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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 implies a read/comparison action but does not state side effects, return format, or whether the tool fetches, summarizes, or simply presents data. The redundant 'compared comparison' adds no behavioral information.

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 but poorly structured: 'Every' is oddly capitalized mid-sentence and 'compared comparison' is redundant. It is not a cleanly concise statement; the wording confuses rather than efficiently informs.

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, no annotations, and no parameter complexity, this description is the sole documentation, yet it fails to explain what the comparison output contains or how criteria and filters are presented. The malformed grammar increases the chance of misinterpretation, so even a simple tool is not adequately described.

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 is an empty object with full coverage, so there are no parameter semantics for the description to clarify. The 0-parameter baseline applies, and the description does not need to compensate for parameter documentation gaps.

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 subject—'criteria and any filters' of UK school term date sources—and says they are 'compared,' which distinguishes it somewhat from sibling tools like compare_options and compare_table. However, it lacks a clear action verb such as 'returns' or 'displays,' and the phrase 'compared comparison' is tautological and grammatically garbled, weakening 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?

There is no guidance about when to use this tool versus compare_options, compare_table, or the enquiry tools. The description only states what is compared, with no context or exclusions, leaving the agent to infer when this tool is appropriate.

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 of behavioral disclosure. It only reveals that results are optionally filtered by a tag value and does not state whether the operation is read-only, what output shape to expect, or how the comparison is computed. This is under-disclosing, though not contradictory.

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 but poorly structured and hard to parse. The phrase 'compared comparison' is redundant and confusing, and the useful details about fields and filtering are buried behind an awkward lead-in.

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 sibling tools, missing output schema, and sparse parameter documentation, this description is incomplete. It does not explain what the tool returns, how filterKey and filterValue interact, or how compare_options differs from compare_criteria and compare_table. It provides only a fragment of the needed context.

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 two bare string parameters with 0% description coverage. The description weakly explains filterValue by mentioning 'filtered by a tag value', but filterKey is never explained, and there are no formats, allowed values, or defaults. It does not compensate for the schema's silence.

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 grammatically garbled ('The options in the Every source of UK school term dates, compared comparison') and never states a clear verb such as 'list' or 'compare'. It mentions fields (name, best for, tags) and optional tag filtering, so it is not a pure tautology, but an agent cannot confidently determine what action the tool performs.

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 choose compare_options over siblings like compare_criteria, compare_table, or the enquiry_* tools. The only usage hint is the optional tag filter, with no criteria, exclusions, or 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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It only states the content of the output and does not reveal whether the operation is read-only, whether it depends on prior enquiry state, how the table is formatted, or what additional context is needed.

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 but not cleanly written. The phrase 'Every source of UK school term dates, compared' appears to be an unintended insertion and does not contribute useful meaning. The core idea is front-loaded, but the malformed wording harms 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?

For a tool with no annotations and no output schema, the description should more fully explain what the returned table looks like, the meaning of 'option' in practice, and how this tool fits into the overall enquiry workflow. It conveys only the general shape of the output and leaves significant room for misinterpretation.

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 documents the single parameter with high coverage: 'one option's name, else all'. The description's mention of 'Each option's value' aligns with the parameter but does not add meaningful detail beyond the schema, so the baseline score of 3 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 says the tool returns each option's value on every criterion, which identifies the resource as a full comparison table and loosely distinguishes it from siblings like compare_criteria or compare_options. However, it lacks a clear verb and the phrasing is garbled: 'Every source of UK school term dates, compared comparison' reads like a merge artifact and obscures the intended meaning.

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 for when to use compare_table versus compare_criteria or compare_options. The optional 'option' parameter suggests filtering, but the description does not explain when to provide a specific option versus omitting it to get all options.

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 transparency burden and handles it well: it discloses that no purchase or payment occurs, no quote is guaranteed, the service is free, and the response includes recipient details, consent wording, and confirmation method. This is strong behavioral disclosure for a zero-parameter informational 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 three sentences with no wasted words, front-loaded with the 'Read first' instruction, and then delivers the essential facts and return content. 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?

Given there is no output schema, the description sufficiently summarizes what the tool returns: who receives the details, the consent wording, and how confirmation happens. For a simple explanatory tool with no parameters, this is complete enough for an agent to select and invoke 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?

The input schema is empty, so there are no parameters to document; the schema coverage is vacuously 100%. The description appropriately avoids inventing parameter details, and the 0-parameter 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 states a specific purpose: it plainly explains what submit_enquiry does on the Term Dates API, including the free, non-guaranteed nature of the enquiry. It clearly distinguishes itself from siblings like submit_enquiry and the compare_* tools by positioning itself as the 'read first' explanatory tool.

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 usage cue telling the agent to consume this description before submitting an enquiry. The description also clarifies what the outcome is not (not a purchase, not a guaranteed quote), but it does not explicitly contrast with sibling tools such as compare_options or enquiry_fields.

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 available, the description carries the disclosure burden. It makes clear this is a metadata/read operation returning field definitions, and it establishes that the returned keys are the contract for submit_enquiry. It does not explicitly declare read-only behavior, but the zero-parameter, descriptive nature reduces the risk of misuse.

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 tight sentences with no filler. The core purpose is front-loaded, and every clause adds useful information about either the return contents or the downstream usage with 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, zero-parameter metadata lookup with no output schema, the description is sufficiently complete. It enumerates the returned field attributes and explains how the result should be used, giving an agent everything needed to call the tool and interpret the response.

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?

This tool has zero parameters, so there are no parameter semantics to document. The baseline for zero-parameter tools is 4, and the description adds appropriate context about how the returned data should be used, even though it says nothing about parameters.

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 returning every field of the Term Dates API enquiry and enumerates the attributes included: key, label, type, required status, help text, and options. It is distinguishable from submit_enquiry, which consumes answers rather than listing fields, though it lacks an explicit verb like 'list' or 'fetch'.

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 final sentence implies the intended workflow by instructing that answers to submit_enquiry should be keyed by the field key, so this tool is the lookup step before submission. However, it does not explicitly state when to prefer this over enquiry_describe or other sibling tools, leaving usage somewhat implied.

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 fully delivers: it discloses validation, two-step submission, confirmation token handoff, email link requirement before provider visibility, and the exact consent wording. There is no hidden mutation 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 longer than average, but every sentence earns its place for a two-step workflow: core definition first, then step-by-step instructions, then the exact consent text. Nothing is 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?

Even without an output schema, the description tells the agent exactly what each call returns (summary, consent line, confirmation token) and what happens after submission (email with link). For a complex two-step tool with no annotations, 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 beyond the schema: answers are keyed by field key from enquiry_fields, consent is tied to the exact consent text, and confirmation is the token from step 1 required in step 2. This clarifies how the parameters relate to the workflow.

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 opens with a specific verb and resource ('Submits an enquiry to Term Dates API') and immediately distinguishes the tool from purchase or quote tools. It also names the two-step nature and references enquiry_fields, making it clearly distinct from sibling comparison/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?

The description provides explicit when-to-use instructions: Step 1 with answers and consent=true, then Step 2 only if the person agrees, reusing the same answers plus confirmation token. It also states when not to use it ('NOT a purchase, NOT a guaranteed quote') and points to enquiry_fields for valid answer keys.

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