Live quote for one Upbit KRW market by ticker symbol (e.g. BTC, ETH, XRP): price, 24h change, 24h high/low, 24h traded value in KRW. Costs $0.005 in USDC per call, settled via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Coin ticker symbol, e.g. BTC |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the disclosure burden. It discloses a key behavioral trait: each call costs $0.005 in USDC settled via x402. It also states what data will be returned. It does not cover invalid-ticker behavior, but for a read-only quote tool the important transparency is present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two tight sentences: the first front-loads the tool's purpose, scope, and output fields; the second provides the critical cost and settlement detail. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description covers the returned fields, market scope, and pricing—enough for an agent to invoke it correctly. Minor gaps are the lack of guidance for discovering valid tickers and behavior on invalid symbols, but these do not block correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter is already fully documented in the schema ('Coin ticker symbol, e.g. BTC') with 100% coverage. The description adds examples and market context, but no new semantic constraints, formatting rules, or enumeration, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Live quote') and a precise resource ('one Upbit KRW market by ticker symbol'), with concrete examples and the exact data fields returned. This clearly distinguishes it from siblings like crypto_krw_markets, which lists markets, and fx_usdkrw, which covers USD/KRW FX rates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes the context: use this tool for a single Upbit KRW market quote identified by ticker. However, it does not explicitly state when not to use it or point to crypto_krw_markets as the way to discover valid tickers, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a fairly distinct resource and action: market snapshots vs. single tickers, current vs. historical vs. statistical kimchi premium, headlines vs. English headlines, and per-company vs. latest vs. consensus research. The main ambiguity is between preview_research and preview_research_coverage, and korea_market_snapshot overlaps with several individual data tools, but descriptions clarify the granularity and combined-briefing intent.
All tool names use a consistent lowercase snake_case convention with clear domain prefixes like crypto_krw_, kimchi_premium_, news_, preview_, and research_. The English variant news_headlines_en and the aggregate korea_market_snapshot still follow the same readable naming style.
Fifteen tools sit at the upper boundary of a well-scoped set, but each serves a clear purpose in a paid API that exposes market data, kimchi analytics, news, research, and free previews. The set is slightly broad because it spans two domains and includes aggregate and preview endpoints, but the count is defensible.
Core workflows are well covered: current and historical market data, USD/KRW, kimchi premium current/history/stats, translated news, per-company research, latest research, and consensus. Gaps are minor and mostly outside the stated scope, such as full-text news articles, historical crypto OHLC, or advanced research filtering by sector or brokerage.