Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full disclosure burden, and it delivers almost nothing: no statement about rate limits, pagination behavior, request cost, or what a scrape returns. The only cost hint (Advanced costs 2 requests) lives in the schema, not the description.

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 short sentence is technically lean, but the brevity is under-specification rather than economy — it omits the subject of the operation entirely. Nothing is front-loaded because there is nothing substantive to front-load.

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 five-parameter scraping tool with no annotations and no output schema, the description should explain return shape, cost implications, and category-vs-term search fallback. The schema covers parameters well, but the description leaves the operation itself unexplained.

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%, including examples for location, category availability caveats, and the Basic/Advanced trade-off, so the baseline of 3 applies. The description adds no parameter meaning beyond what the schema already states.

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 only says "Select any category you want to scrape," which restates the required search_category parameter rather than naming a specific verb+resource. It never identifies the tool as a Yelp business-search/scrape operation, and with an empty name and title the agent gets no other anchor. This is close to a tautology against the 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?

There is no indication of when to use this tool versus siblings such as business_details, reviews, get_menus_beta, or popular_dishes. Only the schema's mention of category vs term search hints at usage, and that is not framed as guidance.

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 behavioral burden, and it discloses nothing: no rate limits, no cost model, no pagination semantics, no auth requirements. The only behavioral detail (Advanced option costs 2 requests) lives in the schema, not the description.

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 short, but that reflects under-specification rather than disciplined brevity. A single throwaway sentence is not an appropriately sized definition for a 5-parameter 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?

With 5 parameters, two required, no annotations, and no output schema, the definition should carry substantial context. One vague sentence leaves an agent unable to determine what the tool returns or how it differs from the other Yelp-related siblings.

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% and every parameter (limit, offset, location, search_term, business_details_type) is documented in the schema. The description adds no parameter meaning beyond 'just like on Yelp', 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 name '_2' and title '2' convey nothing, and the description only analogizes to yelp.com's search box. It implies a business search of some kind, but never states the verb+resource (e.g. 'search Yelp businesses by term and location') or distinguishes itself from siblings like business_details or reviews.

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 when-to-use guidance, no prerequisites, and no mention of the sibling tools (business_details, reviews, get_menus_beta) that an agent must choose between. The Yelp-analogy line is a stylistic hint, not routing guidance.

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 behavioral burden, and it mostly fails to: nothing about authentication or API key requirements, rate limits, or what the scraped response contains. The only behavioral detail, the 39-id per-request cap, also appears in the schema rather than being added by the description.

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 wording is front-loaded with the action, but the text is cut off mid-clause and contains a dangling escaped quote, which reads as broken rather than concise. A malformed sentence forces the agent to guess at intended meaning instead of extracting it cleanly.

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 scraping tool with no annotations and no output schema, the description should at minimum say what comes back and whether the request is billable or rate-limited; it says neither. The truncation also means whatever guidance the final sentence intended to convey is lost entirely.

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% and both parameters are documented there, including the 39-id limit and an example id list, so the baseline is 3. The description adds only a sample Yelp URL, which duplicates the schema's own example rather than clarifying constraints such as whether business_url and business_ids can be combined.

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 names a verb and resource ('Scrape By Yelp URL') and specifies the two input modes (Yelp URL or business ids), so the core purpose is inferable. However, the text is truncated mid-sentence ('You can get these business urls from the "'), leaving the intent garbled, and it never distinguishes itself from siblings such as business_url_to_id or reviews.

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 hints at a workflow by telling the agent where the inputs come from ('business ids found from /search endpoint'), which implies when to call it. It offers no explicit when-not-to-use guidance and does not explain when to use business_url versus business_ids, the two mutually ambiguous inputs for this same tool.

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 it discloses almost nothing: no read-only confirmation, no statement of what happens for an invalid or unknown URL, and no mention of auth or rate limits. For a lookup tool this is a notable 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?

A single short sentence with zero filler and the key action front-loaded. It is efficient, though bordering on under-specified rather than optimally concise.

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?

There is no output schema, so the description should clarify the return value; 'find biz id' implies an identifier is returned but not its type or failure behavior. For a simple one-parameter lookup tool this is minimally adequate but leaves obvious questions unanswered.

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?

Only one parameter exists and the schema documents it at 100% coverage ('Enter url to find the business id'), so the baseline is 3. The description's 'from url' phrasing adds no format, normalization, or validity detail beyond what the schema already says.

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 (find) and a specific resource (biz id from url), so an agent can tell it performs a URL-to-ID lookup. It does not differentiate itself from siblings, though the sibling list (reviews, get_menus_beta, business_details) is mostly unrelated, so the risk of confusion is low.

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, no prerequisites, and no mention of alternatives or follow-up tools. The use case is inferable from the name and parameter, but the description itself provides no routing information.

