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calvernaz

Alpha Vantage MCP Server

by calvernaz

bbands

Calculate Bollinger Bands to analyze stock price volatility and identify potential overbought or oversold conditions using Alpha Vantage market data.

Instructions

Fetch bollinger bands

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
intervalYes
monthNo
time_periodYes
series_typeYes
nbdevupYes
nbdevdnYes
datatypeNo
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Fetch' suggests a read-only operation, but it doesn't specify data sources, rate limits, authentication needs, error conditions, or what the output looks like. For a tool with 8 parameters and no output schema, this is a significant gap in transparency.

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 extremely concise with just two words, 'Fetch bollinger bands', which is front-loaded and wastes no space. While it may be under-specified, it earns full marks for brevity and clarity within its limited scope.

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?

Given the complexity (8 parameters, 6 required, no schema descriptions, no annotations, no output schema), the description is completely inadequate. It doesn't explain the tool's behavior, parameter meanings, output format, or usage context. For a data-fetching tool with multiple inputs, this leaves the agent with insufficient information to use it correctly.

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?

The schema description coverage is 0%, meaning none of the 8 parameters are documented in the schema. The description 'Fetch bollinger bands' adds no information about what parameters like 'symbol', 'interval', 'time_period', 'series_type', 'nbdevup', 'nbdevdn', 'month', or 'datatype' mean or how to use them. It fails to compensate for the lack of schema documentation.

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

Purpose3/5

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

The description 'Fetch bollinger bands' clearly states the action (fetch) and resource (bollinger bands), providing a basic purpose. However, it lacks specificity about what bollinger bands are or what data source is used, and doesn't differentiate from sibling tools like 'sma' or 'ema' which are also technical indicators. It's not tautological but remains somewhat vague.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for technical indicators (e.g., 'sma', 'rsi', 'macd'), there's no indication of when bollinger bands are appropriate, what prerequisites exist, or any exclusions. Usage is implied only by the tool name, not explained.

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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