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WhiteNightShadow

camoufox-reverse-mcp

save_script

Download JavaScript files from web pages to local storage for analysis and debugging in reverse engineering workflows.

Instructions

Download a JavaScript file from the page and save it to a local path.

Args: url: URL of the script to download. save_path: Local file path to save the script to.

Returns: dict with status, save path, and file size in bytes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
save_pathYes
Behavior2/5

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

With no annotations provided, the description carries full burden but only covers basic functionality. It mentions the return format (dict with status, path, size) but omits critical behavioral details: error handling (e.g., invalid URLs, permission issues), file overwriting behavior, network timeouts, or authentication needs. For a download/save operation, this leaves significant gaps in understanding how the tool behaves in edge cases.

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 and front-loaded with the core purpose, followed by parameter and return details. Every sentence adds value without redundancy, though it could be slightly more concise by integrating the 'Args' and 'Returns' sections into flowing text. Overall, it's efficient and easy to parse.

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

Completeness3/5

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

Given no annotations, no output schema, and low schema coverage, the description provides basic completeness for a simple download tool but lacks depth. It covers purpose, parameters, and returns adequately, yet misses advanced context like error scenarios, performance limits, or integration with sibling tools (e.g., 'get_script_source' for verification). For a tool with potential file system and network interactions, more behavioral detail would improve completeness.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate—it clearly explains both parameters: 'url' as the script's URL to download and 'save_path' as the local file path for saving. This adds essential meaning beyond the bare schema, though it could enhance with format examples (e.g., absolute vs. relative paths) or validation rules. With 2 parameters fully documented, it meets most needs.

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 clearly states the specific action ('Download a JavaScript file from the page and save it to a local path') with both verb and resource, distinguishing it from siblings like 'get_script_source' (which retrieves but doesn't save) or 'list_scripts' (which enumerates). It precisely defines the tool's function without ambiguity.

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

Usage Guidelines3/5

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

The description implies usage for downloading and saving scripts from web pages, but provides no explicit guidance on when to use this tool versus alternatives like 'get_script_source' (for viewing without saving) or 'save_path' parameter specifics. It lacks clear exclusions or prerequisites, leaving usage context inferred rather than stated.

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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