AIsa Technologies & Whois

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

Annotations already declare destructiveHint=true and openWorldHint=true, so safety is covered. The description adds valuable behavior: independence of items (one failure doesn't cancel others) and per-call billing. These are not derivable from annotations and help the agent set expectations.

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?

Three short sentences with zero filler. The action and limit are front-loaded. The phrase 'tool-router's batch_use' is redundant since it restates the tool name, but it's a minor flaw. Overall it is concise and well-structured.

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 annotations covering destructive behavior and an output schema presumably describing results, the description covers the key operational aspects: concurrency limit, independence, and billing. It doesn't mention error reporting formats, but those likely live in the output schema. It is sufficiently complete for a batch 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?

Schema description coverage is 100%, so the schema fully documents each parameter. The description adds no parameter-specific details. The calls parameter's description already explains the structure and batching context, so the baseline of 3 applies; the description doesn't need to compensate.

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 clear action (execute) and resource (operations) with a concrete limit (up to 20) and concurrency. It doesn't explicitly name the sibling 'use' for single operations, but the distinction is clear enough from the concurrency and limit. The redundancy of 'tool-router's batch_use' is minor.

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 no guidance on when to use this tool versus the sibling 'use' tool. The schema note about 'steps at the same execution_level of a plan go in one batch' is helpful, but it lives in the schema, not the description. The description only implies batching via concurrency but doesn't state when to choose it over the single-operation 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?

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description contributes nothing beyond that - no indication of the shape of the filter reference, whether it includes operators/syntax, or whether results are static. With annotations present the bar is lower, but this adds essentially zero behavioral context.

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 short sentence with no redundancy, which is proportionate. But the opening clause is pure filler ("Here you will find all the necessary information") and the substantive content is buried in a relative clause rather than front-loaded.

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?

An output schema exists, so return values need not be described, and there are no parameters to document. Still, for a reference-lookup tool whose whole value is telling an agent what filters are legal on the sibling endpoints, the description never says what the filters are for or how they connect to the live endpoints, leaving a meaningful gap.

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 per the rubric the baseline is 4. There is nothing for the description to disambiguate, and the empty schema is self-explanatory.

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 (filters usable with Domain Analytics Technologies API endpoints) and the sibling name get_dataforseo_domains_whois_available_filters makes the domain scoping distinguishable. However, the verb is weak filler ("Here you will find all the necessary information") rather than a specific operation like "list available filter fields", so the agent has to infer that this returns a reference list.

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 about when to call this tool, e.g. before composing a request to post_dataforseo_domains_tech_domains_by_technology_live or other filter-accepting endpoints. No alternatives or exclusions are named, and the sibling get_dataforseo_domains_tech_list / _locations / _languages relationship is left unexplained.

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?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds that the response is JSON with a tasks array, but since an output schema exists this is largely redundant; no auth, rate-limit, or caching behavior is disclosed.

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 first sentence restates the title tautologically ('You will receive the list of languages by calling this API') and the second is boilerplate about JSON-encoded responses that duplicates the output schema. Neither sentence is front-loaded with useful actionable information.

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 lookup with an output schema and full annotation coverage, the description is minimally adequate but relies on the title for context. It does not explain what a 'language' entry represents (code, name, format) or any constraints, leaving some gaps an agent might want filled.

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 per the rubric the baseline is 4. There is nothing extra for the description to add or omit in terms of parameter meaning.

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 resource (the list of languages) retrieved from the Domain Analytics Technologies API, which together with the title makes the purpose clear. It does not explicitly differentiate itself from siblings like get_dataforseo_domains_tech_locations, though the resource name is distinct enough to route by.

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 call this tool versus alternatives such as get_dataforseo_domains_tech_locations or get_dataforseo_domains_tech_available_filters. The phrase 'by calling this API' is tautological and offers no selection criteria.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds that the output is structured by technology groups and categories, which is useful context beyond the annotations. It doesn't discuss caching, auth, or result size.

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 efficient sentence with no waste, front-loading what the endpoint provides. It is appropriately sized for a parameterless reference call, though the phrasing is slightly wordy.

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 zero parameters, rich annotations, and an output schema already defining the return shape, the description needs only to establish purpose. It does this adequately, though a note on when to prefer this list over the sibling technology_stats or domains_by_technology endpoints would complete it.

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 nothing to document. The baseline of 4 applies for a parameterless endpoint.

