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k11 API Functional QA

k11 API Functional QA

Official

List environments

list_environments

Retrieve environments, auth profiles, databases, fixtures, and test flows from .qa-mcp/api-test.yaml so you can choose the right target and verify API test setup before running functional checks.

Instructions

Environments (base URL, whether writes are allowed and why), auth profiles, databases and fixtures from .qa-mcp/api-test.yaml, plus the flows in tests/api/.

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": "list_environments"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full burden, and it does disclose useful behavioral content by enumerating what is returned, including the write-permission flag and its rationale, which matters for safety decisions. It still never says the tool is read-only, side-effect free, or purely file-sourced rather than a live probe, leaving the mutation profile implicit.

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?

A single sentence that front-loads the highest-value item (environments and their write policy) and then lists the remaining resource types. It is dense but every clause names a distinct return category; the embedded file path is the only element that could be trimmed.

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?

There is no output schema, so the description must convey return content, and it enumerates all five categories an agent would need. For a zero-parameter, side-effect-free listing tool this is close to complete; only the read-only/no-side-effects note is missing.

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

Parameters4/5

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

The tool takes zero parameters, so there is no parameter meaning to add and the baseline of 4 applies. The description correctly spends its space on return content instead of inventing arguments.

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 the concrete contents it surfaces: environments (base URL, write permission and the reason), auth profiles, databases, fixtures from .qa-mcp/api-test.yaml, plus flows under tests/api/. That is specific enough to separate it from call_api, query_db and run_flows, which act on resources rather than enumerate configuration. It never states the verb outright (the title carries 'List'), so it falls short of a clean 5.

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 when-to-use statement, no prerequisite, and no mention of an alternative tool. An agent must infer on its own that this is the discovery step before call_api or run_flows, and nothing in the text confirms that inference.

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