4ai – premium .ai domains for sale

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered and the description only needs to add context. It does add useful data-shape context (price in USD, date, venue, source) in the absence of an output schema, but says nothing about sort order, how 'biggest' is determined, recency of the dataset, or what an empty result looks like. Adequate, with real gaps.

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 short sentences with no filler; the data scope is front-loaded and the use case follows. Nothing is wasted, though the parenthetical field list is the only slightly dense element.

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 output schema, the description usefully enumerates what comes back (price, date, venue, source), and the two optional params are fully covered by the schema. What's missing is minor but real: sort semantics and data recency. Close to complete for a simple read-only lookup.

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 both optional parameters (limit with default 20, max_length excluding the .ai suffix) are fully documented structurally. The description adds no parameter meaning beyond that, though 'biggest' hints at an ordering that the schema does not state. Baseline 3 is appropriate when the schema carries the load.

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 resource: the biggest publicly reported .ai domain sales, with the returned facets (price, date, venue, source) named. The verb is implicit (a read/list) but the scope is unambiguous, and 'publicly reported' plus 'biggest' sharply narrows what data this is versus a general domain lookup. It does not explicitly differentiate itself from estimate_domain_value, which is the closest sibling.

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 clause 'Useful to estimate what a .ai domain is worth' implies a use case but gives no when-to-use/when-not guidance and names no alternative. It actually sits adjacent to estimate_domain_value without saying whether this is evidence for that estimate or a substitute for it, leaving the agent to infer the routing. Implied usage only.

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 and openWorldHint=false, so safety is covered; the description adds real value by disclosing what the comparison yields (length, type, words, seller status, value ranges, verdict). It does not cover handling of invalid or unknown domains, which is a minor 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 sentence with no waste: the action and its constraint come first, followed by the exact attributes returned. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with no output schema, the description adequately previews the return contents so the agent knows what it gets back. Edge-case behavior (nonexistent domains, partial failures) is left unstated but is low risk here.

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 'domains' array is fully documented with an example, so baseline is 3. The description does add the 2-to-5 cardinality constraint that is absent from the schema (no minItems/maxItems), which is genuinely useful but not syntax-level detail.

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 (Compare) and resource (.ai domain names) with the exact cardinality (2 to 5) and enumerates the compared attributes. This clearly separates it from single-domain siblings like get_domain or estimate_domain_value without needing 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?

The '2 to 5' bound and 'side by side' framing tell the agent when this tool applies rather than calling estimate_domain_value repeatedly. It stops short of naming an explicit alternative or stating when not to use it, so no exclusions are provided.

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 annotations already declare this a read-only, closed-world operation, so the bar is lower; the description still adds real context by declaring the call is free and that it returns a sale status with an offer link. It stops short of saying whether the free tier has quotas or whether the valuation is heuristic and therefore non-binding.

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, with the core purpose and the word 'Free' as the first two words, so the important part is front-loaded. The output enumeration in the middle is long, but because the tool has no output schema, each item still earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description must make the return values clear, and it does so. A single required array parameter keeps the surface small, and the batch cap is disclosed. The only real omission is routing guidance relative to the sibling tools, which matters because their responsibilities overlap.

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?

Coverage is 100%, so 3 is the baseline; the description does better than that by disclosing the per-call batch limit of 100 names, which the schema does not encode as a maxItems constraint. The one gap is that it doesn't say whether the input is a bare domain or allows duplicates or a scheme.

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?

It states a specific verb and resource ('Free value estimate for any .ai domain name') and enumerates exactly what the agent gets back: auction, marketplace and brokerage values, ranges, name type, verdict and notes. It does not name or differentiate the sibling tools (get_domain, ai_domain_sales, search_domains), which is the only reason it falls 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?

There is a clear implicit context (you want a valuation, not raw sales data) and a useful batch cap of 'up to 100 names per call', but the description never explicitly cross-references an alternative or a prerequisite, even when the sibling set is assumed to already exist.

