List NSFW AI

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

With no annotations present, the description carries the full burden, and it does disclose a useful access caveat: the submit link and contact address are only visible on the place's page for signed-in visitors, implying this tool may not return them. It also enumerates what the record contains, but says nothing about auth requirements for calling the tool itself or rate limits.

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, no filler, and the core purpose (one place's full terms) is front-loaded before the returned-field list and the access caveat.

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 enumerating the returned fields (verdict, price text, link, review, submit method, notes, checked date, terms paragraph) is genuinely necessary and done well. The signed-in-visitor caveat covers the main behavioral gap; only tool-level auth or error behavior is unaddressed.

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 'place' parameter is documented as accepting a slug or domain. The description repeats the slug/domain concept without adding syntax, format, or fallback behavior beyond what the schema already provides, so baseline 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?

States a specific verb and resource ('The full terms of one place') and specifies the lookup key ('by its slug or domain'), then enumerates the fields returned. It is clearly a single-place detail fetch, though it does not explicitly distinguish itself from the related sibling where_is_app_listed.

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 or comparison to alternatives like search_places or listing_costs is given. The reader can infer that this is the detail lookup for a single place, but nothing states when to prefer it or what it excludes.

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 safety and behavior disclosure. It does add a behavioral detail—the date of the last check—and the phrasing implies a read-only aggregation, but it does not explicitly state that it has no side effects, nor does it mention authorization or rate-limit considerations. For an apparent query-only tool this is adequate but not thorough.

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 entire description is one compact sentence with no filler or repetition. Every clause adds a distinct piece of information, and the main purpose ('Counts and prices across all places') is front-loaded, making the tool's function immediately obvious.

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 absence of a schema and annotations, the description serves as the full contract and enumerates most expected output dimensions, including a freshness timestamp. It falls just short of specifying the output's structure (e.g., object vs list, currency, or exact breakdown of 'by kind'), which an agent might need for reliable parsing, but it is largely sufficient for a zero-parameter aggregation tool.

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 an empty input schema, so the description is the sole source of meaning beyond the structured schema. It goes well beyond the baseline by detailing what the output covers (counts, pricing modes, price range, median, link types, kind, freshness), adding substantial semantic value where the schema provides none.

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 specific verb ('Counts and prices') and a clear resource ('across all places'), then enumerates the dimensions it covers (free vs paid, price range, median, link types, by kind, last-check date). This distinguishes it from sibling tools like get_place (single place) and search_places (search), which focus on individual records or discovery rather than catalogue-wide aggregation.

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 conveys that this is the tool for an aggregate, catalogue-wide pricing snapshot, which is distinct from the single-record focus of get_place and the discovery focus of search_places. It does not explicitly state when not to use it or name alternatives, but the context makes the appropriate use case clear enough.

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 clearly states what the tool returns (name, domain, kind, verdict, etc.) and that it filters by several criteria, which implies it is a read-only query. However, it does not mention pagination, default limit (though the schema does), sorting, or any potential side effects (though none are expected for a search). The description is transparent about outputs but not about limits or error 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, information-dense sentence that front-loads the purpose and then lists filters and return fields. It contains no filler and each clause adds value. It is concise enough for an agent to parse quickly, though it could be slightly improved with a bulleted list, but as prose it is effective.

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 tool has 7 parameters, no annotations, and no output schema, the description covers the essential aspects: what it returns and how it filters. It lists the return fields completely, which is crucial since there is no output schema. It does not mention default behaviors like the 25-item limit (which is in the schema) or any auth requirements, but for a search operation those are typically not needed. The description is sufficient for an agent to call the tool effectively.

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 86%, and the schema already documents each parameter (enums for kind, link, price, accepts; limit with default and range; query with maxLength). The description adds no additional parameter-level meaning beyond restating the filter categories. Since the schema does the heavy lifting, a baseline 3 is appropriate; the description does not clarify or expand on any 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 states a specific verb ('Find') and a concrete resource ('directories, review sites, list sites, AI directories, launch sites, press and networks'), then lists explicit filters and return fields. It is clear and distinct from siblings like get_place, which suggests a single-place retrieval, whereas this is a broad search. The purpose is unambiguous and not a tautology of the tool name.

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 the tool is for searching directories and similar sites, and the filter list indicates when to use it. However, it does not explicitly state when to use this tool versus alternatives like get_place or where_is_app_listed, nor does it mention any exclusions or prerequisites. The context signals show this is the primary search tool, but the description leaves routing logic to the agent.

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 well: it discloses the result cap (count plus up to 10 places), the freshness of the data (nightly read), and why the list is truncated (free tier). It omits no-match behavior and error handling, but the core behavioral traits are present.

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 front-loaded sentences that lead with the actual result. The pricing pitch ('Starter from $99 a year', 'Pro watches it every night') is partly promotional, but it does justify the 10-result cap, so it earns its place enough to avoid penalty.

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 and no annotations, so the description must describe returns and behavior; it covers returns (count, up to 10 places with link pages) and data freshness well. Only edge-case behavior (no results, invalid domain) is unaddressed.

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 already documents it at 100% coverage with an example (candy.ai). The description adds only the framing that it is an app domain, so it stays at the baseline 3 for high schema coverage.

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: which tracked places link to a given app domain. It is clearly distinct from siblings like get_place and search_places, though it never names them to reinforce the distinction.

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?

Usage is implied by the query itself ('which places link to this domain'), but there is no explicit when-to-use guidance, no mention of when to prefer get_place or search_places, and no prerequisites or exclusions.

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