly states that the tool provides every question, option, and verdict in the Employer change checker guide, positioning it as a complete decision tree. It implicitly distinguishes itself from interactive siblings like checker_start and checker_answer, though it lacks an explicit verb such as 'returns' or 'lists'.

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 obtaining the full decision tree in one call. However, it does not explicitly say when to choose this over checker_start, checker_answer, or the enquiry tools, nor does it 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?

With no annotations, the description carries the full behavioral burden. It explicitly discloses that nothing is bought, ordered, or paid, that no quote is guaranteed, and that the action is free. It also states what the tool returns, giving the agent confidence that this is an informational read path.

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, front-loaded with the most important call to action ('Read first'), and every sentence adds useful information. It avoids repetition and fluff while covering purpose, constraints, and return content.

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 explainer tool with no output schema, the description provides the key context an agent needs: what the related action does, what is guaranteed versus not, and what information will be returned. It could slightly expand on prerequisites, but 'Read first' sufficiently signals that no prior state is expected.

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 are no parameter semantics to explain. The description appropriately focuses on purpose and output rather than inventing 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?

The description names a specific resource (submit_enquiry on New Employment Rules) and states the tool's exact role: explaining what that action does. It is clearly distinguished in the title as informational rather than transactional, and the 'Read first' framing makes the intent unmistakable.

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 placement as an introductory/pre-flight tool before using submit_enquiry. It does not explicitly discuss when not to use the checker siblings, so it stops short of full alternative routing.

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 burden, and it clearly discloses what the tool produces: every field's key, label, type, required flag, help text, and allowed options. It also conveys the relationship to submit_enquiry. It does not mention return formatting or edge cases, but for a no-parameter, read-only schema tool the disclosed behavior is adequate.

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 entire definition is two sentences with no filler: the first packs the full scope and content of the returned fields, and the second adds the integration hint with submit_enquiry. Every phrase contributes information.

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 and no annotations, the description covers what is returned, the level of detail, and how to use the result with a sibling tool. Nothing essential 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?

There are zero parameters and schema coverage is 100%, so the baseline is 4. The description adds relevant semantic value by stating that answers passed to submit_enquiry must be keyed by field key, clarifying how the returned keys are meant to be used.

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 specifies the resource and content: 'Every field of the New Employment Rules enquiry' with key, label, type, required, help text, and options. It lacks an explicit verb like 'list' or 'return', but the intent is unmistakable. It distinguishes itself from submit_enquiry by explaining that answers are keyed by field key, though it does not 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 instruction 'Pass answers to submit_enquiry keyed by field key' implies this tool is the source of authoritative field keys before submission, which gives useful context. It does not explicitly state when to choose this over enquiry_describe or other siblings, nor does it give exclusions. The usage guidance is therefore present but indirect.

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 well: it discloses that step 1 only validates and returns a summary/consent line/token, that step 2 causes an email with a click-through link required before any provider sees the data, and that details go to up to three advisers the person can stop. This is meaningful downstream-effect disclosure that cannot be inferred from the schema.

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 purpose and the not-a-purchase caveat, then the numbered flow — easy to scan. Minor waste: the consent sentence is reproduced verbatim from the schema's consent description, an unavoidable but still redundant repetition.

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?

No output schema and no annotations exist, so the description must explain return behavior — and it does, describing what step 1 returns (summary, consent line, confirmation token) and what the person receives after step 2. Nothing an agent needs to invoke this two-phase tool 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; the description adds real value by telling the agent that 'answers' are keyed by field key from enquiry_fields and that 'confirmation' is the token returned by step 1. It doesn't add format detail beyond that, but the cross-tool reference and sequencing of parameters go beyond 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 and resource ('Submits an enquiry to New Employment Rules') and immediately rules out two misreadings ('NOT a purchase, NOT a guaranteed quote'). It also anchors the 'answers' input to the sibling tool enquiry_fields, so an agent can distinguish it from the checker_* and enquiry_* 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 two-step workflow is spelled out with an explicit gating condition ('Step 2: only if the person agrees'), which tells the agent exactly when to call again. It stops short of explicitly contrasting itself with enquiry_describe/enquiry_fields as alternatives, but the sequencing guidance is clear.

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