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playwright-network-chaos-mcp

playwright-network-chaos-mcp

by vola-trebla
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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inject_latency

Adds artificial delay to specific requests to simulate slow networks and overloaded APIs, verifying loading indicators and graceful timeouts.

Instructions

Adds artificial delay to requests matching a URL pattern, simulating slow networks or overloaded APIs. Use to answer: does the app show loading states when the API takes 3 seconds? Does it time out gracefully?

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>",
      "intercept_pattern": "<intercept_pattern>"
    },
    "name": "inject_latency"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesURL of the page to test
viewportNoViewport size (default: 1280×720)
jitter_msNoRandom additional delay in milliseconds (default: 0)
latency_msNoBase delay in milliseconds to add to each matched request (default: 3000)
loading_selectorNoCSS selector for the loading state that should appear (e.g., '.skeleton-loader')
intercept_patternYesGlob pattern for requests to delay (e.g., '**/api/**')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It states the action (adding artificial delay) and its purpose (simulating slow networks/overloaded APIs), but does not disclose details like reversibility, session scope, cleanup, or impact on subsequent requests. It is not misleading, but leaves out behavioral nuances expected for a network-interception tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action, followed by concrete use-case questions. It is concise, zero waste, and every 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?

Given 6 parameters, a nested viewport object, and no output schema, the description provides essential purpose and use cases but does not explain the interplay between latency_ms and jitter_ms, the role of loading_selector, or potential side effects. It is adequate for selection but not fully complete for invocation without relying on schema details.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all six parameters thoroughly. The description does not add parameter-specific meaning beyond mentioning 'URL pattern' (which relates to intercept_pattern). Baseline 3 is appropriate since the schema does the heavy lifting, and the description adds minimal unique value.

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's function with a specific verb ('Adds artificial delay') and resource ('requests matching a URL pattern'). It distinguishes itself from sibling tools like simulate_api_failure or block_resources by focusing on latency injection rather than errors or blocking.

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 provides concrete use cases ('Does the app show loading states when the API takes 3 seconds? Does it time out gracefully?'), giving clear context for when to use this tool. It does not explicitly mention alternatives or exclusions, but the use cases are specific enough to guide an agent.

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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