GAIIA Expert Proxy (MCP Server)

gaiia_list_experts

List available AI experts and their specialties for code audits and architectural analysis. Use an optional search query to find relevant experts.

Instructions

List available AI experts and their specialties.

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": "gaiia_list_experts"
  }
}

Input Schema

Name	Required	Description	Default
`query`	No	Optional search query

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 exist, so the description carries full transparency burden. It conveys a read operation but omits any details about side effects, authentication requirements, rate limits, or output format. Minimal behavioral context beyond the basic action.

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 with no extraneous words. It is appropriately front-loaded, though slightly under-specified for the parameter usage.

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 the tool's simplicity (one optional param, no output schema), the description provides enough to understand the core function. It mentions output includes specialties, but does not describe the response structure or provide an example, leaving minor gaps.

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?

The input schema has 100% description coverage for the single optional query parameter. However, the tool description does not elaborate on how the query filters results (e.g., by name or specialty), offering no added value over the schema. A brief hint would improve usability.

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 lists AI experts and their specialties, distinguishing it from sibling tools like gaiia_list_processes and gaiia_analyze_project. A slight lack of specificity about what constitutes an 'expert' prevents a higher score.

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, nor does it mention any prerequisites or exclusions. The agent receives no context for decision-making.

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

Deploy Server