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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 say what the tool does, what it returns, whether it is a read-only lookup, or how the criteria and filters are presented. The description only names the subject matter.

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 very short and free of filler, but it is structured as a fragment rather than a complete instruction. Missing a verb makes it less useful, and the brevity crosses from concise into under-specified.

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 should state what the caller receives or can expect. 'The criteria and any filters' hints at content but does not explain the return value, format, or behavior, leaving the tool incomplete for an agent to call confidently.

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 properties, so there are no parameters whose semantics need clarification. The description does not need to compensate for missing parameter documentation, and the baseline for a zero-parameter tool is appropriate.

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 essentially a noun phrase that restates the tool's name and title: it says the tool is about 'the criteria' of a comparison, which is what 'compare_criteria' and 'What is compared' already say. It adds domain context ('US HVAC field service software') but no explicit verb or action, so an agent cannot tell whether the tool returns criteria, explains them, or accepts them as input.

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 guidance on when to use this tool versus the siblings such as compare_options, compare_table, or enquiry_fields. The description does not state a condition, context, or exclusion that would help an agent choose this tool instead of an alternative.

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 behavioral disclosure. It reveals that the tool returns options with given fields and supports filtering by a tag value, which is useful behavioral context. However, it does not explain the effect of omitting both parameters, the relationship between filterKey and filterValue, or the response format. Partial disclosure, no side-effect warnings needed for a likely read-only tool.

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 redundancy or extraneous detail. It front-loads the core resource and then states the optional filtering behavior, making it easy to scan and understand. Every word contributes to the 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 simple list tool with two undocumented optional parameters and no output schema, the description leaves critical gaps. It does not clarify how to use filterKey or that filterKey should be set to a specific tag key, nor does it describe the result when no filter is applied. It also fails to relate the tool to its siblings, leaving the agent unsure about boundary cases.

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 no descriptions for filterKey or filterValue, and schema coverage is 0%, so the description must explain the parameters. It only mentions 'filtered by a tag value,' which hints at filterValue but leaves filterKey entirely unexplained and unclear how the two interact. This is insufficient compensation for the missing parameter documentation.

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 specific resource ('options') and details its content fields (name, what it is best for, tags) and the optional tag filter. It clearly differentiates from sibling tools like compare_criteria or compare_table by focusing on the options entity. However, it is phrased as a noun phrase without an explicit verb like 'list' or 'retrieve', so it stops short of a fully explicit action statement.

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 when to use the tool: when you need the list of options in the comparison, optionally filtered by tag. It does not mention alternatives or exclusions, such as when compare_criteria or compare_table would be more appropriate. Usage is inferable but not explicitly 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It says what the table contains but does not explicitly say this is a read-only lookup, what the output format looks like, or how the optional 'option' parameter changes the result. The schema partially covers parameter behavior, but the description itself adds no behavioral context beyond content.

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, tightly worded sentence with no filler. The key phrase 'the full table' is placed at the end after an em dash for emphasis. Every word contributes to defining the tool's scope, earning a 5.

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 one-parameter, no-output-schema, no-annotation tool, the description plus schema parameter documentation provide the essential calling information. It names the domain and the full scope, and sibling tool names offer enough context for differentiation. The only gap is not describing return formatting, which is minor for a table lookup.

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 single parameter 'option' is already fully documented in the schema with 'one option's name, else all,' so schema coverage is 100%. The description's phrase 'each option's value' loosely maps to the parameter but adds no new meaning beyond what the schema already provides. Baseline 3 is appropriate because the schema handles the semantic weight.

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 (US HVAC field service software comparison) and the scope (every option's value on every criterion), calling it 'the full table.' It distinguishes from sibling tools like compare_criteria and compare_options by emphasizing the complete dataset rather than a focused subset. However, it lacks an explicit verb like 'returns' or 'displays,' which keeps it just short of a 5.

