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tianhuil

webfetch-camouflage

by tianhuil

fetch_url

Fetch web content with browser fingerprint camouflage to bypass bot detection and convert HTML to clean Markdown.

Instructions

Fetch web content from a URL with browser camouflage.

Args: url: The URL to fetch impersonate: Browser to impersonate (default: 'chrome'). Can be any string - curl_cffi will attempt to use the corresponding browser fingerprint. Common values include: chrome99, chrome100, chrome101, chrome104, chrome107, chrome110, chrome116, chrome119, chrome120, chrome123, chrome124, chrome131, chrome133a, chrome136, chrome99_android, chrome131_android, safari153, safari155, safari170, safari180, safari184, safari260, safari172_ios, safari180_ios, safari184_ios, safari260_ios, firefox133, firefox135, firefox135_android, tor145, edge99, edge101, edge133, edge135 timeout: Request timeout in seconds (default: 10) max_chars: Maximum number of characters to return in the response. If None, returns the full content (default: None)

Returns: The fetched content converted to Markdown format, or an error message if the request fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
impersonateNochrome
timeoutNo
max_charsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must fully disclose behavior. It explains the fetch, browser impersonation, Markdown conversion, and error conditions. However, it lacks details on potential issues like rate limiting, authentication requirements, or behavior on invalid URLs, which would improve transparency.

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?

The description is well-structured with a clear summary line followed by argument and return documentation. The list of impersonation values is lengthy but informative. It earns its place, though it could be slightly more concise.

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

Completeness5/5

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

Given the tool's simplicity, the presence of an output schema (which we assume documents return structure), and the description's coverage of all parameters and behavior (including conversion to Markdown), the description is complete for an AI agent to use correctly.

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

Parameters5/5

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

The input schema has no descriptions (coverage 0%), but the description provides extensive semantics for all four parameters, including default values, examples for impersonate, and explanation of max_chars behavior. This adds significant meaning beyond the schema.

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

Purpose5/5

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

The description states 'Fetch web content from a URL with browser camouflage,' which clearly defines the tool's action and resource. It also specifies a unique feature (browser camouflage), making it easily distinguishable even without sibling tools.

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?

While no explicit when-to-use or when-not-to-use guidance is given, the description thoroughly explains the tool's purpose and parameters. The absence of sibling tools reduces the need for alternatives comparison, so the description is clear enough for an AI agent to decide.

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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