x402-text-scrape
Text Scrape: Extract text from URL. ๐ 5 free trial calls per registered wallet
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Text Scrape: Extract text from URL. ๐ 5 free trial calls per registered wallet
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It only adds the free-trial quota; it does not explain output format, authentication requirements, rate limits, failure behavior, or limitations such as JavaScript rendering.
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 brief and front-loaded, with no fluff. The 'Text Scrape:' prefix is mildly redundant with the tool name, but the remaining content is efficient and includes a useful trial-call note.
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 no output schema, no annotations, and an empty parameter schema, the description is too sparse to support correct invocation. It omits the URL parameter mechanism, output expectations, and differentiation from scraping siblings.
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 has zero parameters, yet the description implies a URL input. This mismatch leaves the agent unable to determine how to supply the URL or whether a parameter is missing from the schema. The description names the input concept but does not resolve the invocation ambiguity.
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 verb and resource: extract text from a URL. This is clear and goes beyond the tool name, but it does not distinguish the tool from closely related siblings such as x402-web-scrape, x402-browser-scrape, x402-fetch, or x402-web-retrieve.
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?
No guidance is given about when to use this tool versus the many scraping/fetching siblings. The free-trial note is business information, not usage direction, so an agent has no basis for choosing this tool over alternatives.
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.