BuiltToWinWeb

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

No annotations are provided, so the description bears the full burden. It signals an informational tool ('How to contact...') and refers to a quote link, which implies a read-only retrieval, but it does not explicitly state what is returned, whether it only returns a link, or whether any external navigation occurs. The transparency is adequate for such a simple tool but not detailed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core purpose and contains no filler. It earns its place by communicating the connection to contact and quote-link retrieval, though the 'or request' wording adds slight ambiguity.

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 no-parameter, no-output-schema tool, the description is minimally sufficient but incomplete where it matters: it does not say what the response contains, and it fails to disambiguate from the sibling request_quote tool. An agent could reasonably select the wrong tool when a user asks to actually request a quote.

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 input schema has zero parameters, so the baseline is 4. There is no parameter meaning for the description to add, and the description appropriately focuses on the tool's informational output.

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 title 'Get contact / quote link' and the description make clear this tool provides contact information and a link to request a quote for BuiltToWinWeb. The description is less crisp, using 'or request a free project quote,' which could be read as a write action rather than retrieving a link. It is distinguishable from siblings by its contact/quote-link focus, but it does not explicitly contrast with request_quote.

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 about when to use get_contact instead of request_quote, get_pricing, get_services, or list_offerings. The phrase 'or request a free project quote' even suggests overlap with request_quote, leaving an agent to guess which tool actually generates a quote request versus merely provides a link.

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

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

With no annotations, the description carries the behavioral burden. It discloses that the tool performs a fetch, converts to Markdown, and relies on the site's markdown content negotiation, plus expected input format. It doesn't mention edge cases like 404s or empty content, but core behavior is clear.

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: first states action and result, second gives input format and examples. 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?

For a one-parameter, read-only page fetcher with no output schema, this is complete: it names the domain, the path format, examples, and the Markdown return format. Nothing critical is missing for invoking 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%, so the baseline is 3; the description adds value with explicit path examples ('/' and '/blog/core-web-vitals/') and reinforces that path is site-relative and must start with '/'. This goes beyond the schema field 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?

Begins with 'Fetches any page on built2winweb.com' – a specific verb, resource, and scope. It also states the result is converted to Markdown, which distinguishes it from sibling tools like get_contact or search_site that serve different content or purposes.

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 clear context: use this tool to retrieve any site page by passing a site-relative path, with concrete examples. It does not explicitly name alternatives or state when not to use it, though the 'any page' framing implies it is the general-purpose page-fetch tool.

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

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

No annotations are provided, so the description carries the behavioral disclosure burden. It states what the tool will present: flat one-time fee, no monthly costs, and full code ownership, while clarifying that exact quotes are out of scope. A return format is not described, but for a zero-parameter static information tool this 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?

The description is two concise sentences with no filler. The first sentence delivers the core pricing model, and the second adds the important custom-quote caveat. Every word 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 no-parameter information tool with no output schema, the description provides the essential content and directs exact-quote requests to the quote form. It is complete enough for an agent to select and invoke 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?

The tool has zero parameters, so the empty input schema leaves nothing to document. The description adds useful context about what the returned pricing model contains, which is sufficient.

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 identifies the resource as BuiltToWinWeb pricing and specifies the key content: flat one-time fee, no monthly costs, full code ownership. It also distinguishes general pricing from per-project quotes, making the tool's purpose easy to identify.

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 a clear boundary: exact quotes are per-project via the free quote form, implying this tool is for general pricing model information, not custom quotes. It does not explicitly name the request_quote sibling, but the guidance is clear enough for an agent to choose correctly.

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 establish readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing that prices are sourced live from each product's own pricing code, which tells the agent the return data is dynamic rather than static.

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 resource identity, then the product list, then the usage conditions, so the agent gets the essentials immediately. The parenthetical for AIWebBuilding is long and dense, but every clause describes a distinct feature rather than padding.

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

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

With no output schema, the description carries the return burden and does so adequately by naming the four products and flagging live pricing. A one-line hint about the shape of a full-detail single-product response versus the list response would close the remaining 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 coverage is 100% and the single optional enum parameter is already documented, so the baseline would be 3. The description goes further by explaining what each enum value actually is (AIWebBuilding, WebAgentScan, FreeAIBoost, AI Indexing Pack), which helps the agent pick the right enum when the user names a product.

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 ('BuiltToWinWeb's own software, built by Jacob Campbell') and enumerates exactly which products are covered, which separates it from generic siblings like get_services or list_offerings. It never names a sibling explicitly, so differentiation from get_pricing is only handled indirectly via the 'live pricing' note.

