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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 of behavioral disclosure, but it says nothing about side effects, return format, or whether the operation is read-only. It merely names an object without indicating any behavior.

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 short sentence, but it is under-specified and poorly structured as a noun phrase. It is concise in length but fails to convey a clear action, making it unhelpful rather than efficiently written.

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 tool with no parameters and no output schema, the description is the only source of meaning, yet it is too vague to enable correct invocation. An agent cannot determine what operation is performed, what inputs it might accept (though there are none), or what result to expect.

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 shows no properties. Per the rubric, the baseline is 4 for 0 parameters; there is nothing for the description to add about parameter 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 is a noun phrase ('The criteria and any filters...') without a verb, so it fails to state what the tool actually does. The title 'What is compared' adds no clarification. It is vague and does not distinguish from siblings like compare_options or compare_table.

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?

No guidance is provided on when to use this tool versus the sibling tools (compare_options, compare_table, etc.). There is no mention of context, prerequisites, or exclusions, leaving the agent to guess.

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 mentions optional filtering but does not state whether the operation is read-only, whether results are paginated, what the output format is, or any side effects. This is insufficient for a tool with zero annotation coverage.

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, which is concise, but it is somewhat convoluted and lacks front-loading of the core action. The phrasing 'The options in the US field service software for electrical contractors comparison' is awkward and could be clearer, though it doesn't waste 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 tool with no output schema and no annotations, the description is insufficient. It does not clarify what 'options' are, how they relate to sibling tools, the meaning of filtering, or the expected return structure. An agent would likely need to inspect the schema or make assumptions.

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 and the description does not map filterKey and filterValue to the 'tag value' filtering concept. It mentions optional filtering but leaves the exact parameter roles ambiguous, failing to add meaningful value beyond the bare 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?

The description states the tool returns options in a US field service software comparison, listing fields (name, best-for, tags) and optional filtering. However, it doesn't explicitly state the action verb (e.g., 'lists' or 'returns') and lacks differentiation from sibling tools like compare_criteria or compare_table, leaving the specific resource vague.

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?

No guidance is provided on when to use this tool versus siblings. It implies filtering by tag but doesn't mention alternatives, exclusions, or prerequisite context. An agent would not know if this is the right tool for a given comparison task.

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 full responsibility for behavioral disclosure. It does not state whether the tool is read-only, what the output format looks like, or any side effects. It only describes content, not behavior.

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. The key point (full table of values) is front-loaded. It lacks structure but is appropriately brief for the simple tool.

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 tool with one optional parameter and no output schema, the description conveys the core purpose but omits details like the output format or how the optional parameter affects results. The schema covers the parameter, but the description does not elaborate on the return structure, leaving some ambiguity for an agent.

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 provides 100% coverage of the single parameter 'option' with a clear description ('one option's name, else all'). The tool description adds no additional meaning or context about parameter usage, so the baseline of 3 applies.

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 provides 'each option's value on every criterion' for the comparison, clearly identifying the resource (comparison table) and its scope. It hints at being the full table, which loosely distinguishes it from siblings like compare_criteria or compare_options, though it does not name them explicitly.

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?

No guidance is given on when to use this tool versus the sibling comparison tools. The only differentiator is 'the full table,' which is implicit rather than explicit. There are no stated conditions or 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 burden. It discloses that nothing is bought, ordered, or paid, that no quote is guaranteed, and that it is free—all behavioral details about the underlying enquiry process. It also specifies what the tool returns (who receives details, consent wording, confirmation method). This is transparent about both the tool's output and the nature of the action it describes, though it could elaborate on any side effects of the describe tool itself, which are none.

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 exceptionally concise: two sentences with zero filler. The critical guidance 'Read first' is front-loaded, followed by a precise explanation of what the tool returns. Every word earns its place, making it easy for an agent to parse quickly.

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 documentation tool with no output schema, the description fully explains what the tool does and what it returns. It covers the key behavioral aspects (no purchase, no guarantee, free) and the return content (who receives details, consent wording, confirmation). There is nothing an agent needs to know to use this tool correctly that 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?

The tool has zero parameters, so the schema is fully covered. The description appropriately focuses on the tool's purpose and return content rather than parameter details, which are nonexistent. The baseline for zero parameters is 4, and the description meets it by providing the expected return information clearly.

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 function: it describes what submit_enquiry does, specifically that it starts an enquiry with human providers. It distinguishes itself from sibling tools like compare_* and submit_enquiry by being the 'read first' documentation tool. The verb 'states plainly' is specific and the resource (submit_enquiry behavior) is unambiguous.

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' signals it should be used before invoking submit_enquiry, providing clear context for when to use it. It does not explicitly mention when not to use it or name alternatives, but the sibling list (especially submit_enquiry) makes the intended sequence obvious. It gives no explicit exclusions, hence a 4 rather than 5.

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 clearly discloses the returned content categories and the integration point with submit_enquiry, which is more than a minimal description would provide. It does not explicitly state side-effect safety, but for a parameterless metadata-listing tool this is a reasonable gap.

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?

One dense, information-rich sentence with no filler. The field content is front-loaded, and the connection to submit_enquiry is appended naturally.

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 metadata tool with no output schema, the description sufficiently explains what is returned and how it should be used. It could be more explicit about the return shape or sorting, but nothing critical is missing 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, so schema coverage is effectively 100% with an empty schema. The description adds no parameter information because none is needed, matching 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 states exactly what the tool exposes: every field of the enquiry, including key, label, type, required flag, help text, and options. It distinguishes itself from submit_enquiry by telling the agent to use its keys when submitting answers, though it does not explicitly differentiate from the sibling 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 description implies the tool should be used before submitting an enquiry, since it says to pass answers to submit_enquiry keyed by field key. It gives context but no explicit when-not-to-use or comparison with 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, the description carries the full burden and handles it well. It discloses the two-step protocol, validation, the returned summary/consent/token, the email link requirement, and the exact consent wording the person must agree to, giving the agent a clear behavioral model.

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 contributes necessary procedural or consent-related detail. It is front-loaded with the critical 'NOT a purchase' clarification and organized into clear Step 1/Step 2 actions, though the title already conveys some of this 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?

Given the two-step interaction, mandatory consent, and absence of an output schema, the description is remarkably complete. It explains what is returned at each step, the exact condition for proceeding, and the downstream email-link behavior, leaving no critical ambiguity for an agent deciding how to call the tool.

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 already fully describes all parameters, so the baseline is 3. The description adds meaningful context beyond the schema by explaining how answers should be keyed from enquiry_fields, why consent must be true, and how the confirmation token from step 1 is reused in step 2.

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 'Submits an enquiry' to Trades Software Picker, immediately distinguishing it from a purchase or guaranteed quote. It also differentiates itself from the sibling tools by focusing on submission rather than comparison or field listing, and reinforces the two-step nature.

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 explicit sequencing: call first with answers and consent=true, show the summary, then call again with the confirmation token only after agreement. It also points to enquiry_fields for valid answer keys, but it does not explicitly name when to prefer this tool over each sibling or state exclusions beyond 'not a purchase.'

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