x402-web-retrieve
Web Retrieve: Fetch a webpage safely with SSRF protection and extract its clean text content plus title and meta tags.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| maxLen | No | MaxLen to process | |
| target | No | Target to process |
Web Retrieve: Fetch a webpage safely with SSRF protection and extract its clean text content plus title and meta tags.
| Name | Required | Description | Default |
|---|---|---|---|
| maxLen | No | MaxLen to process | |
| target | No | Target to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does mention SSRF protection and the extraction of clean text/title/meta, which is helpful, but it omits important behaviors such as redirect handling, JavaScript rendering, timeout behavior, rate limits, response size limits, or error conditions. The maxLen parameter hints at size control but its behavior is unexplained.
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 compact sentence with no filler, and the core action and output are stated early. The redundant 'Web Retrieve:' prefix is minor waste, but overall the description 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 web-fetching tool with no annotations, no output schema, and vague parameters, this description is incomplete. An agent does not learn what maxLen means, what the return structure looks like, how SSRF protection affects allowed URLs, or when this tool is preferable to the numerous scraping siblings. Key operational details needed for correct invocation are 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 baseline is 3, but the parameter descriptions ('MaxLen to process', 'Target to process') are nearly tautological. The tool description adds no detail about what maxLen represents (e.g., characters, bytes) or what format target must be (URL). It neither compensates for nor worsens the schema, so the baseline score holds.
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 webpage), a safety property (SSRF protection), and a concrete output (clean text, title, meta tags), which clearly distinguishes it from generic fetch tools. However, it does not name or contrast any sibling tools among the many web-scraping siblings, so differentiation is left mostly to the reader.
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 x402-web-scrape, x402-browser-scrape, x402-text-scrape, or x402-fetch. No conditions, exclusions, or selection criteria are provided, so an agent has no basis for choosing this tool over the many similar siblings.
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.