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BACH-AI-Tools

Indian Stock Exchange API2 MCP Server

analyst_recommendations

Get analyst recommendations for specific Indian stocks to inform investment decisions. This tool provides professional insights on stocks listed on NSE and BSE exchanges.

Instructions

$23c

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stock_idYesExample value: TCS

Implementation Reference

  • server.py:56-61 (registration)
    The tool is automatically registered via FastMCP.from_openapi based on the OpenAPI specification definition.
    mcp = FastMCP.from_openapi(
        openapi_spec=openapi_dict,
        client=client,
        name="indian_stock_exchange_api2",
        version=__version__
    )
Behavior1/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. '$23c' reveals nothing about side effects, return format, rate limits, or whether this is a read or write operation. The agent cannot determine what happens when this tool is invoked.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

While the description is short, it is not 'concise'—it is empty. Conciseness requires efficient communication of meaning. This description fails to communicate anything and therefore earns no credit for structure; every sentence must earn its place, and there are zero coherent sentences.

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

Completeness1/5

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

For a financial data tool with 15+ siblings and no annotations/output schema, the description should clarify the data source, recommendation types (buy/sell/hold), and timeframes. The content '$23c' represents a complete absence of necessary context.

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

Parameters3/5

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

Schema description coverage is 100% (1 parameter with description field), establishing a baseline of 3. The description itself adds no parameter information, but the schema provides an example value 'TCS' which, combined with the parameter name 'stock_id', minimally clarifies the expected input format.

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

Purpose1/5

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

The description '$23c' is gibberish and conveys no information about what the tool does. While the tool name 'analyst_recommendations' suggests it retrieves financial analyst recommendations, the description itself is completely opaque and fails to specify the verb, resource, or scope.

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

Usage Guidelines1/5

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

There is zero guidance on when to use this tool versus siblings like 'stock_forecasts' or 'get_stock_data_by_name'. The description provides no contextual boundaries or prerequisites for invocation.

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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