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 'the full table' implies this tool is for a comprehensive view, and sibling names like compare_criteria and compare_options suggest narrower alternatives. But the description never explicitly states when to choose this tool over those siblings or when not to use it. Usage guidance is only implied, not 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 full burden and does so thoroughly: it states the operation is free, is not a purchase or payment, and guarantees no quote. It also discloses the return content, including who receives the details, the consent wording, and how the person confirms, leaving the agent with 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 compact and front-loaded, opening with the important instruction 'Read first.' Each sentence adds meaningful information: what the tool does, what it does not do, and what it returns, with no filler.

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 is complete: it tells the agent the tool's purpose, the key exclusions, and the exact return contents. Nothing critical is missing for correct invocation or interpretation.

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 there is no parameter surface for the description to document. With schema coverage at 100% trivially and no params to explain, the baseline of 4 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 clearly states that this tool returns a plain-language explanation of what submit_enquiry does, with the instruction 'Read first.' It distinguishes itself from the actual submission action by clarifying nothing is bought, ordered, or paid, and no quote is guaranteed, but it does not explicitly differentiate itself from the sibling compare/enquiry tools.

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' is an explicit cue that this tool should be consulted before proceeding, and the content frames it as the entry point for understanding submit_enquiry. It gives clear context for when to use it, though it does not explicitly list exclusions or compare against the sibling 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?

No annotations are provided, so the description carries the full burden. It describes the content of the response but does not explicitly disclose that this is a read-only operation, nor does it mention any authentication, rate-limit, or response-format behavior. The instruction to pass values to submit_enquiry implies a non-mutating lookup, but the transparency is not complete.

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 unnecessary words. It front-loads the core 'every field of the enquiry' and then enumerates the attributes, followed by a single practical usage sentence. Every sentence 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?

With no output schema, the description does a good job of specifying what the response contains: keys, labels, types, required flags, help text, and options. It also explains how to use the results. It stops short of describing the exact response format or any error conditions, but for a parameterless introspection tool it is largely complete.

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 coverage is 100%, so the baseline is 4. The description adds useful context by explaining that field keys are used to key answers to submit_enquiry, which clarifies the meaning of the returned key attribute even though no parameters exist.

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 Compare HVAC Software enquiry, including key, label, type, required flag, help text, and allowed options. This is a specific resource with a clear scope, and it is easily distinguished from siblings like compare_criteria or compare_table. The mention of submit_enquiry also anchors its role in the workflow.

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 clear practical guidance: use the returned field keys to key answers when calling submit_enquiry. It does not explicitly name alternative tools or state when not to use this one, but the purpose of inspecting the enquiry fields is self-evident and the workflow hint 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 burden and does so richly: it discloses that step 1 only validates and returns a summary/consent line/token, that nothing is submitted until step 2, that the person must click an emailed link before any provider sees the data, and that details go to up to three suppliers who may contact directly. It also defines what consent means, which is critical for an irreversible data-sharing action.

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 and clearly segmented with 'Step 1:'/'Step 2:' labels, so the reader gets the not-a-purchase caveat and the sequence first. The verbatim repetition of the long consent paragraph (already in the schema) is mild redundancy, but the overall length is justified by the two-step protocol.

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?

Covers everything an agent needs for a 3-param tool with no output schema: it describes the step-1 return values (summary, consent line, token), the step-2 side effect (submission plus verification email), the dependency on enquiry_fields, and the consent semantics. The nested 'answers' object is tied to its external source.

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 real meaning: it pins 'answers' to field keys from enquiry_fields, restricts 'consent' to the agree case, and crucially explains that 'confirmation' is the token returned in step 1 and used only after the person approves the summary. This is more than the schema's field-level docs provide.

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 Compare HVAC Software') and immediately negates likely misreadings ('NOT a purchase, NOT a guaranteed quote'). The two-step framing plus reference to 'enquiry_fields' distinguishes it clearly from siblings like compare_table, enquiry_describe, and enquiry_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?

Explicitly spells out when to call each step: step 1 with answers keyed by field key from enquiry_fields and consent=true; step 2 only 'if the person agrees', with the same answers plus the confirmation token. The gating condition and the alternative sequence are both stated, leaving nothing to inference.

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