Git RAG MCP Server

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validate_github_result

Validates GitHub operation results to ensure they are correct and error-free. Use it to verify responses from the GitHub MCP server.

Instructions

Perform basic validation of a GitHub MCP tool result.

Args: operation: GitHub operation being tested.

result:
    Result returned by the GitHub MCP server.

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": {
      "operation": "<operation>",
      "result": "<result>"
    },
    "name": "validate_github_result"
  }
}

Input Schema

Name	Required	Description	Default
`result`	Yes
`operation`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral-disclosure burden. It says only "basic validation," without explaining what is checked, what triggers failure, whether the tool has side effects, or any limitations; this is insufficient for a validation operation.

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 is front-loaded, brief, and well-structured with an Args section. Every sentence contributes to understanding the tool and its inputs, with no redundant or filler text.

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?

An output schema exists, so return-value explanation is not required. However, with no annotations and only a vague "basic validation" description, the tool's behavioral contract is under-specified for an agent deciding whether and how to call it.

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 description coverage is 0%, so the description must supply parameter meaning. It does define both parameters (operation = GitHub operation being tested; result = result returned by the GitHub MCP server), but adds no format, examples, or expected value details.

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 uses a specific verb ("validate") and resource ("GitHub MCP tool result"), making the core purpose clear. It is distinguishable from sibling validate_rag_result by the GitHub focus, though it does not explicitly name that alternative.

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 gives no explicit guidance on when to use this tool versus alternatives such as validate_rag_result or create_test_case. Usage is only implied by the phrase "operation being tested," which is not enough to route an agent reliably.

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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