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 specifies a clear verb+resource: it returns the full list of available technologies, structured by groups and categories. This distinguishes it from sibling reference endpoints like tech_languages and tech_locations, though it doesn't explicitly name them.

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 mention of prerequisites, and no routing to alternatives among the many sibling tools. The reference/discovery nature of the endpoint is only implied by the description text.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered structurally. The description adds no behavioral context at all — no mention of caching, rate limits, or that this is a static reference lookup — so it contributes nothing beyond the annotations.

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 short sentence with no wasted clauses, but the phrasing 'by this API call' is filler that conveys no information. Brevity here reflects under-specification rather than disciplined conciseness.

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?

An output schema exists and the tool has no parameters, so the return shape and inputs need no explanation. What is missing is the one thing the description should supply: which of the many similar sibling list endpoints this one is for and when to choose it.

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 nothing for the description to disambiguate and the baseline is 4. The schema itself is empty and fully covered.

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 only 'You will receive the list of locations by this API call,' which restates the tool name and title without adding anything. It names the resource (locations) but offers no distinguishing detail from siblings such as get_dataforseo_domains_tech_languages or get_dataforseo_domains_tech_available_filters.

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, when not to, or which sibling to prefer — despite a crowded sibling set of similar 'reference list' endpoints (languages, available_filters, list). The agent is left to infer usage entirely from the name.

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?

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered structurally. The description adds no behavioral context beyond them — nothing about what the filter list contains, its shape, or how it should be consumed.

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 short sentence, so it is not bloated, but 'Here you will find all the necessary information about' is generic filler that could be trimmed to a direct statement of what is returned.

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?

An output schema exists, so return-value detail is not required of the description, and a zero-parameter discovery tool has a modest burden. Still, the description never says what the filters are used for or how they tie into the sibling POST endpoints, leaving the definition minimally adequate.

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 for the description to document; the 4 baseline applies. Nothing in the schema is left unexplained.

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 the resource (filters for the Domain Analytics Whois API), so an agent can infer it returns the set of query filters. However, it never states the verb ('lists/returns available filter fields') and relies on the tool name to carry the meaning, leaving the purpose only implied rather than stated.

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 call this versus the sibling filter-discovery tools such as get_dataforseo_domains_tech_available_filters, nor any mention of prerequisites or workflow placement. The whois-vs-tech distinction is left entirely to the name.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context: it is free, stops before any spend, and explains how price.model varies (quoted, list, dynamic, composed). It also clarifies that suggested_max_price_usd has headroom. This goes beyond the annotation flags and gives the agent a clear model of what happens.

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 moderately long but well structured: it opens with the core purpose, then explains the price model in a dedicated paragraph. No redundancy or filler. It front-loads the most critical information (contract fields) and then gives necessary detail about price semantics. Slightly dense but not overly verbose.

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 has an output schema, so return values need no description. The description covers the key behavioral aspects (no spend, pricing models, max_price headroom) and clarifies edge cases like routes without a price. For a read-only informational tool, this is complete enough for an agent to use 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?

Schema description coverage is 100%, so parameters are already documented. The description adds some nuance, such as how arguments affect pricing and that required parameters may be needed before a price can be quoted. It also clarifies with_quote's purpose (one round trip, spends nothing). These are useful but not essential given the schema's completeness.

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: returning the full contract of one or more operations, including schemas, read_only, side_effects, price, and known_pitfalls. It clearly distinguishes this from executing operations (use, batch_use) and from discovery (search, list_categories). The verb 'get' and the noun 'details' align with the title, and the first sentence is explicit.

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 used to assess an operation before spending (e.g., 'A quote authenticates like a call but stops before any spend'), and the schema says 'One operation_id from search', hinting at a flow. However, it never explicitly states when to choose this over siblings like use or search, nor does it give exclusions. The guidance is 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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond annotations: the tool is free, requires no key, and can direct users to a category-specific endpoint that lists tools directly rather than through search.

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 moderately detailed but every sentence adds useful information: output scope, cost/auth, sibling differentiation, and endpoint usage. It is slightly longer than strictly necessary but remains well-structured and front-loaded with the core purpose.

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, read-only tool with an output schema and safety annotations, the description is complete. It covers what the tool returns, the free/no-key access model, and provides the category endpoint for specialized use, leaving no essential gap for an agent to 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 has zero parameters, so the baseline is 4. The description includes a <category> placeholder only in the endpoint examples, not as a tool parameter, which is appropriate supplementary guidance rather than a parameter-semantics gap.

