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minia2a-mcp

x402-browser-scrape

Browser Scrape: Fetch a public URL and return the full raw HTML page source — for agents that need the complete page, not just extracted text. SSRF-guarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

B3.1/5.0
Behavior2/5

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

Annotations are absent, so the description bears the full burden of behavioral disclosure. It does add useful context — only public URLs are fetchable and the tool is 'SSRF-guarded', signaling that private/internal targets will fail. But it omits critical behaviors for a network tool: how the URL is supplied (the schema has zero parameters), failure modes (timeouts, non-200, blocked sites), size limits, and whether pages are rendered or fetched as raw bytes. This is a serious transparency gap given the phantom URL capability.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no padding — the verb+resource is front-loaded and the SSRF note is a single efficient fragment. Minor redundancy: 'Browser Scrape:' repeats the tool name 'x402-browser-scrape' and could be dropped without losing meaning. Otherwise appropriately tight.

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

Completeness2/5

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

For a network-fetching tool with no annotations, no output schema, and no parameters, the description is far from sufficient. An agent cannot determine how to specify the URL, what happens on failure, what response shape to expect, or whether there are limits on page size. The single behavioral note (SSRF-guarded) does not compensate for these missing essentials.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters, the baseline would be 4 since no parameter documentation is needed. But the description explicitly references 'a public URL' as an input without the schema or description explaining how it is provided. An agent reading this description will reasonably expect a URL parameter that does not exist, making invocation ambiguous. The description needed to clarify the mechanism (e.g., a configured default or context-supplied URL) and does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — 'Fetch a public URL and return the full raw HTML page source' — and differentiates from extracted-text tools via the clause 'not just extracted text'. This distinguishes it from siblings like text-scrape, html-text-extract, and web-retrieve without opening their schemas. However, the claim that it fetches a URL is undercut by the empty input schema, which provides no parameter to specify the target URL.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear usage condition: use this tool when agents 'need the complete page, not just extracted text', which implicitly contrasts with text-extraction alternatives. It does not name specific sibling tools or state exclusions explicitly, but the when-to-use context is concrete enough for an agent to route correctly.

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

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TDQS

D1.6/5.0
Disambiguation1/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness2/5

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.

Resources