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 openWorldHint=false. The description adds real behavior beyond that: results are limited to the 4ai portfolio and it explicitly reports when a domain isn't in it, which shapes how the agent interprets an empty/unhelpful response.

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, followed by the returned-field list and the negative case. No filler or redundancy.

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 output schema, listing the returned fields is the right compensatory move, and the not-found behavior is covered. Minor gaps remain (what 'page' and 'offer link' actually contain), but an agent has enough 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?

Schema coverage is 100% and the schema already says the name is accepted with or without '.ai'. The description's only addition is a concrete example ('p0.ai'), so it neither compensates for nor exceeds what the schema provides — baseline 3.

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: fetch details for one domain in the 4ai portfolio, and enumerates the returned fields (categories, page, offer link, comparable public .ai sales). That scope is clearly distinguishable from siblings like search_domains, list_categories, ai_domain_sales, and estimate_domain_value.

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 single-domain, portfolio-scoped framing, and the not-in-portfolio case is handled. But it never states when to prefer a sibling (e.g., use search_domains to find a domain, or estimate_domain_value for a valuation), so the agent must infer the routing.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that: nothing is transmitted, the user must manually confirm and send, and the $3,000 minimum offer constraint applies. It does not state the return type (presumably a URL string), which is the remaining 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?

Three short sentences, no filler. The key behavioral fact ('Nothing is sent') is front-loaded immediately after the purpose, and the minimum-offer constraint closes it out 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 3-parameter, non-mutating tool with no output schema, the description covers purpose, side-effect profile, and the business constraint. The only missing piece an agent might want is what the call returns (a link string) and whether the domain must exist in the portfolio.

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 documented there including the minimum and the 300-character note limit. The description only restates that the amount and note get 'filled in' and repeats the $3,000 minimum, adding no syntax or format detail beyond the schema, 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 names the concrete artifact produced (a prefilled link to the offer form) and the inputs it embeds (amount, optional note, 4ai domain), so an agent can tell this apart from transactional siblings like ai_domain_sales or search_domains. It is phrased as a noun phrase rather than a verb, but the resource is unambiguous.

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 user opens the link, checks the offer and sends it' — the tool is for drafting an offer, not completing a purchase. However, no sibling is named as an alternative and no explicit when-not guidance is given (e.g., what to do if the user wants to buy at asking price or browse listings first).

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 openWorldHint=false, so the safety profile is covered; the description adds that this is a static informational answer and spells out the topics it covers (fees, minimum offer, transfer time). With no output schema, that content summary is the main behavioral disclosure an agent gets, and it is reasonably specific.

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: the first front-loads the covered topics, the second gives the invocation trigger. No filler, no repetition of the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless, read-only FAQ-style tool with no output schema and annotations already covering safety, listing the covered topics plus a use trigger is everything an agent needs 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 takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the exact resource (steps, payment via Escrow.com, fees, minimum offer, transfer time for buying a .ai domain from 4ai) rather than restating the name. That content enumeration clearly separates it from data-oriented siblings like search_domains or estimate_domain_value.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit trigger: 'Use it when the user asks whether buying is safe or how it works.' That is a clear use condition, though it stops short of naming the alternatives an agent should pick instead for adjacent questions (e.g. pricing or valuation).

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 openWorldHint=false, so safety and locality are covered. The description adds that each entry carries a purpose blurb and a name count, which tells the agent what each row contains, but says nothing about size of the list, stability of the data, or whether counts are live.

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 compact sentence with the resource front-loaded and no filler. It reads as a noun phrase rather than a full sentence, which is slightly less scannable than an explicit verb-led statement.

