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Check live conformance

check_live_conformance

Calls a running API endpoint and verifies its status, content type and JSON response body against the OpenAPI spec's response schema to catch live drift from the documented contract.

Instructions

Call a running endpoint (e.g. endpoint='GET /orders/{id}', path_params={'id': '1001'}) and check status, content type and the JSON body against the spec's response schema. Header values may use ${ENV:NAME}.

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": {
      "spec": "<spec>",
      "base_url": "<base_url>",
      "endpoint": "<endpoint>"
    },
    "name": "check_live_conformance"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyNo
specYes
queryNo
headersNo
base_urlYes
endpointYes
path_paramsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose the validation criteria and a non-obvious behavior (headers support ${ENV:NAME} substitution). However, it omits that this fires a real network request, says nothing about whether non-GET endpoints mutate remote state, and does not cover auth, timeouts, or failure handling.

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 dense sentences with the action front-loaded and a compact inline example; there is no filler. The example is embedded mid-clause rather than set apart, which makes it slightly harder to scan but wastes no words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter tool with no annotations and no output schema, the definition is thin: how the conformance result is reported is never described, four of the seven parameters have no semantics, and the request's side-effect profile is unstated. An agent would have to guess before calling it safely.

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 description coverage is 0% across 7 parameters, so the description must compensate. It clarifies endpoint syntax ('GET /orders/{id}') and the path_params mapping via example, but leaves spec (file path vs URL vs inline), base_url, query, and body entirely unexplained.

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 gives a concrete verb and resource: it calls a running endpoint and validates status, content type, and JSON body against the spec's response schema. That is clearly distinct from static siblings like diff_contracts or generate_api_tests, though it never explicitly names an alternative to sharpen the contrast.

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?

There is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives (e.g. check_deployed_contract). The phrase 'running endpoint' hints that this is for live servers rather than static specs, but the agent must infer the selection criteria entirely.

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