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kothar

kothar

by yahiaklk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

explain_why

Explains why a specific MCP server is a good fit for your project by evaluating the server name and project description.

Instructions

Explain why a specific MCP server is a good fit for a given project. Example: server_name="github", project_description="open source Python library with CI/CD"

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": {
      "server_name": "<server_name>",
      "project_description": "<project_description>"
    },
    "name": "explain_why"
  }
}

Input Schema

NameRequiredDescriptionDefault
server_nameYes
project_descriptionYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.3/5.0
Behavior2/5

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

No annotations and description only states purpose. Does not disclose behavior like error handling, required permissions, or output format beyond what output schema might provide.

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?

Description is a single sentence plus example, which is concise. However, the structure could be improved by adding a brief usage context.

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?

Given low complexity and presence of output schema, description is minimally adequate but lacks usage guidelines and behavioral details that would make it fully self-contained.

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

Parameters2/5

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

Schema coverage is 0%, meaning parameters have no descriptions. The description provides an example usage but does not explain parameter semantics beyond the example.

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?

Describes a clear verb+resource combination: 'Explain why a specific MCP server is a good fit for a given project.' This distinguishes it from sibling recommendation tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides an example but no explicit guidance on when to use this tool versus the sibling recommendation tools. The example helps but does not fully clarify context.

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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