massive-mcp

by danielbres

Overview Schema Source Related Servers Discussions Admin

Python

Local

get_short_volume

Retrieve daily short-volume data for a stock ticker, with optional date filtering and pagination.

Instructions

Daily short-volume data for a ticker.

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": {
      "ticker": "<ticker>"
    },
    "name": "get_short_volume"
  }
}

Input Schema

Name	Required	Description
`ticker`	Yes	Stock symbol.
`date_gte`	No	Inclusive lower bound on date.
`limit`	No	Max rows. Default 30.
`cursor`	No	Pagination cursor.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 8, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, and the description does not disclose behavioral traits such as data freshness, pagination behavior, or any rate limits. The schema implies pagination via cursor parameter, but the description omits this entirely.

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?

Very concise single sentence that front-loads the purpose. No wasted words, but no structured formatting (e.g., bullet points) that could help readability if more details were added.

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 4 parameters (including pagination) and no annotations, the description is too brief. It does not explain the output, typical use, or pagination mechanics, leaving gaps 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?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what the schema provides; e.g., 'for a ticker' mirrors the schema description for ticker.

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 it provides 'Daily short-volume data for a ticker,' specifying the resource (short-volume data) and the target (ticker). This differentiates it from siblings like get_short_interest which focuses on short interest rather than volume.

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 on when to use this tool vs alternatives such as get_short_interest or get_snapshot. It does not mention prerequisites, typical use cases, or any conditions.

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