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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 of explaining behavior. It only states that this is the first question, but does not disclose what invoking the tool returns, whether it changes any state, or how the question is presented. This is insufficient for a tool that is part of an interactive decision guide.

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 wasted words. It front-loads the key fact that this is the first question of the guide. For a tool with no parameters, this level of conciseness is appropriate.

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 the zero-parameter schema and no output schema, the description is thin on operational context. It does not explain what happens after starting, how the decision guide progresses, or how the sibling tools relate. An agent would need to guess the follow-up actions, making the description incomplete for effective invocation.

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 the baseline is 4. The description reinforces that the tool is a starting point requiring no input, which is consistent with the empty schema. No parameter clarification is needed, and the description adds appropriate minimal 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 identifies the tool as the first question of a decision guide, which indicates it is the entry point. However, it lacks a concrete verb describing what the tool actually does (e.g., 'starts' or 'displays'), making the purpose somewhat vague. It is not a pure tautology, but it mostly paraphrases the title without adding operational clarity.

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 implies the tool should be used first, but it gives no explicit guidance on when to use it versus the sibling tools like checker_answer or checker_tree. There is no mention of the overall flow or that later steps involve answering questions. An agent is left to infer usage from the title and sibling names.

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 burden. It does disclose that the tool returns the entire decision tree rather than a single step, which is useful behavioral information. However, it does not mention output format, whether the tree is static, or any other behavioral details such as size or structure.

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, efficient sentence that immediately states the tool's contents and purpose. Every word contributes meaning, and the phrase 'every question, option and verdict' is specific without being 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?

For a parameterless tool with no output schema, the description adequately communicates what the agent will receive. It could mention the response format or how the tree relates to the sibling step-by-step tools, but the core purpose and content are clear enough for correct invocation.

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 description coverage is 100%, so there is nothing for the description to add. The description correctly focuses on what the tool returns rather than parameter behavior, meeting the baseline 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 clearly identifies the resource as the complete decision tree for the 'Which contract document does this hire need?' guide, listing its contents: questions, options, and verdicts. This distinguishes it from siblings like checker_answer and checker_start, which appear to handle individual steps rather than the whole 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 'for reasoning end to end' provides clear context that this tool is intended for viewing or reasoning through the full decision flow in one call. It implies the tool replaces step-by-step traversal, though it does not explicitly name exclusions or direct the agent to checker_start/checker_answer for interactive use.

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 well: it states that nothing is bought, ordered, or paid, that no quote is guaranteed, and that the process is free. It also discloses what the tool returns: recipient details, consent wording, and confirmation method.

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 and front-loaded with the most important guidance: 'Read first.' Every sentence adds value, covering what the tool explains, what it does not mean, and what content it returns, with no 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?

For a documentation-style tool with no parameters and no output schema, this description is complete. It explains the tool's role, clarifies the non-transactional nature, and states exactly what information the returned description will contain.

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, so there are no parameters to document. The description adds no parameter detail, but none is needed; the baseline of 4 applies for zero-parameter 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 this tool explains what submit_enquiry does on Employment Contract Generator, including starting an enquiry with human providers who quote directly. It also lists what the description returns, making the tool's purpose distinct from the action-oriented submit_enquiry sibling.

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 phrase 'Read first' explicitly signals that this tool should be consulted before using submit_enquiry. It gives clear context for when to use the tool, though it does not explicitly name alternative tools or state when not to use 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, the description carries the burden of explaining behavior. It transparently discloses what the tool returns: every field with its key, label, type, required status, help text, and allowed options. It does not mention side effects or read-only status, but the content description makes its read-only nature clear enough.

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 concise, front-loaded with the tool's purpose, and every sentence earns its place. The first sentence details the return content, and the second provides actionable guidance on connecting to submit_enquiry.

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 simple, parameterless tool, the description is complete: it specifies exactly what data will be returned and how to use it with submit_enquiry. No output schema exists, so the description's enumeration of field attributes adequately covers return values.

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, so the baseline is 4. The description appropriately adds no parameter information since none is needed, and the schema already confirms no inputs.

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 providing every field of the Employment Contract Generator enquiry, listing the specific attributes (key, label, type, required, help text, allowed options). This distinguishes it from siblings like submit_enquiry by framing it as the metadata source for the enquiry's fields.

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 provides clear context for when to use the tool: to discover the fields and their keys before submitting answers. It explicitly guides the agent to use submit_enquiry with answers keyed by field key, though it does not explicitly mention alternatives or when not to use this 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 burden and does so: it discloses validation behavior on step 1, the returned artifacts (summary, consent line, confirmation token), that submission is not final until the person clicks an emailed link, and the exact scope of consent (up to three solicitors, notified per firm, stoppable). No contradictions to reconcile.

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 core distinction (enquiry, not purchase) before the procedural detail, and the two steps are cleanly sequenced. The verbatim repetition of the consent sentence already present in the schema costs it a point, but nothing else is padding.

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 must cover returns — and it names all three (summary, consent line, confirmation token) plus the asynchronous email step. For a nested-object, token-gated, two-call tool, this is complete enough to invoke 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 is 3, but the description adds meaning the schema cannot: it explains where the confirmation token comes from (step 1's response, after approval) and ties consent=true to a two-phase flow rather than a single flag. The consent text itself is duplicated verbatim from the schema, which limits the added value.

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 (submit an enquiry to human providers) and immediately fences off what it is not (not a purchase, not a guaranteed quote). The two-step framing is distinctive enough that an agent can separate 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?

Gives explicit per-step conditions: step 1 with answers+consent=true to validate and obtain a token, step 2 only if the person agrees, with the same answers plus the token. The gate ('only if the person agrees') and the downstream email-click requirement are both spelled out.

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