tickscope-mcp

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get_ticker

Retrieve a current price snapshot for any symbol, including bid/ask, 24h high/low, volume, and change. Starts a live WebSocket watch to provide fresher data on subsequent calls.

Instructions

Get the current price snapshot for a symbol (the primary quote tool).

Returns last/bid/ask, 24h high/low/volume, 24h change %, plus freshness fields source (websocket|rest), age_ms and timestamp. The first (cold) call answers via REST and starts a live WebSocket watch, so subsequent calls return fresher websocket-sourced data.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "get_ticker"
  }
}

Input Schema

Name	Required	Description	Default
`symbol`	Yes
`exchange`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 6, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It goes beyond the obvious by explaining the cold-call REST behavior and subsequent WebSocket freshness, plus the meaning of the 'source' field. It doesn't cover error handling or rate limits, but the provided context is valuable and not expected by default.

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 concise and front-loaded, opening with the main purpose in the first sentence. It then efficiently lists return fields and explains the freshness/WebSocket behavior without redundancy. Every sentence carries useful information, achieving maximum economy.

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 and the presence of an output schema, the description covers key aspects: return fields, cold/warm behavior, and the freshness fields. It falls short only in not addressing the 'exchange' parameter, which is a small omission relative to the overall completeness.

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?

The schema has 0% description coverage, so the description must compensate for parameter meaning. While 'symbol' is self-evident, the optional 'exchange' parameter is not elaborated at all—the description never mentions what 'exchange' is for or how it affects results. This leaves a significant gap in parameter understanding.

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 clearly states the tool gets a current price snapshot for a symbol and explicitly positions it as 'the primary quote tool.' It distinguishes itself from siblings like get_recent_trades and get_ohlcv by focusing on the quote/ticker use case with specific return fields (bid/ask, 24h data).

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 phrase 'primary quote tool' provides clear context for when to use it (for current price snapshots), but it does not explicitly mention when not to use it or name alternative tools for other data needs. It implies usage without exclusions, which fits the 'clear context, no exclusions' level.

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