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code-lens

code-lens

by j0hanz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Generate Test Plan

generate_test_plan
Read-onlyIdempotent

Generates test cases from code diffs, auto-detecting language and test framework.

Instructions

Generate test cases. Prerequisite: generate_diff. Auto-infer repo/language/framework.

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": "generate_test_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoPrimary language (e.g. TypeScript, Python, JavaScript, Go, Rust, Java). Auto-infer from files.
testFrameworkNoTest framework (jest, pytest, etc). Auto-infer.
maxTestCasesNoMax test cases (1-30). Default: 15.

Output Schema

NameRequiredDescriptionDefault
okYesWhether the tool completed successfully.
resultNoSuccessful result payload.
errorNoError payload when ok is false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.12.0

TDQS

A3.5/5.0
Behavior1/5

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

Description says 'Generate test cases' implying creation, but annotations declare readOnlyHint: true. This is a direct contradiction. Other behavioral traits are not disclosed beyond annotations.

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?

Two sentences, no extraneous words. Efficiently communicates core purpose and prerequisite.

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?

Has output schema, so return values are covered. Description mentions prerequisite and auto-inference but lacks detail on how inference works or what assumptions are made. Contradiction reduces completeness.

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%; description adds 'Auto-infer' which is already in schema descriptions. No additional meaning beyond 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?

Clearly states the verb 'generate' and resource 'test cases'. Prerequisite and auto-inference differentiate from siblings like generate_diff.

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?

Explicitly states prerequisite generate_diff, implying a sequence. Does not mention when to avoid or alternative tools, but context is clear.

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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