x402-fetch
x402-fetch: Fetch a page safely: returns raw HTML, HTTP status and extracted links with SSRF protection. Not a rendered browser view.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| raw | No | Raw to process | |
| input | No | Input to process |
x402-fetch: Fetch a page safely: returns raw HTML, HTTP status and extracted links with SSRF protection. Not a rendered browser view.
| Name | Required | Description | Default |
|---|---|---|---|
| raw | No | Raw to process | |
| input | No | Input to process |
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 request is protected against SSRF, that the output includes raw HTML, status, and links, and that no rendering occurs. This goes beyond the bare 'fetch' name and gives the agent meaningful expectations about safety and output.
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 compact sentences that front-load the core purpose, then state output contents and a key limitation. Every phrase adds useful information, and the structure makes the most important facts immediately visible.
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 description covers return values and the safety/rendering distinction well, but it omits the critical input contract: which param is the URL and whether it is required. With no output schema and no annotations, this gap makes the overall tool definition incomplete for correct 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 description says 'fetch a page,' but the schema parameters are only described as 'Raw to process' and 'Input to process.' Neither the description nor the schema explains which parameter should contain the URL, whether both are needed, or what formats are accepted. Despite 100% nominal schema coverage, the parameter descriptions are generic placeholders, so an agent cannot reliably construct a valid call.
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 action (fetch a page), the resource (a page), and concrete outputs (raw HTML, HTTP status, extracted links). It also distinguishes this tool from rendered-browser tools by explicitly saying 'Not a rendered browser view,' so an agent can tell it apart from siblings like browser-scrape.
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 when-not-to-use signal: this is not a rendered browser view, so it should not be chosen when the agent needs a fully rendered page. However, it does not explicitly name alternatives such as web-scrape, web-retrieve, or brower-scrape, nor does it state exact conditions for preferring this over those.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.