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Optimist MCP Server

Optimist MCP Server

by Atomic-Germ
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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detect_code_smells

Detect anti-patterns and code quality issues by analyzing a file or directory, with configurable severity thresholds.

Instructions

Identify anti-patterns and code quality issues

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": {
      "path": "<path>"
    },
    "name": "detect_code_smells"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesDirectory or file path to analyze
severityNoMinimum severity to report

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the purpose and does not describe how the analysis works, whether it is read-only, what types of code smells it detects, or what side effects or performance considerations exist.

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?

The description is a single concise sentence that front-loads the core action with no filler or redundancy. It is appropriately sized for the amount of information conveyed, though it is minimal in scope.

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?

There is no output schema and no annotations, so the description must explain what happens when the tool is invoked, but it does not mention return values, result format, or any runtime behavior. An agent would be uncertain about the tool's outcome and how to handle its response, making the context incomplete.

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?

Both parameters are already fully described in the schema: 'path' as the directory/file path to analyze and 'severity' as the minimum severity to report. Since schema coverage is 100%, the description adds no additional parameter semantics, so the baseline of 3 applies.

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 'Identify anti-patterns and code quality issues' uses a clear verb and resource that matches the tool name 'detect_code_smells'. It is easy to understand what the tool does, but it does not distinguish itself from sibling tools like analyze_complexity or suggest_refactoring, so the differentiation is weak.

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?

The description provides no guidance on when to use this tool versus its siblings. There is no mention of alternatives, exclusions, or conditions under which this tool is the best choice among the listed analysis and optimization tools.

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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