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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 or mutating, what it returns, whether it performs an actual comparison, or any side effects or constraints.

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 and not bloated, but it is awkwardly structured and does not front-load a clear action. Its brevity comes at the cost of clarity rather than being efficiently informative.

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 should explain what the tool does and what it returns. Instead it only names the subject matter, leaving an agent unable to determine the tool's behavior or result from the definition alone.

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 takes zero parameters, so there is no parameter semantics to document. Per the baseline for 0 params, a 4 is appropriate; the description does not need to compensate for schema 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 is a noun phrase ('The criteria and any filters...') that does not state a clear action or verb. It identifies a domain and mentions 'accepted rate comparison,' but does not say what compare_criteria actually does or how it differs 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?

There is no guidance on when to use this tool versus compare_options, compare_table, or the enquiry tools. The description provides context about the data involved but no usage conditions, prerequisites, 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?

No annotations are provided, so the description must carry the full behavioral burden. It discloses the returned fields and optional tag filtering, but says nothing about read-only status, permissions, pagination, ordering, or what 'accepted rate comparison' means operationally.

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?

It is a single sentence, so it is compact, but the phrasing 'accepted rate comparison' is awkward and not front-loaded with a clear action. The sentence is concise without being especially clear.

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, no output schema, and undocumented parameters, the description is not complete enough for an agent to call the tool confidently. It should clarify the comparison behavior, filter semantics, and return shape.

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% for two parameters. The description hints that filterValue is a tag value, but does not explain filterKey at all or how the two parameters interact. It adds minimal meaning 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 identifies the resource as 'the options in the Hindi AI training listings' and lists returned fields (name, best for, tags), but the verb is unclear and 'accepted rate comparison' is ambiguous. It does not clearly distinguish this tool from siblings like 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 only usage guidance is that filtering by a tag value is optional. There is no explanation of when to use this tool versus compare_criteria or compare_table, and no prerequisites or exclusions 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, the description carries the full disclosure burden, but it does not state whether the operation is read-only, what permissions are needed, or what the response looks like. The phrase "accepted rate comparison" is undefined and adds ambiguity rather than behavioral clarity.

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, so it is brief, but it is awkwardly structured and contains unclear wording such as "with an accepted rate comparison". It is concise without being well front-loaded or informative.

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 and no nested objects — but there is no output schema, and the description does not adequately explain return values or usage context. Given the absence of annotations and sibling tools, the definition should do more to make the tool callable with confidence.

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%, and the single optional "option" parameter is fully documented in the input schema as "one option's name, else all". The description does not add meaning beyond that, but the baseline of 3 is appropriate when the schema already handles 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 — "Each option's value on every criterion... the full table" — rather than a clear verb+resource statement. It hints at a comparison-table output but does not explicitly distinguish the tool from siblings compare_criteria and compare_options.

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 when-to-use guidance and no mention of the sibling comparison tools. "The full table" weakly implies a complete comparison view, but the agent is left to infer when this tool should be chosen over compare_criteria or compare_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, the description carries the full burden and does real work: it states that nothing is bought or paid, that no quote is guaranteed, that it is free, and what specifically is returned (recipient list, consent wording, confirmation flow). That is meaningful 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?

Front-loads 'Read first', which is good, but the three sentences are partly redundant: 'Nothing is bought, ordered or paid' and 'it is free' restate the same point already carried by the title's 'not a purchase, not a guaranteed quote'. Tightening to two sentences would lose nothing.

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, annotation-free informational tool with no output schema, the description still names the return payload (recipients, consent wording, confirmation). Missing only guidance on when this is redundant versus enquiry_fields, but an agent can call 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 tool takes zero parameters, so the baseline is 4 per the rubric; nothing in the description conflicts with the empty 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 says it plainly states what submit_enquiry does, and enumerates the returned content (recipient of details, consent wording, confirmation method), so an agent knows it is an informational/read tool. It does not distinguish itself from the sibling enquiry_fields, which likely also describes the enquiry, leaving some ambiguity between the two read 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?

'Read first' is an explicit sequencing instruction relative to submit_enquiry, and the description clarifies what this tool is not (a purchase, an order, a guaranteed quote). No explicit exclusion against the other read siblings such as enquiry_fields or compare_criteria, so 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 must carry the full behavioral burden. It discloses the returned attributes (key, label, type, required, help text, options) but does not explicitly state that the operation is read-only, has no side effects, or requires any particular authentication. No contradiction with annotations exists since none are provided.

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?

Two sentences, front-loaded with the return content, and the usage hint is secondary. Every clause adds value, and there is no wasted text.

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 no output schema, the description compensates by listing the field attributes an agent will receive. It does not specify the overall response structure (e.g., an array of objects) or explicitly state that the call is read-only, but for a simple zero-parameter metadata 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 takes zero parameters, so the baseline is 4. The schema is empty with 100% description coverage, and the description's mention of field keys adds useful context for the downstream submit_enquiry call.

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 returns every field of the Hindi AI Trainer Jobs enquiry and enumerates the attributes (key, label, type, required, help text, options). It distinguishes itself from submit_enquiry by explaining the relationship, though it does not explicitly distinguish from enquiry_describe or use a direct verb like 'returns' or 'lists'.

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 sentence 'Pass answers to submit_enquiry keyed by field key' implies this tool is used to discover field keys before submitting, but it does not explicitly state when to use this tool, when not to, or how it differs from siblings like 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 provided, the description carries the full behavioral burden and does so well: it discloses the two-step validation/submission flow, the email verification gate, the exact consent meaning, and the fact that the enquiry is not a purchase or guaranteed quote. It adds important context beyond the schema without contradicting any structured metadata.

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 front-loaded with the core purpose and negative constraints, then organized into clear Step 1 and Step 2 instructions. Despite its length, every sentence contributes necessary workflow or consent information for a two-step submission 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?

Given the two-step consent flow, nested answers object, and absence of an output schema, the description supplies what an agent needs: return behavior for step 1, submission behavior for step 2, consent wording, and the email verification requirement. No critical caller guidance appears to be 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?

Schema description coverage is 100%, so the schema already documents all three parameters, but the description adds procedural meaning: answers are keyed by field key from enquiry_fields, consent must be true only after agreement, and confirmation is the token returned from step 1 after approval. The added context is useful but overlaps substantially with schema parameter descriptions.

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 verb and resource — submitting an enquiry to human providers — and immediately clarifies that it is not a purchase or guaranteed quote. It is clearly distinguishable from sibling tools such as enquiry_fields and the compare_* tools by its submission/consent 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?

It gives explicit, sequential guidance: step 1 validates and returns a summary plus token, and step 2 is only called if the person agrees, using the same answers and the token. It also tells the agent to show the person the summary and consent line, and explains that an email link must be clicked before providers see the enquiry.

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