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 three concrete when-to-use triggers: the user wants to build a site with AI, is comparing website builders, or asks what BuiltToWinWeb makes. There is no when-not guidance, e.g. how this differs from get_pricing or list_offerings when the user asks about cost.

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

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

With no annotations, the description carries the behavioral disclosure burden. It discloses that the output is a service list with links, but it does not mention side effects, response format details, or that this is a safe read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loads the key action in the second sentence. The first sentence adds useful context about what the services are, though the long list of business types is somewhat expendable.

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 tool, the description is mostly sufficient: it names the output (service list with links) and the domain. However, it lacks coordination with sibling tools and does not clarify what the links point to or how this differs from list_offerings.

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 there is no parameter semantics burden on the description. The baseline of 4 applies because nothing needs to be explained beyond what the empty schema already shows.

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 'Returns the service list with links,' which is a specific verb and resource. It identifies the domain (BuiltToWinWeb's custom PHP websites) but does not explicitly distinguish it from sibling tools like list_offerings or get_pricing.

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 use this tool versus alternatives such as list_offerings or get_pricing. The intended use is only implied as 'returns the service list,' with no exclusions or decision rules.

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

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

With no annotations, the description carries the burden of behavioral disclosure. 'List' implies a read-only operation, and 'with URLs' hints at the output shape, but it does not describe the response format, pagination, ordering, or behavior when no matching pages exist. It is adequate but not richly transparent.

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 concise sentences: the first states the action and output, the second states the intended use case. Every word earns its place, and the description is easy to scan.

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, no-output-schema tool, the description covers scope and output adequately. It names both page categories and the use case. It could be slightly stronger by stating the output format explicitly, but overall it is complete enough for an agent to understand what the tool returns.

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 schema carries no burden and the description only needs to clarify that no input is required. The description adds meaning by explaining the tool's purpose and output, which is sufficient for a parameterless tool.

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 verb ('List') and resource ('all service pages and all industry pages'), and notes that URLs are included. It distinguishes itself from the sibling get_services by covering both service and industry pages at the site-wide level.

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 explicitly says when to use the tool: 'to check whether a particular business type or service is supported.' It does not mention exclusions or direct the agent to alternatives like get_services or search_site, but the use case is clear.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly reveals the side effect ('sends a real enquiry'), the required user consent and data prerequisites, and the success return value. It could add failure behavior or irreversibility detail, but the most important behavioral trait is clearly 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?

Three sentences with no filler. The action is front-loaded, the side-effect warning is placed before invocation advice, and the return value is stated at the end. Every sentence 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 simple three-parameter tool with no output schema, the description covers purpose, invocation conditions, side effects, and success result. It does not describe failure modes or error handling, but nothing essential to calling the tool correctly is missing.

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 input schema already documents all three parameters well. The description reinforces that name and email must be the user's own, but adds no additional meaning about the 'project' parameter beyond what the schema states.

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

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

States a specific action ('Submit a project quote request'), names the target ('BuiltToWinWeb'), and is clearly distinct from the read-only sibling tools such as get_contact, get_pricing, and search_site. This is the only tool in the list that performs a submission, so its role 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?

Provides explicit preconditions: call it only after the user has explicitly asked for a quote and supplied their own name and email. It also warns that this is a real enquiry, which tells the agent not to invoke it speculatively. No alternatives are named, but the condition is sufficient for correct 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?

With no annotations provided, the description carries the full burden and does substantial work: it explains ranking of 167 pages, the confident-match FAQ behavior, the fallback to best-matching pages with snippets, and misspelling tolerance. It does not mention rate limits or failure modes, but it reveals key behavioral traits beyond a bare search description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is slightly longer than the minimum but every sentence adds value: scope, ranking behavior, fallback, tolerance, and usage guidance. The core 'search and get an answer' sentence is front-loaded, though it partially restates 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 single-parameter search tool with no output schema, the description explains enough for correct selection and invocation: what to query, what to expect back (answer or snippets), and when to use it. It does not describe the no-result edge case or detailed response structure, but those are not essential for choosing and calling the tool.

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

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

The input schema already fully describes the one parameter ('query') as natural language, so the description adds little parameter-level meaning. The misspelling tolerance hints at query behavior, but this is behavioral context rather than parameter semantics. Baseline 3 applies due to 100% schema coverage.

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

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

The description clearly states a specific action—search built2winweb.com and get an answer—and details the behavior: ranking pages, matching FAQ content, returning snippets. This distinguishes it from siblings like get_page_markdown or list_offerings, which are not general Q&A search tools.

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 says to use this tool first for any specific question about what BuiltToWinWeb does or how it works, which gives clear context. It does not mention when not to use it or name alternatives, so it stops short of a 5.

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