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yalcin

ta-lib-mcp

by yalcin

talib_compute_indicator

Read-onlyIdempotent

Compute technical indicators (e.g., SMA, RSI, MACD) from aligned numeric arrays. Provide indicator name, input data, and optional parameters to obtain output values.

Instructions

Compute a TA-Lib indicator from aligned numeric inputs.

Computes the requested indicator over the provided numeric arrays and returns the result. All input arrays must have the same length.

Args: indicator: TA-Lib indicator name (e.g., "SMA", "RSI", "MACD"). inputs: Aligned numeric input arrays (e.g., {"close": [1.0, 2.0, 3.0]}). parameters: Optional indicator parameters (e.g., {"timeperiod": 14}).

Returns: Computation result with indicator name, length, parameters, and output values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indicatorYes
inputsYes
parametersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Annotations already indicate readOnly, non-destructive, idempotent. The description adds critical behavioral details: inputs must be aligned and same length, and returns structured result. No contradictions.

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 well-structured with clear sections for args and returns, and is not overly verbose. Slightly more text than necessary, but still effective.

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?

Despite no output schema shown, the description explains return format. Given the complexity (3 params, nested objects), and absence of schema coverage, the description is complete enough for correct invocation.

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 coverage is 0%, but the description fully compensates by describing each parameter with types and examples: indicator as string with examples, inputs as object of number arrays with example, parameters as optional object with example. This exceeds requirements.

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 starts with 'Compute a TA-Lib indicator from aligned numeric inputs', which clearly states the verb (compute) and resource (TA-Lib indicator). It further distinguishes from siblings like 'talib_list_indicators' by focusing on computation.

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 description implies usage for indicator computation, but does not explicitly state when not to use it or mention alternatives. However, the context of sibling tools makes the use case clear.

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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