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get_technical_indicators

Read-onlyIdempotent

Compute technical indicators (RSI, MACD, EMA, SMA, Bollinger Bands, ATR, ADX, Stochastic, OBV, VWAP, CCI, MFI, Williams %R) for a crypto futures symbol at a specific timeframe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTrading pair symbol, e.g. BTCUSDT
intervalNoCandle interval/timeframe1h
indicatorsNoTechnical indicators to compute

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
priceNoLatest close, or null when no candles are stored
symbolNo
intervalNo
indicatorsNoRequested indicators keyed by name; shape differs per indicator

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds that it computes indicators but does not mention potential rate limits, data availability, or that it might use historical candles. No contradiction.

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 sentence that is concise and front-loaded with the verb 'Compute'. It lists the main indicators and the key inputs (symbol, timeframe), providing no superfluous information. Every word adds value.

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

Completeness4/5

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

Given the tool's moderate complexity (13 indicators, output schema present), the description is adequate but could mention that the agent can request any subset via the 'indicators' parameter. However, the output schema likely clarifies the return format, so this is not a major gap. Slightly incomplete regarding when to use it relative to get_candles.

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?

Schema coverage is 100%, providing descriptions for all three parameters. The description adds no new parameter information, but the schema already documents symbol, interval, and indicators thoroughly, including enums and defaults. Therefore, the description adds little but does not detract.

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

Purpose4/5

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

The description clearly states the tool computes technical indicators for a crypto futures symbol at a specific timeframe, listing the supported indicators. It distinguishes itself from siblings like get_candles (which fetches raw candle data) and get_price (current price), though it does not explicitly name alternatives.

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 the tool is for computing indicators on historical price data, but does not state when to use it versus get_candles (which might be needed for raw data) or how it relates to other market data tools. No explicit guidance on prerequisites or alternatives.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools are clearly distinct, targeting different data categories (market data, signals, traders, account). Some potential overlap exists between get_price, get_candles, and get_market_stats, but their descriptions clarify the specific use cases. Overall, an agent can differentiate them reliably.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with the verb 'get' and a descriptive noun (e.g., get_candles, get_signals, get_trader_profile). This uniform naming makes it very predictable for an agent.

Tool Count5/5

With 15 tools, the count is within the ideal range for a domain-specific server. Each tool serves a distinct purpose related to market data, signals, and trader analytics, and none feel redundant or extraneous.

Completeness4/5

The tool set covers core read operations for market data, signals, traders, and account info, which aligns with the apparent purpose of a data-provider server. Minor gaps include lack of write operations (e.g., placing trades) or historical signal details beyond individual IDs, but these are not critical for a data-oriented service.