vibecraft-mcp

audit_system_performance

Audit backend code, database queries, network waterfalls, and frontend rendering to identify performance bottlenecks, N+1 queries, IDOR security risks, and slow pagination.

Instructions

Audits backend API code, database queries, network waterfalls, and frontend rendering for performance bottlenecks, N+1 queries, un-transactional mutations, IDOR security issues, and slow OFFSET pagination.

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": {
      "codeOrQuery": "<codeOrQuery>"
    },
    "name": "audit_system_performance"
  }
}

Input Schema

Name	Required	Description	Default
`scope`	No	Optional optimization scope
`codeOrQuery`	Yes	Backend controller, database query, network call, or React component snippet to audit

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.8.0Sep 14, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the transparency burden. It does disclose exactly what it examines and which issue classes it detects, implying a read-only analysis, but it never explicitly states that the snippet is not modified, that no external systems are touched, or what the result looks like.

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?

A single dense sentence front-loads the action, resource, and scope, then enumerates the detected issue types. No filler.

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?

For a two-parameter audit tool with a fully described schema, the description supplies all selection-relevant detail: resource domains, optional scope, and target issues. The only minor gap is no explicit mention of the return/report format, but this is not needed to invoke it correctly.

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 baseline is 3. The description reinforces what codeOrQuery may contain and adds the issue-detection context, but it doesn't provide syntax/format details 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?

Opens with the strong verb 'Audits' and names four concrete resource classes (backend API code, database queries, network waterfalls, frontend rendering), followed by a specific list of issue types it hunts for. This clearly differentiates it from sibling audit_ux_compliance, which targets UX rather than performance/security.

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 establishes clear context: supply backend/database/network/frontend snippets to get a performance/security audit. It doesn't explicitly name alternatives or when not to use it, but the domain is unambiguous.

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

Deploy Server