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indicator_ema

Calculate the Exponential Moving Average (EMA) for any crypto trading pair to gauge trend direction by weighting recent prices more heavily for accurate analysis.

Instructions

Calculate the Exponential Moving Average (EMA) - weights recent prices more heavily for trend analysis

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of OHLCV data points to fetch
periodNoPeriod length
symbolYesTrading pair, e.g., 'BTC/USDT'
timeframeNoTimeframe, e.g., '1m', '1h', '1d'1h
Behavior2/5

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

No annotations are provided, so the description must carry the transparency burden. It only explains the mathematical concept of EMA and does not disclose operational behaviors such as fetching OHLCV data, handling of the limit/timeframe parameters, or return format. This is a significant gap for a tool that likely performs data retrieval and computation.

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 a single, front-loaded sentence that efficiently states the tool's verb and resource while adding a useful explanatory note. There is no filler or redundant information, making it highly concise and well-structured.

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

Completeness3/5

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

The tool is a simple calculation, but given the absence of annotations and output schema, the description should offer more operational context. It does not mention that the tool retrieves OHLCV data based on symbol and timeframe, nor does it give any hint of the return structure. The well-documented schema compensates somewhat, but the description remains minimal for the tool's complexity.

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?

The input schema already covers all four parameters with descriptions (100% coverage), so the baseline is 3. The description adds no extra meaning to the parameters themselves; it only references the weighting concept, which is tangential to how the limit, period, symbol, and timeframe work.

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 uses the specific verb 'Calculate' and names the resource 'Exponential Moving Average (EMA)', which is clear and unambiguous. The added phrase 'weights recent prices more heavily' provides a distinguishing characteristic versus other moving averages, effectively differentiating it from sibling indicator tools.

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 description implies use for trend analysis ('for trend analysis') but provides no explicit comparisons or exclusions relative to other indicators. While this provides a basic context, it does not say when to choose EMA over SMA, MACD, or other alternatives, which are abundant in the sibling list.

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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