texttostl

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

With no annotations, the description carries the full burden. It transparently indicates a read-only, informational operation via the verb 'describes' and notes that it is 'Free' (no cost). It does not mention side effects, which are unlikely for an informational tool, so this is adequate.

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, concise sentence that fully conveys the tool's purpose without unnecessary words. It front-loads the key information ('Free') and then defines the scope.

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

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

Given the simplicity of the tool (no parameters, no output schema), the description is complete. It tells the agent what the tool does and what it returns (a description of paid tools and pricing), which is sufficient for invocation.

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 per instructions is 4. The description adds no parameter-specific information, but none is needed.

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's function: 'describes this server's paid tools and pricing.' It uses a specific verb ('describes') and resource ('this server's paid tools and pricing'), making it distinct from siblings like generate_stl or web_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 tool's context is clear: it provides information about paid tools and pricing. There are no explicit exclusions or alternatives mentioned, but the purpose implies when to use it (when such information is needed). The 'Free:' prefix adds context about cost but does not explicitly contrast with 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?

With no annotations, the description carries the full burden. It discloses cost ($0.15 USDC on Base) and return format (base64 resource + JSON metadata), which is valuable. However, it doesn't mention prerequisites (e.g., payment setup), error behavior, or potential side effects, leaving gaps for a paid generation tool.

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 three short, focused sentences: what it does, what it costs, and what it returns. Every sentence provides essential information with no redundancy or filler.

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 tool with 9 parameters, no output schema, and no annotations, the description is too sparse. It covers the core purpose and output but lacks details on parameter usage, unit constraints, error handling, and payment prerequisites, which are critical for an AI agent to invoke 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 only 11% (only 'prompt' has a description), so the description must compensate for the other 8 parameters. It does not explain widthMm, heightMm, modelMode, includeBase, etc., and the mention of 'stamp' contradicts the enum which only includes 'cookie-cutter' and 'jewelry'. This is misleading and lacks necessary parameter context.

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 generates a 3D-printable STL from a text prompt, naming specific output categories (cookie cutter, stamp, jewelry). This specific verb+resource combination distinguishes it from the unrelated sibling tools (about, web_search, web_search_read).

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 context: use when you need a 3D-printable STL generated from a text prompt, and it mentions cost and output format. It doesn't explicitly state exclusions or alternatives, but the sibling tools are clearly unrelated, so the usage context is sufficient.

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. It discloses a cost of $0.01 and specifies the return format (title, url, snippet, engine), which adds transparency. However, it omits details like rate limits, error behavior, or pagination, so it is only partially 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?

The description is a single, efficient sentence that front-loads the primary purpose and includes useful details about cost and output. It is appropriately sized, though it could add parameter context without becoming 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?

Given the tool is simple, the description covers the purpose and output but lacks essential context about parameters and usage. The absence of an output schema means the return format is described, but input semantics are entirely missing, making it incomplete for effective tool invocation.

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%, and the description does not mention either parameter (query or limit). The description solely focuses on output, providing no semantic guidance for the input parameters beyond what the raw schema already shows (type/default). This is a significant 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 it performs web searches across multiple named engines (Google, Bing, DuckDuckGo, Brave), giving a specific verb and resource. However, it does not explicitly differentiate from the sibling tool web_search_read, so it misses the full distinction for 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 no guidance on when to use this tool versus alternatives like web_search_read. It mentions the cost, which implies it should be used judiciously, but no explicit when-to-use or when-not-to-use scenarios 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?

With no annotations provided, the description carries the transparency burden. It discloses the cost ($0.02 USDC, Base) and the return JSON shape, which are useful behavioral details. However, it does not mention potential failures, rate limits, or behavior when pages cannot be fetched, leaving some 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?

The description is two concise sentences, front-loads the core function, and provides essential cost and output details without unnecessary filler. 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?

The tool is simple (2 params, no output schema), and the description provides the return format and cost. However, it omits the semantics of the 'pages' parameter and does not explicitly guide when to use this tool versus web_search, making it slightly incomplete for fully informed use.

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%, so the description must compensate but does not. The 'query' parameter is obvious from 'Web search', but 'pages' is not explicitly explained; the phrase 'per page' only hints at its meaning. The schema's default/min/max for pages are not reflected 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?

The description uses a specific verb phrase: 'Web search plus the full plain-text content of the top results in one call.' It clearly distinguishes itself from the sibling web_search tool by adding the full-content retrieval capability, making its purpose 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?

The description implies use when full page text is needed ('full plain-text content of the top results in one call') but does not explicitly state when to use this tool over web_search or mention exclusions. Sibling differentiation is present but not formalized as guidance.

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