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pyalgobot

angelone-mcp

by pyalgobot

gtt_create_rule

Create a Good-Till-Triggered rule that automatically places an order when the market hits your chosen trigger price.

Instructions

Create a GTT (Good Till Triggered) rule that auto-places an order when the trigger price is hit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qtyYes
priceYes
exchangeYes
timeperiodNo
producttypeYes
symboltokenYes
disclosedqtyNo
triggerpriceYes
tradingsymbolYes
transactiontypeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full disclosure burden. It does reveal a key non-obvious behavior—auto-placing an order later when the trigger price is hit—which is helpful. However, it omits other behavioral traits such as authentication requirements, persistence, error handling, or what happens after creation.

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 a single, tightly worded sentence that front-loads the action and resource, expands the GTT acronym, and contains no filler. Every word adds value, though the brevity does leave substantive gaps.

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?

For a 10-parameter create operation with 0% schema parameter descriptions and no annotations, this description is too thin. Even though an output schema exists, the agent still lacks guidance on how to populate required fields like symboltoken, exchange, producttype, transactiontype, and disclosedqty, and gets no context about the GTT lifecycle or timeperiod behavior.

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?

Schema description coverage is 0%, and the description only indirectly references triggerprice. It does not explain the meaning or valid values for exchange, producttype, transactiontype, symboltoken, disclosedqty, timeperiod, or the difference between price and triggerprice. With 8 required parameters, the description fails to compensate for the schema's lack of descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Create') and a clear resource ('GTT rule'), and explains the core behavior: auto-placing an order when the trigger price is hit. This clearly distinguishes the tool from sibling tools like gtt_modify_rule, gtt_cancel_rule, gtt_details, and gtt_list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for creating a new GTT rule, and the sibling context reinforces that other operations are separate. However, it does not explicitly state when to use this over place_order or the other GTT management tools, nor does it mention prerequisites like authentication or symbol selection.

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

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