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camoufox-versatile-mcp

replay_vmp_offline

Run captured VMP JavaScript in headless Node to verify extracted signing algorithms by comparing output with expected signatures from browser requests.

Instructions

Run captured VMP code in headless Node and call the entry function.

Useful for verifying you've correctly extracted the signing algorithm: call the VMP's signing function with the inputs a real request would use, and check that the output matches what the browser actually sent.

Args: vmp_code: The JavaScript source that defines the VMP / sign function. entry: The name of the function exported on global that we should call. input: A dict to pass to the entry function. Will be JSON-serialized and re-parsed inside the Node sandbox. timeout_ms: VM timeout. JS that runs longer triggers a V8 timeout error. expected_sign: optional reference sign captured from the browser. When set and auto_diff is True, the response includes a structured diff (match / common_prefix_len / first_diff_idx). auto_diff: if True and expected_sign is set, compute a structured diff. supplied_env: optional dict merged into the sandbox before the VMP code runs. Use this to feed navigator.userAgent, screen.width, Date.now(), document.cookie etc. (see auto_suggest_missing_props).

Returns: dict with status, output, elapsed_ms, optional diff, and optional suggestion hint when outputs don't match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entryYes
inputYes
vmp_codeYes
auto_diffNo
timeout_msNo
supplied_envNo
expected_signNo
Behavior5/5

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

With no annotations, the description fully covers behavior: headless execution, JSON serialization/parsing, timeout handling, optional diff computation, environment merging, and return structure. No contradictions.

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 sections and bullet-pointed args, but slightly verbose. Every sentence adds value, though minor trimming could improve conciseness.

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?

For 7 parameters and no output schema, the description covers return fields (status, output, elapsed_ms, diff, suggestion), mentions optional features, and provides enough context for correct invocation.

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?

Despite 0% schema description coverage, the description thoroughly explains each of the 7 parameters, including their types and roles (e.g., vmp_code as JS source, supplied_env for environment). This compensates fully.

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 tool runs VMP code in headless Node and calls an entry function, with a specific use case: verifying extraction of signing algorithm. It distinguishes itself from sibling tools through context.

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?

The description explicitly states when it is useful (verifying signing algorithm extraction) but does not mention alternatives or when not to use. The context is clear enough for selection.

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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