FullStack Audit MCP

trace_integration

List statically recognizable frontend request calls and backend Express-style route declarations with file/line evidence, and flag simple request-field mismatches for literal paths.

Instructions

List statically recognizable frontend request calls and backend Express-style route declarations with file and line evidence. For literal matching paths, report simple request-field mismatches when the same-line JSON object and route body reads are visible. This does not resolve dynamic URLs or prove a route is connected.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "trace_integration"
  }
}

Input Schema

Name	Required	Default
`path`	No	.
`limit`	No
`offset`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 18, 2026

TDQS

B3/5.0

Behavior3/5

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

With no annotations, the description carries the full burden and does disclose important behavioral limits: it only handles static/literal paths and does not prove connectivity. It still omits whether the operation is read-only, how pagination behaves, and what the result shape 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.

Conciseness4/5

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

Three tight sentences with the core capability front-loaded and the caveats last. Every sentence contributes; no filler.

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?

For a static-analysis tool with no output schema and no annotations, the description usefully characterizes the output (file/line evidence, mismatch reports) but leaves pagination and path scoping unexplained, so an agent cannot fully predict invocation behavior.

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 description coverage is 0% across three parameters (path, limit, offset), and the description adds nothing about scoping the scan root or the pagination limits. An agent must guess that limit/offset paginate and that path is a filesystem root.

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?

The description names a specific verb+resource pair (list frontend request calls and backend Express route declarations) and adds the evidence granularity (file and line). It is clearly distinguishable from review_frontend/review_backend in intent, though it never names a sibling to route against.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to choose this over scan_project or the review_* tools. The closing sentence scopes capability boundaries (dynamic URLs, connectivity proofs) but that is a limitation statement, not a when-to-use condition or an alternative.

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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