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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 of behavioral disclosure. It does not state whether the tool is read-only, what it returns, whether any side effects exist, or how the output is structured. The description names content but fails to disclose the operation's 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, which is concise, but its structure is awkward and confusing: 'The criteria and any filters of the Ways a contractor can buy search marketing comparison' reads more like a fragment than a clear tool definition. It would benefit from being reworded as an actionable sentence.

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?

With no annotations and no output schema, the description needed to provide adequate context for an agent deciding among several similar sibling tools. It falls short: it gives no indication of return shape, no behavioral detail, and no guidance on when this tool is preferred over compare_options or compare_table. The low parameter count reduces complexity, but the contextual gap remains significant.

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 input schema is empty, so the baseline is 4. The description does not need to explain parameter semantics, and it does not mislead about parameters. No additional parameter information is necessary here.

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 a concrete object (the criteria and any filters) and ties it to a domain context (the 'Ways a contractor can buy search marketing' comparison), but it is a noun phrase with no verb such as 'returns', 'lists', or 'compares.' It is clearer than a tautology but still leaves the tool's actual operation ambiguous.

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?

There is no explicit guidance about when to use compare_criteria versus the sibling tools compare_options, compare_table, or the enquiry_* tools. The only hint is the word 'criteria/filters,' which weakly implies use for criteria introspection, but no alternatives, exclusions, or context conditions are stated.

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 explaining behavior. It does disclose an optional filtering behavior and mentions the fields returned, which is useful. However, it does not clearly state whether the operation is read-only, what happens when no filter is supplied, or how the filter behaves, so the behavioral picture remains incomplete.

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 short and contains no obvious filler, but it is structurally awkward: it starts with a noun phrase instead of an action, packs the domain context into a long parenthetical, and front-loads neither the operation nor the filtering behavior. It is compact without being cleanly organized.

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 that there are no annotations and no output schema, the description needed to provide more complete invocation context. It fails to explain the parameters, offers no routing guidance relative to the sibling comparison tools, and gives only a partial picture of the return data. The tool may be simple, but the available context is not sufficient for reliable selection and use.

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%, so the description must compensate for the two completely undocumented parameters, filterKey and filterValue. The phrase 'optionally filtered by a tag value' is a vague hint, but it never maps the tag value to either parameter and leaves filterKey entirely unexplained. This is insufficient for an agent to know how to call the tool correctly.

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 resource as 'options' in a specific comparison context and lists the returned fields, so an agent can roughly infer that this tool retrieves option data. However, it is a noun phrase rather than an explicit action like 'list' or 'return', and it largely restates the tool name and title without sharply distinguishing it from compare_criteria 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?

The description gives no guidance about when to use this tool instead of sibling tools such as compare_criteria or compare_table. There is no mention of alternatives, exclusions, or the context in which compare_options is the appropriate choice, leaving the agent to infer usage from the name alone.

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 conveys that the tool exposes a read-only table of values and that the result is the full comparison rather than a subset. It does not explicitly describe side effects, output format, or the effect of the optional option parameter, but nothing in the description is misleading.

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 words, and the core idea—full table of option values by criterion—is front-loaded. It is concise, though the phrasing 'Ways a contractor can buy search marketing comparison' is grammatically awkward and slightly detracts from clarity.

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: one optional parameter, no nested objects, and no output schema. The description adequately communicates the table's content but does not mention the optional option parameter, output shape, or how this tool relates to compare_criteria and compare_options. It is minimally viable but leaves some selection context to inference.

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 covers the single parameter fully with 'one option's name, else all,' so the description does not need to explain it further. The description adds no additional parameter context, but the schema is sufficient, keeping this at the baseline of 3.

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 resource (the comparison table) and specifies its contents: each option's value on every criterion. The phrase 'full table' signals that this is an unfiltered cross-tabulation, which helps distinguish it from compare_criteria and compare_options. However, it lacks an explicit action verb such as 'returns' or 'displays,' and the wording is somewhat awkward.

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 about when to use this tool versus compare_criteria or compare_options. The 'full table' phrase weakly implies a complete view, but there is no explicit condition, exclusion, or mention of alternatives, leaving the agent to infer the tool's role among its siblings.