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 what the tool does: it presents the AIsa catalogue at a glance, including categories, servers, tool counts, and a dedicated category endpoint. It also distinguishes itself from search by explaining that the endpoint lists tools directly instead of via search.

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 clear usage context: use list_categories for a catalogue overview, and use the provided endpoint when you only need one category. It explicitly contrasts with search ('instead of via search') and notes tool-router has no equivalent, although it does not exhaustively cover all sibling alternatives.

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?

Annotations declare readOnlyHint=false and destructiveHint=true, but the description frames this purely as a retrieval endpoint that 'will provide you with a list'. That directly contradicts the mutation/destructive profile the annotations assert. No auth, rate-limit, or pagination context is added either.

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 core purpose and followed by the alternative usage mode. No waste, though the second sentence could be more directive about when to prefer which mode.

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 a rich nested input schema and an output schema present, the description need not explain return values. It is adequate for a data-query endpoint but leaves the POST body contract (at-least-one of group/category/technology/keyword), filtering, and pagination entirely to the schema.

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 description adds nothing about the body array's fields (group, category, technology, keyword, mode, filters, etc.). Its only real value is the 'category or group for wider stats' hint, which loosely maps to the mutually exclusive selector fields. The nested schema property descriptions carry the parameter burden, so a baseline 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 states a specific verb and resource: it returns a list of popular technologies used alongside the specified technologies, and can widen to categories/groups. An agent can grasp the aggregation concept, though it never names or distinguishes itself from siblings like technology_stats_live or summary_live.

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 second sentence gives implied guidance on granularity ('specify technology categories or groups to obtain wider stats'), which hints at how to shape a query. However, there is no explicit when-to-use-this-vs-alternatives guidance against the many sibling endpoints, and no prerequisites.

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?

Annotations already declare openWorldHint, non-idempotency and destructiveHint, so the safety profile is largely carried elsewhere. The description adds useful return-content context (technology profiles, country, language) but says nothing about billing, rate limits, or the pagination/timeout behavior implied by the offset_token. It adds some value without being rich.

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, with the core purpose front-loaded before the secondary detail about returned data. Appropriately sized for the tool's complexity.

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?

An output schema exists so return values need not be spelled out, and the description does give a reasonable summary of the response. However, with a single required nested 'body' parameter and no usage routing, the definition is only marginally complete for choosing and invoking this search endpoint 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 reported top-level schema coverage is 0% (the 'body' wrapper has no description), but the nested sub-properties carry very detailed descriptions covering mode, limit, offset, filters, keywords, order_by, offset_token and search_terms. The description adds nothing about parameters, so it does not compensate, yet the schema itself 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?

The description states a specific verb+object: it returns domains keyed by the HTML terms on their homepage, plus associated technology/country/language data. That is concrete enough to act on. It falls short of 5 because it never distinguishes itself from close siblings such as post_dataforseo_domains_tech_domains_by_technology_live or for_domain_live, which an agent must choose between.

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 when-to-use or when-not-to-use guidance, no mention of prerequisites or cost, and no pointer to any alternative sibling. The agent is left to infer the selection criterion from the name alone.

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?

The description frames this purely as a data retrieval endpoint ('provides domains', 'you will also get their technology profiles...'), yet the annotations declare readOnlyHint=false and destructiveHint=true. An agent reading the description would conclude this is a safe read, while the annotations assert a destructive, non-idempotent write, which is a direct behavioral contradiction.

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 tight sentences with the core purpose front-loaded and no padding; the only soft spot is the trailing 'and other related data', which is vague filler rather than information an agent can act on.

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?

An output schema exists so return values need not be described, and the description adequately signals the scope of results. However, for a single-body request whose array items have multiple mutually-exclusive required selectors and paging rules, the description is silent on how to construct a valid call, and its read-only framing leaves the annotation conflict unresolved.

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?

Reported schema description coverage is 0% at the top level and the description supplies no parameter information at all. It does not explain the single required 'body' array, the mutually-exclusive selector rule (groups/technologies/technology_paths/keywords/categories), or any of the paging and filtering options, so it adds nothing beyond the embedded property-level schema text.

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 and resource ('provides domains') and a clear scoping criterion ('based on the technology they use'), so an agent can tell what data comes back. It does not, however, distinguish this endpoint from close siblings such as post_dataforseo_domains_tech_domains_by_html_terms_live or post_dataforseo_domains_tech_for_domain_live, and the second sentence is mostly about the response payload rather than the operation.

