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network_get

Retrieve captured network events from browser activity. Filter by URL and optionally fetch response bodies.

Instructions

Retrieve captured network events.

Args:
    limit: max entries returned (chronological: oldest first within the last `limit`, newest last)
    filter_url: substring filter on URL
    include_body: fetch response bodies via CDP Network.getResponseBody
        for each matching entry. Bodies are truncated to max_body_bytes.
        Requires network_start(capture_bodies=True) (default).
    max_body_bytes: cap per-body length (default 10000)
    full: if True, return entries with full headers + body fields
        from network_index (use this once you've called network_start).
        Default False = legacy flat event stream (backward compat).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
filter_urlNo
include_bodyNo
max_body_bytesNo
fullNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses ordering, filtering, body fetching with requirements, truncation, and mode behavior. However, it does not mention potential side effects like memory usage or rate limits, which are minor omissions.

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 front-loads the purpose with a single line, then lists parameters with clear explanations. It is efficient but could benefit from more structured formatting (e.g., separate sections) to improve scanability. All sentences are valuable.

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

Completeness4/5

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

Given the presence of an output schema, the description covers all parameters, prerequisites, and behaviors. It omits error handling or edge cases, but overall it provides sufficient context for an AI agent to use the tool 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?

Schema coverage is 0%, and the description compensates by explaining each parameter in detail: chronological ordering for limit, substring filtering for filter_url, requirement for include_body, truncation cap, and full mode distinction. This adds essential 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 clearly states 'Retrieve captured network events' with a specific verb and resource, distinguishing it from sibling tools like network_start which initiates capture.

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 mentions prerequisites such as calling network_start for full mode and capture_bodies=True for include_body, but lacks explicit when-not-to-use or alternative tools beyond the implied dependency. This provides sufficient context for correct usage.

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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