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 disclosure burden and delivers: it states that nothing is 'bought, ordered or paid,' no quote is guaranteed, the process is free, and it returns who receives the details, the consent wording, and the confirmation method. This conveys the non-committal, safe nature of the described flow. It stops short of explicitly declaring that calling enquiry_describe itself has no side effects, but the content is strongly informative.

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?

Three sentences and roughly 60 words, with the core purpose stated in the first sentence. The triadic phrasing 'Nothing is bought, ordered or paid' is slightly emphatic but earns its place by clarifying the non-commercial nature. No filler or irrelevant 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?

For a zero-parameter tool with no output schema and no annotations, the description does convey the return content. But it leaves the agent to infer when to surface this content to the user and how it relates to the sibling enquiry_fields tool, which plausibly returns similar information. A short note on the tool's read-only nature would complete it.

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 with 100% schema coverage, so the baseline for this dimension is 4. The description instead clarifies what the tool returns — recipients, consent wording, and confirmation flow — which is the only semantic content an agent could need. There are no parameters left unexplained.

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's purpose: 'States plainly what submit_enquiry does on Trades SEO Agency,' naming a specific resource and the descriptive action. It clearly connotes a read-and-explain tool rather than a mutating one. However, most text describes submit_enquiry's behavior rather than enquiry_describe's own function, so sibling differentiation is only implicit.

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 directive 'Read first' implies the tool should be invoked before taking action (i.e., before submit_enquiry), which gives meaningful sequencing guidance. But it never states explicit when-to-use versus when-not-to-use conditions, and it does not address sibling alternatives such as enquiry_fields or the comparison 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, the description carries the burden of explaining behavior, and it does so by naming the complete set of returned attributes. It clearly implies a read-only schema discovery operation with no side effects. It does not explicitly state that it makes no changes or require no special authorization, but the content and wording strongly signal a non-mutating lookup.

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 exactly what the tool returns, and the second sentence adds the essential downstream usage tip. Every part earns its place.

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 metadata tool with no output schema, the description fully explains what will be returned and how to use that information with submit_enquiry. Nothing essential is missing for an agent to call this 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?

The input schema is empty with zero parameters, so there are no parameter semantics to document. The baseline for a zero-parameter tool is 4, and the description appropriately avoids inventing unnecessary parameter details.

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 ('every field of the Trades SEO Agency enquiry') and enumerates exactly what is exposed: key, label, type, required status, help text, and allowed options. It is distinguishable from siblings like submit_enquiry and compare_table by focusing purely on the enquiry's field definitions. It lacks an explicit verb such as 'list' or 'get', so the action is only implied, not 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 second sentence provides direct usage context: 'Pass answers to submit_enquiry keyed by field key,' which tells an agent how the output connects to the sibling submission tool. This implies the tool should be used to discover the field structure before submitting. It does not explicitly state when to avoid this tool in favor of siblings like enquiry_describe or compare_criteria, but the keyed-submission guidance is valuable.

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 and does well: it discloses validation on step 1, the returned summary/consent line/token, the double-submit requirement, and the post-submit email-verification gate before any provider sees the data. It also discloses the downstream data-sharing scope (up to three agencies, email notification per firm, ability to stop). What it does not state is error/failure behavior (e.g. what happens on an invalid answer set or an expired token).

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 critical 'NOT a purchase' framing and then cleanly organized as Step 1 / Step 2, so it scans well. The full verbatim consent paragraph is repeated in the schema's consent description, which is some redundancy, but it is arguably load-bearing for a consent-critical 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?

No output schema exists, yet the description explains what each call returns (summary, consent line, confirmation token) and what happens after submission. Combined with 100% schema coverage and the explicit consent semantics for the nested answers object, an agent has everything needed to drive the two-step flow 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 genuine meaning: answers are keyed by field key sourced from enquiry_fields, consent must be true for step 1, and confirmation is only supplied on step 2 after human approval. That sequencing constraint 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 Trades SEO Agency') and immediately scopes it with two negations ('NOT a purchase, NOT a guaranteed quote') that prevent the most likely misclassification. It also names the sibling that supplies the input keys (enquiry_fields), so an agent can route correctly without opening another 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?

Gives an explicit two-step protocol: 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 gating condition ('only if the person agrees') and the required human action (show the summary and consent line) are stated, not implied.

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