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fl_network

Lists the site's fetch/XHR API calls with method, status, timing, body and a JSON sample so agents can replay direct requests instead of UI clicks.

Instructions

List the API calls (fetch/XHR) the site made, with method, status, timing, body and a JSON sample. Use it to replace UI clicks with a direct {do:"request"} step: the fastest possible replay.

Input Schema

NameRequiredDescriptionDefault
limitNo
filterNoSubstring the URL must contain.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It implies a read operation but never says whether calls must be captured live, whether results persist across sessions, how pagination/limit behaves, or whether reading bodies has cost. For a capture-dependent tool with zero annotation coverage, this is a real gap.

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 tight sentences, front-loaded with the resource and its returned fields, then the practical use. The jargon ({do:"request"} step) is dense but each sentence earns its place.

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?

With no output schema, the description usefully names the returned fields, which is the main thing an agent needs. But it omits the capture prerequisite, the meaning of limit, and how results relate to an in-progress recording, leaving meaningful gaps for a network-inspection tool.

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?

Schema coverage is only 50% — filter is documented in the schema, limit is not — and the description mentions neither parameter. It neither explains the default/behavior of limit nor clarifies that filter matches the URL substring, so it does not compensate for the coverage gap.

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 (list the fetch/XHR API calls the site made) and enumerates what comes back: method, status, timing, body, JSON sample. That is far more informative than the sibling names fl_act/fl_extract/fl_snapshot, though it never explicitly contrasts itself with them.

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?

It does give a usage scenario — replacing UI clicks with a direct {do:"request"} replay step — but that phrasing assumes the agent already knows the flow/replay authoring model. There is no explicit statement of when not to use it, nor of prerequisites such as whether a recording session must exist first.

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