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finstack-mcp

finstack-mcp

by finstacklabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sector_performance

Get today's performance of Nifty sectoral indices. See which sectors are up or down, with best and worst performers highlighted.

Instructions

Get performance of Nifty sectoral indices.

Shows how different sectors (Banking, IT, Pharma, FMCG, Auto, Metal, Realty, Energy) performed today, with best and worst performers highlighted.

No arguments needed.

Examples: sector_performance() → Which sectors are up/down today?

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "sector_performance"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.2

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains this is a read-only look at sector indices, the list of covered sectors, and that best/worst performers are highlighted, adding meaningful context beyond the empty schema.

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, followed by a helpful example. Every sentence adds value and there is no redundant filler.

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

Completeness5/5

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

For a parameterless tool with an existing output schema, the description is complete: it identifies the data source, the specific sectors, the time period, and the best/worst highlight feature. No further return-value detail is necessary.

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 tool has zero parameters, so the schema provides no properties. The description explicitly states 'No arguments needed' and includes a call example, fully satisfying the parameterless baseline.

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 clearly states the tool retrieves performance of Nifty sectoral indices, names specific sectors, and mentions highlighting best/worst performers. This distinguishes it from broader market indices and individual stock tools.

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

Usage Guidelines4/5

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

The tool's usage is clear: call it to see today's Nifty sector performance, and the example plus 'No arguments needed' specify exactly how to invoke it. It does not explicitly list alternatives or when-not-to-use cases, but the context is strong.

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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