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pyalgobot

angelone-mcp

by pyalgobot

gtt_modify_rule

Modify an existing GTT rule by updating quantity, price, or trigger price to adjust your automated order conditions.

Instructions

Modify an existing GTT rule.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
qtyYes
priceYes
exchangeYes
timeperiodNo
symboltokenYes
disclosedqtyNo
triggerpriceYes
tradingsymbolYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'Modify an existing GTT rule.' It does not explain whether fields are overwritten, whether rules must be in a particular state, what side effects occur, or whether the modification is reversible.

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 efficient sentence with no filler or redundancy. However, the conciseness comes at the cost of useful detail, so it earns a 4 rather than a 5.

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?

Despite having an output schema, the tool has 9 parameters, zero schema descriptions, and no annotations. The one-sentence description is far too lean to guide an agent on required fields, update semantics, or constraints, so the overall definition is incomplete.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no parameter-level meaning. The agent is left to infer the roles of id, symboltoken, exchange, tradingsymbol, qty, price, triggerprice, and timeperiod from names alone, which is insufficient for a 9-parameter mutation tool.

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 uses a specific verb ('Modify') and a named resource ('existing GTT rule'), clearly distinguishing the operation from creating or cancelling a rule. It does not explicitly name sibling alternatives, but the intent is unambiguous.

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?

Usage is only implied: if you need to change an existing GTT rule, use this tool. No explicit guidance is provided about prerequisites, when not to use it, or how it relates to alternatives like gtt_create_rule or gtt_cancel_rule.

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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