lxDIG MCP

suggest_tests

Suggest test cases for a code element by analyzing its structure and similar existing tests. Identifies test names, types, and coverage gaps.

Instructions

Suggest test cases for a code element. Requires elementId — use the id field returned by graph_query or code_explain (not a symbol name). Returns suggested test names, types, and coverage gaps based on the element's structure and similar existing tests.

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": {
      "elementId": "<elementId>"
    },
    "name": "suggest_tests"
  }
}

Input Schema

Name	Required	Description	Default
`elementId`	Yes	Code element ID
`limit`	No	Number of suggestions
`profile`	No	Response profile	compact

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jun 21, 2026

TDQS

A4.2/5.0

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 discloses the return information (suggested test names, types, coverage gaps) but does not explicitly state whether the tool is read-only, safe, or has any side effects. The non-destructive nature can be inferred, but should be explicit.

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?

The description consists of two sentences with no unnecessary words. The first sentence states the purpose and key requirement, the second describes the output. It is front-loaded and efficient.

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 three parameters, no output schema, and no annotations, the description covers the essential aspects: required input source, return content, and the fact that suggestions are based on structure and existing tests. A minor gap is the lack of detail on the limit and profile parameters' effects, but these are covered in the schema.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value by clarifying that elementId must be the id field from graph_query or code_explain, which is not evident from the schema description ('Code element ID'). For limit and profile, no extra description is added, but they are adequately described in 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?

The description states the tool's main action ('Suggest test cases for a code element') with a specific verb and resource. It also clarifies the required input format (elementId from specific tools) and what it returns (test names, types, coverage gaps), leaving no ambiguity about the tool's purpose.

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 clearly explains the prerequisite for using this tool: the elementId must come from graph_query or code_explain, not a symbol name. This gives context on when to use it. However, it does not explicitly differentiate from sibling tools like test_select or test_categorize, nor state when not to use it.

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