Skip to main content
Glama
pyalgobot

angelone-mcp

by pyalgobot

get_oi_buildup

Retrieve open-interest buildup data for F&O contracts by datatype and expiry type to identify long buildup, short buildup, short covering, or long unwinding.

Instructions

Get open-interest buildup data (long/short buildup, unwinding, etc.) for F&O contracts.

datatype: Long Built Up | Short Built Up | Short Covering | Long Unwinding expirytype: NEAR | NEXT | FAR

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datatypeYes
expirytypeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

B3.2/5.0
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 only says 'Get' data, implying a read operation, but does not disclose authentication needs, rate limits, data freshness, or any side effects. The listed values for datatype and expirytype are parameter information rather than behavioral transparency.

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 compact and front-loaded with the core purpose. The parameter value lists are formatted clearly and contain no filler. Every line contributes useful information.

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?

For a simple read-only tool with two required string parameters and an output schema, the description supplies the necessary valid values to call it correctly. However, it lacks usage context, behavioral expectations, and differentiation from the closely related get_oi_data sibling. It is adequate but has clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage and no enums for either parameter. The description compensates by listing the exact allowed values for datatype and expirytype, which is essential for correct invocation. It does not deeply explain the meaning of each value, but the provided enum lists add substantial value beyond the bare schema.

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 opens with a specific verb and resource: 'Get open-interest buildup data' for F&O contracts. It also enumerates the data categories (long/short buildup, etc.), making the tool's purpose clear. It does not explicitly distinguish itself from the sibling get_oi_data, but the name and content are sufficiently specific.

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 given about when to use this tool versus related alternatives like get_oi_data or get_put_call_ratio. The description states what data is returned but not the scenarios where this data is relevant or when a sibling should be preferred.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pyalgobot/angelone-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server