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ofsazib

dse-mcp

by ofsazib

Compute Indicators

compute_indicators

Calculate MACD, RSI, 50/200-day SMAs, and Bollinger Bands for a symbol using the last year of daily candles. Returns null values when trading history is too short, such as for recent IPOs.

Instructions

Compute technical indicators for a symbol over the last year of day-end candles. Values are null when history is too short (e.g. recent IPOs).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
macdNo
rsi_14No
sma_50No
symbolYes
sma_200No
bollingerNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It usefully discloses that values are null when history is too short, e.g. for recent IPOs, and sets expectations around the day-end candle data scope. This adds meaningful behavior beyond the bare schema.

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 two sentences with no filler. The primary purpose and time scope are front-loaded, and the edge-case note about null values is concise and valuable.

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 that an output schema exists, the description does not need to explain return values. It covers the essential context: symbol, lookback period, candle frequency, and a relevant edge case. It is slightly incomplete in not offering any alternative routing guidance, but it is otherwise sufficient for a compute tool.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for missing parameter documentation, but it does not. It only references 'a symbol' and 'technical indicators' without explaining the boolean toggles, their defaults, or how parameters affect computation. The parameter names are self-explanatory to some degree, but the low coverage is not compensated.

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 a specific action ('Compute'), a specific resource ('technical indicators for a symbol'), and a precise scope ('over the last year of day-end candles'). It is easily distinguishable from data-retrieval siblings like get_price_history or get_quote, though it does not explicitly contrast with technical_summary.

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 implied usage is clear: call this when you need computed technical indicators for a symbol. However, it provides no explicit guidance on when to prefer this over technical_summary or when not to use it, and it names no alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.