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pyalgobot

angelone-mcp

by pyalgobot

get_market_quote

Retrieve live market quotes for up to 50 instruments per exchange in a single request. Choose LTP, OHLC, or FULL data to monitor prices efficiently.

Instructions

Get market quotes for up to 50 instruments per exchange in one call.

mode: LTP | OHLC | FULL exchange_tokens: e.g. {"NSE": ["3045", "881"], "NFO": ["58662"]} - a map of exchange -> list of symbol tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
exchange_tokensYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the 50-instrument-per-exchange limit and the LTP/OHLC/FULL modes, which is useful behavioral context. However, it does not mention authentication requirements, error conditions, or how the API handles invalid tokens, leaving notable gaps.

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 compact and front-loaded with the primary purpose, followed by a useful parameter key block. The example is necessary and well-placed, and there is minimal fluff. The formatting could be slightly tighter, but every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, the description need not detail return values. It covers purpose, parameter semantics, a realistic example, and the batch limit. The main missing element is explicit usage guidance versus related tools, but the core information an agent needs to invoke this tool correctly is present.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully compensates by defining valid values for mode and explaining the exchange_tokens structure with a concrete JSON example. This goes well beyond the bare string/object types in the schema and removes ambiguity about how to construct a valid call.

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 action and resource: 'Get market quotes' with the precise scope 'up to 50 instruments per exchange in one call.' The batching and per-exchange framing distinguishes this from single-instrument siblings like get_ltp.

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 'in one call' phrasing and the per-exchange limit imply that this tool is for batch quote retrieval, but it never explicitly says when to use it instead of alternatives such as get_ltp or get_candle_data. No exclusions or alternative conditions are provided.

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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