fetchgate

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

With no annotations provided, the description carries the full behavioral burden. It does disclose useful traits: server-side fetching, the pricing model (free tier, then $0.001/call via x402), and conditional fields ('when present'). However, it omits rate limits, redirect-following behavior, auth requirements, and error semantics for a network-fetch tool — material gaps when annotations offer zero coverage. The pricing disclosure and server-side note earn it above a 2, but the missing fetch-behavior details cap it at 3.

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 information-dense sentences with no filler. The mandatory action is front-loaded ('Fetch a URL server-side'), followed by a compact enumeration of return fields and then the endpoint/pricing note. The field list is long but earns its place as it substitutes for the absent output schema. Only minor trimming of the endpoint reference (already implied by the tool name) would tighten it.

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 tool with no output schema and no annotations, the description does reasonable work: it lists the returned fields, which partially compensates for the missing output schema, and it discloses pricing. But it lacks rate limits, error handling, redirect behavior, and authentication notes, all of which matter for a server-side network fetch. Complete enough for a basic call, yet with clear gaps an agent would benefit from.

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% for the single url parameter, which the schema already describes as 'Absolute http(s) URL to fetch.' This puts the baseline at 3. The description adds marginal value by explaining that the fetch is server-side and by listing what metadata the returned fields will contain, but it does not specify URL constraints beyond what the schema's uri format already conveys. Adequate but not compensating beyond the 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?

The description gives a specific verb ('Fetch') and resource ('a URL server-side') and enumerates the exact structured outputs (title, description, canonical URL, OpenGraph/Twitter fields, favicon, language, timestamps). It is clearly distinct from siblings: read_url presumably returns raw content, while this returns parsed metadata, and it names the underlying endpoint (GET /v1/meta). An agent could select it correctly without opening 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 'Same free tier as read_url' phrase acknowledges a pricing relationship with a sibling but does not explicitly state when to choose get_metadata over read_url (e.g., 'when you need parsed metadata rather than raw HTML'). No exclusions, prerequisites, or alternative-routing conditions are given beyond an implied cost/pricing context. The guidance is present but left 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?

No annotations are provided, so the description carries the full burden. It transparently discloses that the tool only provides information, does not execute payment, and mirrors a pre-payment step. This is strong behavioral disclosure for a read-only (but financially adjacent) 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 compact and front-loaded. Two sentences cover purpose, key details, and exclusions. It includes a technical parenthetical that hints at the exact API flow, which is slightly dense but still earned for an agent.

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 tool with a clear schema and no output schema, the description explains the purpose, the source of the input, the output (price and purchase flow), and what it does NOT do. Nothing essential is missing 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 schema covers 100% of the parameter with a clear description ('Product id, from list_products' `id` field'). The description adds context by referencing list_products, but the schema already does that. Baseline 3 for high coverage 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 clearly states the verb (look up, explain) and resource (product purchase info), and explicitly distinguishes it from payment by saying 'Does not take payment itself'. It also names the source of the id (list_products) and contrasts with the actual endpoint, making it distinct from 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?

The description says to use it when you have a product id from list_products and need to explain the purchase flow. It explicitly notes that it's informational and doesn't take payment, guiding when not to use it as a payment tool. Combined with the sibling context, this is clear 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?

Since no annotations are provided, the description carries the full burden. It discloses that it is free, has no rate limit, and requires no payment to browse, indicating a safe read-only operation. It also reveals the underlying GET endpoint. It does not mention pagination or error handling, but for a simple list it 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 well-formed sentence that packs in the purpose, the data fields, the endpoint, and the cost/rate constraints. No 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?

Given the simplicity of the tool (no parameters, no output schema, no annotations), the description covers the essential information: the action, the returned fields, and the cost. It is complete for an agent to invoke the tool and expect a list of product objects.

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 are no parameters, so meaning is not needed beyond the schema. The description doesn't need to explain anything about parameters. 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 clearly states the action (List) and the resource (Fetchgate's digital-goods catalog), enumerates the expected fields, and distinguishes from sibling tools (get_metadata, get_purchase_info, read_url) which serve different purposes. The verb is specific, and the scope 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?

It provides context that this is for browsing the catalog with no payment required, but does not explicitly compare with sibling tools or state when not to use it. The intent is clear, but differentiation is implied rather than 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?

Since no annotations are provided, the description gets the full burden of behavioral disclosure. It explains what happens after fetching (Markdown conversion, boilerplate removal), quota and billing structure, and URL acceptance restrictions including rejection of private/internal networks. This goes well beyond anything the schema alone conveys.

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 core purpose in the first sentence. Subsequent sentences address endpoint binding, pricing, and URL constraints; every sentence contributes information and there is no redundant 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 one-parameter read operation with no output schema, the description does enough: it explains return value, content cleanup behavior, rate limits, pricing, and input restrictions. The absence of information about errors, redirects, or non-HTML pages is a minor gap rather than a fatal omission.

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 schema covers the url parameter with 100% coverage, but the description adds meaning beyond the schema by restricting the allowed URLs to http/https, requiring absolute URLs, and explicitly rejecting private/internal hosts. That goes beyond the generic 'uri' format from the schema, so it boosts the baseline 3 to a 4.

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 specific verb and resource: 'Fetch a URL server-side and return its main content as clean Markdown.' It also includes concrete details about stripping scripts/styles/nav/ads/boilerplate, which clearly distinguishes it from sibling tools like get_metadata and list_products.

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 operational context: this is for extracting readable content from a URL, with a wrapper around GET /v1/read and clear input constraints. It points to get_purchase_info for the x402 billing flow, but it does not explicitly state when to use an alternative like get_metadata instead of this tool.

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