raptr-names

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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, so the safety profile is covered. The description adds real behavioral detail beyond that: the 20-domain batch limit and the fact that it suggests and checks variations together, plus the availability+price return. No auth or rate-limit notes.

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 zero filler: usage triggers first, then behavior and return. Every clause earns its place and nothing is redundant with the 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?

For a single-param, read-only, open-world tool with no output schema, the description covers when to call it, the batch limit, and what comes back. Only edge behavior (invalid/malformed domain handling, error cases) is unaddressed, which is minor 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 description coverage is 100% and there is a single well-documented parameter, so baseline is 3. The description restates 'full domain names' and the 20 cap (already in the schema) and adding the 'suggest variations' hint leans more toward usage than parameter meaning, so no upgrade is warranted.

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

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

The description states a concrete verb and resource (checks domain names) plus the output (availability and price), so an agent immediately knows what the tool does. It stays distinct from register_domain by implication, but never names the sibling or explicitly contrasts checking versus registering.

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

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

It gives explicit trigger scenarios ('user wants a domain name', 'naming a business or project', 'asks whether a domain is taken'), which is strong usage context. It lacks any when-not guidance or a pointer to register_domain for the follow-up action, so it stops short of full 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=true, so the agent knows this is a safe external read. The description adds useful context about ranking and the default endings (.com, .co, .ai, .io, .app) and the free-.com weighting, but does not disclose latency, rate limits, or how 'GitHub name free' is determined. With annotations carrying the safety profile, this is adequate but not 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?

Front-loads the when-to-use condition, then describes the workflow and output. It is information-dense with little waste, though the long enumeration of use cases (side hustle, shop, podcast, project) is slightly padded.

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-only tool with no output schema, the description covers trigger, input limits, output content, and iteration strategy. It stops short of describing result format or error behavior, but the annotations and schema cover the remaining structured ground.

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

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

Schema description coverage is 100% and both parameters are documented with types and examples, so the schema already does the heavy lifting. The description adds the meaningful constraint that up to 8 names can be checked at once and names the default endings list, which is useful but mostly mirrors the schema's maxItems and examples.

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 (check) and resource (names) and describes the exact output: domain availability with prices plus GitHub name availability, ranked. It distinguishes itself from sibling check_domain by handling up to 8 candidates across multiple endings at once.

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?

Explicit when-to-use trigger (naming a business, startup, product, brand, etc.) and a clear workflow: brainstorm first, check up to 8, then iterate if the best are taken. This tells the agent both when to invoke it and how to sequence it relative to iterating on candidates.

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, and the description reinforces this usefully with 'Nothing is bought by this tool' plus the per-call payment model for agents and the human request path. It goes beyond the annotations by clarifying the informational nature and the cost model, though it doesn't explain what the tool actually returns.

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, front-loaded with the usage trigger, and every clause carries some information. The 'AI agents pay per call; people ask us' construction is compact but slightly cryptic.

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 should clarify what the agent receives back from an 'explanatory' tool, and it doesn't. It covers when to use it and that nothing is purchased, which is the safety-relevant core, but the return behavior remains unspecified for a tool whose entire purpose is to convey information.

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

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

There is a single parameter with 100% schema description coverage ('The domain to register'), so the schema already carries the semantics. The description adds no format, TLD, or availability requirements beyond that, making the baseline 3 correct.

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 that the tool 'explains how to register' a domain rather than performing the registration, which is a specific verb+resource, but it sits awkwardly against the name 'register_domain' and the title 'How to register a domain'. It never explicitly distinguishes itself from the sibling check_domain, so an agent must infer whether this checks, explains, or performs registration.

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 when the user wants to buy an available domain' gives a clear triggering condition, and the trailing note separates agent and human paths. However, no exclusion or explicit hand-off to check_domain (for availability) or request_service is stated, so the routing is left partly implicit.

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 a non-read-only, non-destructive, closed-world write, and the description adds meaningful context beyond that: only the request text is stored, no name or contact data, and user consent must be obtained first. It stops short of describing what happens after the request is recorded or any confirmation 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?

Three short sentences, front-loaded with the usage condition, then the privacy scope, then the consent gate. Nothing is redundant and every sentence carries 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 single-parameter write tool with no output schema, the description covers trigger, consent, and data scope adequately. Only minor gaps remain, such as what the agent should do if the person says no or what happens after the request is recorded.

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 parameter's description already says 'as they agreed to send it.' The description's phrasing mirrors that constraint rather than adding format, length, or fidelity details beyond the schema, 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?

The description states the tool records a request the person agrees to send, which is a specific verb+resource, and implicitly distinguishes it from siblings by framing it as the fallback when none of 'these tools' can fulfill the need. It is clear, though the purpose is conveyed through usage framing rather than a direct statement.

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?

Explicitly gives the trigger condition ('wants something none of these tools can do and says yes to passing the request on') and a prerequisite ('Ask before calling it'). The agent knows exactly when to invoke it and what consent gate must be cleared first.

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