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, when-not-to-use, or alternative-tool guidance. The description never tells an agent why it would pick 'domains by technology' over the summary, aggregation, or for-domain endpoints in the same family, leaving selection entirely to inference.

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?

Annotations already declare openWorldHint and destructiveHint, but the description adds nothing about the live/real-time nature of the endpoint, rate limits, or what the response contains. It does not contradict the annotations, but it also fails to add behavioral context beyond the one-line purpose statement.

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 filler. It is efficient, though the 'Using this endpoint you will' preamble is boilerplate that could be trimmed.

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 an output schema present, return values need not be explained, but the description still omits any usage context for a POST endpoint family with many near-identical siblings, and provides no parameter guidance despite 0% schema coverage on the body wrapper. Not sufficient for an agent to invoke 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?

Schema description coverage is 0% for the top-level body, and the description only implicitly references a domain ('a particular domain'), adding no syntax, format, or batching semantics for the required array-wrapped target field. The single required parameter is effectively undocumented in the description.

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: 'get a list of technologies used in a particular domain.' An agent can understand what the tool returns. However, it does not distinguish itself from close siblings such as post_dataforseo_domains_tech_domains_by_technology_live or post_dataforseo_domains_tech_summary_live, leaving the 'for_domain' vs 'by_technology' distinction to be inferred from the name alone.

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 contains no when-to-use guidance, no exclusions, and no reference to any alternative sibling tool. With a dense family of tech-related endpoints (aggregation, summary, technology_stats, domains_by_technology), the absence of routing guidance is a real gap.

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?

Annotations declare readOnlyHint=false and destructiveHint=true, but the description presents this purely as a retrieval ('will provide you with the number of domains'), giving the agent no explanation of what the write/destructive aspect means in practice. Nothing is said about the live/synchronous nature, cost, or rate limits. With annotations already sparse and somewhat surprising for a summary query, the description adds no behavioral context.

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 filler, and the core output (domain counts by country/language) leads. It is efficient, though it largely restates the endpoint/title without adding differentiating detail.

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?

An output schema exists, so return values need not be explained, and the input schema is rich. But for a tool with 14+ similar siblings and surprising destructive annotations, the description is thin on selection guidance and behavioral expectations. It is minimally viable rather than 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 description contributes nothing about parameters, but the nested body schema documents each field (mode, groups, filters, categories, technologies, technology_paths, internal_list_limit) in detail, including limits like 'up to 10'. Baseline 3 is appropriate when the schema carries the parameter burden, though the top-level 'body' wrapper itself is undocumented.

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+resource: it returns domain counts by country and language for specified technology names, groups, or categories. That is concrete and understandable. However, it does not distinguish this tool from close siblings such as post_dataforseo_domains_tech_aggregation_live or post_dataforseo_domains_tech_technology_stats_live, which sound nearly identical.

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 when-to-use guidance, no comparison to the many sibling endpoints, and no prerequisite or exclusion stated. The agent is left to infer entirely from the name which of the technology endpoints to pick. Nothing in the text routes the agent here rather than to aggregation_live or domains_by_technology_live.

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?

The description frames this as a retrieval ('will provide you with historical data'), yet the annotations declare destructiveHint=true, readOnlyHint=false, and idempotentHint=false. That is a direct conflict between the described behavior and the structured safety profile, and the description offers no reconciliation (no note that it is a billed live POST call, no rate-limit or cost disclosure).

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 that states the endpoint's output, with no filler or redundancy. It is efficient, though the brevity is partly what leaves usage and behavior unaddressed.

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?

Since an output schema exists, return values need not be described, and for a single-parameter tool the purpose statement is nearly sufficient. But the missing usage routing across many near-identical siblings and the unreconciled destructive annotation leave the definition only minimally adequate.

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 reported as 0% for the top-level body parameter, but the nested fields (technology, date_from, date_to, tag) carry their own descriptions in the schema. The prose implies the 'technology' selector and the country/language breakdown but adds no new syntax, defaults, or date-range semantics 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?

The description gives a concrete verb+resource+scope: it returns historical counts of domains per country and language using a given technology. An agent can distinguish this 'stats' output from siblings like summary_live or domains_by_technology_live. It does not, however, explicitly contrast itself against those 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?