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, and it does contribute one genuinely useful constraint: menus on personal websites cannot be collected. It does not disclose the response shape, whether results can be empty, or any auth/rate-limit behavior, leaving meaningful gaps for a read tool with zero annotation support.

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?

A single short sentence with the resource front-loaded and no wasted clauses. It is slightly informal in phrasing ('if present on yelp'), but nothing is padding.

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 single-parameter read tool with no output schema, the description covers the core operation but omits what a returned menu looks like and that an empty result is possible. Adequate but with identifiable gaps given the lack of annotations.

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?

There is exactly one parameter and schema description coverage is 100%, so the schema already documents business_id and its limitation. The description adds no syntax, format, or identifier-source detail beyond what the schema field text provides, matching the baseline for fully covered 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?

States a specific verb+resource ('Get restaurant menus') with a scoping condition ('if present on yelp'), which is enough for an agent to understand the operation. It does not differentiate from siblings such as popular_dishes or business_details, which also appear to return food-related business data, so it stops 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 'if present' hints at conditional availability, but there is no explicit statement of when to call this versus the sibling tools (reviews, popular_dishes, business_details) or what to do when no menu exists. Usage must be inferred entirely.

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, yet it discloses almost nothing: not what happens when dishes are unavailable, whether auth is required, nor the shape of the result beyond 'a list'. 'When available on the website' hints at a conditional failure mode but leaves it unexplained.

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?

A single front-loaded sentence with no redundant padding. The vague trailing qualifier is the only element that does not fully earn 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?

There is no output schema and no annotations, so the description should explain the return format and the 'not available' case, but it does neither. For a data-retrieval tool with a conditional result, this leaves meaningful gaps.

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 single business_id parameter is already documented; the description adds no format, type, or source detail beyond restating the purpose. Baseline 3 applies when the schema does the heavy lifting.

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 (Get) and resource (popular_dish list) scoped to a restaurant, so the core purpose is clear. It does not differentiate itself from siblings such as get_menus_beta or reviews, whose resources overlap conceptually.

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 cue is the vague qualifier 'when available on the website,' which does not tell the agent when to prefer this over get_menus_beta or other siblings. No prerequisites, exclusions, or alternatives are given.

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, yet it only implies a read via 'Get'. It says nothing about pagination being cursor-driven, rate limits, auth requirements, or what the response contains, leaving behavior largely unexplained.

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?

A single short sentence with no filler, and the purpose is front-loaded. It is efficient, though the extreme brevity leaves the definition thin rather than genuinely tight.

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 six parameters, no required fields, no annotations, and no output schema, the description does too little: it never explains which of the two lookup parameters to prefer, that results are paginated via end_cursor/hasNextPage, or what a review record looks like.

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 baseline is 3. The phrase 'by url or id' corresponds to business_url/business_id but adds no syntax or format detail beyond what the schema already documents.

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 ('Get') and resource ('reviews') scoped to a business, and clarifies the two addressing modes ('by url or id'). It is clearly distinguishable from siblings like business_details or get_menus_beta, though it never names 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?

The only usage hint is 'by url or id', which maps loosely to the two addressing parameters. There is no statement of when to use this over business_details or get_menus_beta, and no prerequisites or exclusions are given.

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 supplied, so the description carries the full behavioral burden, and it discloses almost nothing: no auth requirements, no indication of latency or whether the call is cheap versus rate-limited, and no statement of what happens on failure. A status probe is implicitly read-only, but that is inference, not disclosure. The only real signal is the word 'Check', which suggests a non-mutating operation.

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?

A single short sentence with the action front-loaded; nothing is padded or repeated. The informal exclamation mark slightly undercuts the professional register, but the size is appropriate.

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 is the only source of information about this tool, and it omits both the response shape (boolean? status string? latency?) and the meaning of the required 'check' parameter. For a one-parameter probe this is a small surface, but the agent still cannot form a correct call or interpret the result.

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 nominally 100%, but the sole parameter's schema text is the unhelpful 'Example value: true' for a string field named 'check' - it neither explains what to pass nor reconciles the type/example mismatch. The description adds nothing about this parameter, so the agent is left guessing what 'check' means. Nominal coverage does not compensate here because the schema content is not actually informative.

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 concrete verb and resource: 'Check if the api status is live.' An agent can tell this is a health/status probe rather than a data-fetch tool, which is enough to place it apart from siblings like 'business_details' or 'get_menus_beta'. It loses a point for vagueness ('the api' - which API? 'live' - uptime, latency, cached?) and for naming no sibling it excludes.

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 statement of when to call this tool, what precedes it, or what alternative to use instead. It reads as an unconditional call with no context about preconditions or timing. The only implied usage is 'when you want to know if the API is up.'

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