GAIIA Expert Proxy (MCP Server)

gaiia_transform

Audit, refactor, or generate code by providing a code block and instructions to an active GAIIA expert.

Instructions

Audit, refactor, or generate code using the active GAIIA expert.

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": {
      "code": "<code>",
      "instructions": "<instructions>"
    },
    "name": "gaiia_transform"
  }
}

Input Schema

Name	Required	Description	Default
`code`	Yes	The code block to process
`instructions`	Yes	Instructions for the expert

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 26, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions auditing, refactoring, or generating code but does not explain side effects (e.g., file modifications), prerequisites (e.g., active expert must be set), or safety considerations. This is insufficient for a transformation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 10 words, which is concise but lacks front-loaded specifics. While it conveys the core purpose, it does not earn its place fully due to vagueness and missing details that would aid agent selection.

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?

Given the tool has no output schema and two simple parameters, the description should provide more context about return values, behavioral outcomes, or typical use cases. It fails to do so, leaving gaps in understanding for an AI agent.

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?

The input schema has 100% coverage with descriptions for 'code' and 'instructions'. The tool description does not add any additional meaning or context for these parameters, so the baseline score 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 clearly states the tool's actions ('Audit, refactor, or generate code') and resource ('using the active GAIIA expert'). It distinguishes from siblings by specifying the active expert, though could be more explicit about differences from tools like gaiia_analyze_project.

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 alternatives like gaiia_analyze_project or gaiia_start_process. It lacks any 'when-to-use' or 'when-not-to-use' information, leaving the agent to infer usage context.

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

Deploy Server