There is no statement of when to use this endpoint versus the numerous sibling tech endpoints (aggregation_live, summary_live, domains_by_technology_live, for_domain_live). No prerequisites, no exclusion conditions, and no guidance on the live-vs-batch tradeoff despite batch_use existing as a sibling.

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?

The description frames the tool purely as a read that 'will provide you with Whois data,' while annotations declare readOnlyHint=false and destructiveHint=true. An agent reading the description would infer a safe lookup, so the description and the structured safety metadata give conflicting signals (it also says nothing about billing/cost, which is the likely real reason for the destructive hint).

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, cleanly front-loaded with the core purpose. The second sentence ('Using this endpoint you will be able to get all these data...') merely restates the first and could be dropped without information loss.

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?

An output schema exists, so return values need not be explained, and the live-endpoint nature is implied by the name. Still missing for a credit-consuming POST endpoint are cost/billing implications, pagination expectations for large result sets, and any hint about the type of query/filters accepted, all of which an agent would need to call it 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?

Schema description coverage is reported as 0% (only the top-level body array is exposed as a parameter), so the description is the only chance to explain inputs, and it instead defers entirely with 'the parameters you specify in the request.' Filters, limit/offset, order_by, and offset_token are never mentioned, so no compensation for the coverage gap occurs.

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 resource (Whois data for domains) and enumerates the enrichment fields returned (backlink stats, ranking and traffic from organic and paid search), so an agent knows what the endpoint yields. It does not, however, distinguish this tool from its many domains_* siblings (e.g., get_dataforseo_domains_whois_available_filters or the tech_* live endpoints), which is the difference between a 4 and 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?

No guidance on when to use this live endpoint versus setup/filter endpoints such as get_dataforseo_domains_whois_available_filters or batch_use, and no prerequisites are stated. The only usage statement is the tautological 'for the domains matching the parameters you specify in the request,' which tells the agent nothing about selection.

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?

The description discloses meaningful behavior beyond annotations: search spans the entire AIsa catalogue, candidates may belong to modules other than the current one, multiple providers for the same metric are surfaced, and no API key is required. This gives the agent a clear picture of scope and output 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 front-loaded with the core purpose and is dense with useful information: scope, no-auth requirement, response shape, and relationship to the catalogue. Each sentence adds operational value, and the structure makes the tool's behavior predictable.

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 complex discovery tool with output schema, the description is unusually complete: it explains the response modalities, candidate fields, direct pass-through to `use`, full-catalogue search behavior, and cross-provider visibility. An agent has enough context to invoke and interpret the tool 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 schema already documents all parameters. The description adds value by explaining that the category parameter is not a hard boundary—search spans the full catalogue—and that queries are plain-language task descriptions, which clarifies how to use the tool effectively.

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 finds AIsa data operations across many categories via a plain-language query. It distinguishes itself from siblings like get_details and use by emphasizing that search covers the full catalogue, not just the pinned category.

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 when to use search: when you need to discover operations across the full catalogue, even those not in the current tools/list. It also implicitly contrasts with get_details by noting that returned candidates already include input_schema, so they can be passed directly to `use` without an extra call.

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?

Annotations already provide readOnly=false, openWorldHint=true, and destructiveHint=true. The description adds valuable behavior beyond that: billing per call, the BatchCallResult response shape, and the error structure with retryable status. It does not spell out side effects, but the destructive flag is already carried by annotations, so the additional context is sufficient.

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?

Three short sentences, each earning its place: purpose, cost, response shape, and routing guidance. Key behavioral facts are front-loaded, and nothing is redundant with the schema or annotations.

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 that an output schema exists and all parameters have descriptions, the tool description is complete enough for correct invocation. It covers cost, return/error contracts, and how routing to this tool differs from calling pinned tools directly, leaving no practical gap.

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 each parameter is already clearly documented: operation_id as returned by search, search_id provenance, arguments matching input_schema, and max_price_usd as a spend guard. The description does not need to add parameter detail, so baseline 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 opens with 'Execute one AIsa operation,' a specific verb+resource statement. The word 'one' distinguishes it from the sibling batch_use, and the closing note distinguishes it from calling pinned tools directly. An agent can tell what this tool is for immediately.

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 explicitly states when to use the tool: 'this is the way to call anything found through search.' It also gives the alternative: 'Pinned tools in tools/list can also be called directly.' This is clear when-versus-alternative guidance with no ambiguity.

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