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 parameters and no output schema, the description bears the burden of explaining the return shape, and it does so only at a high level (purpose text plus name counts). It is sufficient to decide to call it but leaves the agent unsure about list size, ordering, and how the counts relate to search results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the baseline of 4 applies. The description correctly implies no filtering arguments are needed, consistent with the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names the resource precisely ('categories of .ai domains in the 4ai portfolio') and implies a full enumeration, which sets it apart from search_domains and get_domain. It lacks an explicit verb ('list'), so the action is inferred from the tool name rather than stated, keeping it just below 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 'what they are good for' hints that this is orientation/introductory data, but there is no explicit statement of when to call it versus search_domains or ai_domain_sales. No prerequisites, ordering, or when-not-to-use conditions 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description usefully reinforces the closed portfolio scope ('the 4ai.ai portfolio'). 'Every result has an offer link' adds a concrete fact about result content, but ordering, pricing presence, and empty-result behavior remain undisclosed.

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 clauses with zero waste: purpose and scope first, then the filter axes, then a note on result content. Every sentence earns its place and nothing is buried.

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 output schema, the description carries the burden of describing returns, and it only notes that results carry an offer link. For a domain-sale search, price/availability and result ordering are material omissions, though the parameter surface is fully covered by 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?

Schema coverage is 100%, so the schema already documents all five parameters, making 3 the baseline. The description restates the filters and adds a small clarification ('a word in the name') plus the list_categories pointer for the category key, but omits the limit parameter entirely.

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 with scope: searching the 4ai.ai portfolio of premium .ai domain names for sale, with the available filter axes named. It cross-references list_categories but doesn't distinguish itself from ai_domain_sales or get_domain, so sibling differentiation is partial rather than 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?

Usage is implied by the filter list ('filter by a word in the name, a category...'), and it correctly routes the agent to list_categories for category keys. However, there is no statement of when to use this versus ai_domain_sales, get_domain, or estimate_domain_value, and no guidance on what to do with zero results.

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 annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful scope: results are limited to domains that are actually for sale on 4ai. It does not describe the shape of the response or how ranking works, so it adds context but not rich 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?

One sentence that front-loads what the tool returns and then the input, with no filler. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read tool with no output schema, the description covers the input, the purpose, and the market filter. The only gap is that it does not say what the results look like, for example domain names only or names plus prices.

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 both parameters are documented in the schema, including that the domain may be given with or without .ai. The description's 'give any name' adds a little meaning but no syntax or format detail beyond the schema, so the 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: returns the closest .ai domains that are alternatives to a given name. That is clearly distinct from get_domain or estimate_domain_value. It does not explicitly differentiate itself from the nearby suggest_domains or search_domains siblings, so it falls just 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?

Gives concrete triggering conditions: when the name is taken, too expensive, or the user already likes it. This tells the agent when to pick this tool, but it never names an alternative tool or says when not to use it.

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 cover the safety profile (readOnlyHint=true, openWorldHint=false, i.e. a closed-portfolio read). The description adds real value on top: the matching is semantic (plain-language description rather than keywords), results come back ranked with per-domain rationale and an offer link. It does not mention result limits or whether an empty/poor match is possible, which keeps it short of a 5.

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 what the tool returns before the usage trigger. The inline examples earn their space by showing the input granularity and the output shape simultaneously; nothing is redundant with the title or schema.

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?

Read-only annotations plus a description that sketches the return payload (ranked domains, reasons, offer links) make this callable without opening anything else. Missing only edge-case behavior, such as what happens when nothing in the portfolio fits the description.

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 all three parameters are already documented, including the default/max on limit. The description's examples of acceptable input ("telehealth app for mental health", "crypto casino") do clarify the expected granularity of the required description parameter, but say nothing about limit or max_length. 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: describe a project in plain words and receive ranked, best-fitting .ai domains from the 4ai portfolio, each with a fit reason and offer link. That is far more concrete than the title alone. It never names search_domains or similar_domains, so the agent must infer that this is the semantic/description-based variant rather than an explicit differentiation.

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?

"Use this when the user asks for a .ai name for something" gives a clear triggering condition tied to a real user request. There is no when-not guidance and no alternative sibling is named, so an agent facing a keyword-style query has to guess between this and search_domains.

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