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v8-cpu-profile-decoder-mcp

v8-cpu-profile-decoder-mcp

by vola-trebla
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

analyze_async_bottlenecks

Identify wasteful async machinery in V8 CPU profiles, such as microtask queues and nextTick saturation, to determine if event-loop overhead is the real bottleneck.

Instructions

Detects event-loop overhead in a V8 CPU profile by identifying V8 internal frames that represent async machinery — microtask queue processing, nextTick saturation, and timer/immediate callbacks. These frames are invisible to most profilers but consume real CPU when promise chains are deep or nextTick is overused. Use to answer: is the bottleneck async orchestration overhead rather than synchronous computation?

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": {
      "profile_path": "<profile_path>"
    },
    "name": "analyze_async_bottlenecks"
  }
}

Input Schema

NameRequiredDescriptionDefault
profile_pathYesAbsolute path to the .cpuprofile file
threshold_percentNoAsync overhead percentage above which a warning is emitted in the verdict (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds valuable context about why these frames are invisible to profilers and when they consume CPU (deep promise chains, nextTick overuse). However, it does not explicitly state that the operation is read-only, describe side effects, or outline the return format. While the analytical wording implies a safe read, the transparency is not complete.

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?

Three sentences, each with a purpose: the first states the core action, the second provides necessary technical nuance, and the third gives a crisp usage question. It is front-loaded and contains zero filler or redundant information.

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 tool's simplicity (2 params, no output schema), the description is quite complete. It covers detection target, mechanism, and a concrete use-case. The absence of an explicit return description is a minor gap, but the threshold_percent schema's 'verdict' mention and the description's question form partially compensate by implying a resulting answer.

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%: profile_path is described as an absolute path and threshold_percent has a default, range, and behavior note about a verdict warning. The description itself adds no parameter-level detail, so the schema fully carries the meaning. Baseline of 3 is appropriate.

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 uses a specific verb ('Detects') and precise resource ('event-loop overhead in a V8 CPU profile by identifying V8 internal frames'), clearly distinguishing it from siblings like extract_hottest_functions or analyze_gc_pressure. It names exact async mechanisms (microtask processing, nextTick saturation, timer/immediate callbacks), leaving no ambiguity about what the tool does.

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 a clear usage context: 'Use to answer: is the bottleneck async orchestration overhead rather than synchronous computation?' This tells the agent when to select this tool. However, it does not explicitly state when not to use it or name alternative sibling tools, so it falls short of full exclusion guidance.

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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