AIGigLab MCP Server

list_assets

List AI-generated assets with pagination. Use page and limit parameters to browse through your generated visual and voice assets.

Instructions

List your generated AI assets.

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": "list_assets"
  }
}

Input Schema

Name	Required	Description	Default
`page`	No	Page number (default: 1)
`limit`	No	Items per page (default: 20)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.3.0Jul 15, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations exist, so the description must fully disclose behavior. It only implies a read operation ('list') but omits details such as pagination behavior, default ordering, maximum limit, error responses, or whether empty results return an empty list or an error.

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, clear sentence with no unnecessary words. It is front-loaded and efficient, though it could be expanded slightly to include usage guidance or behavioral notes without sacrificing conciseness.

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 lack of output schema and annotations, the description is too minimal. It does not explain expected return format, pagination behavior, or potential edge cases (e.g., zero assets). The tool is simple, but the description still falls short of providing complete context for reliable invocation.

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 100%, and the parameters 'page' and 'limit' are adequately described in the schema itself. The description adds no additional meaning beyond what the schema already provides, earning the baseline score of 3.

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 verb 'List' and the resource 'your generated AI assets'. It is specific about ownership and scope. However, it does not differentiate from other list tools like 'list_voices' or 'get_leads', which could lead to confusion when choosing among siblings.

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?

No guidance is provided on when to use this tool versus alternatives (e.g., for different asset types) or any prerequisites. The agent gets no context about optimal usage or limitations.

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