One-call Korea briefing: dual-basis kimchi premium + top Upbit KRW markets + USD/KRW + latest economy headlines translated to English. Everything needed for a Korea market read in a single paid request. Costs $0.08 in USDC per call, settled via x402.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 present, the description carries the full burden, and it delivers meaningful disclosures: the call is paid (costs $0.08 in USDC, settled via x402) and the headlines are translated to English. This goes beyond what the empty schema provides. It stops short of a 5 because it does not mention data freshness, caching, latency, or what happens if an upstream source fails.
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?
Three sentences with no waste: the value proposition is front-loaded, the content list is structured with a colon and plus-separated items, and the cost/payment detail is isolated in the final sentence. Every sentence 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 0-parameter aggregator with no output schema, the description is complete enough: it enumerates all content components and discloses the cost and settlement mechanism. Minor gaps remain around the response format and data freshness, but these are not critical for an agent deciding to invoke this tool.
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 tool has zero parameters and the schema already documents that completely, so the baseline of 4 applies. The description correctly focuses on what the tool returns rather than parameters, and there is nothing missing for an agent to invoke it correctly.
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 clearly states what the tool delivers: a composite Korea briefing with specific enumerated components (dual-basis kimchi premium, top Upbit KRW markets, USD/KRW, translated economy headlines). It implicitly differentiates from the granular sibling tools by framing itself as the 'one-call' aggregator, though it never names a sibling or states a concrete verb.
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 phrase 'Everything needed for a Korea market read in a single paid request' gives clear context for when to choose this tool: when the agent wants a complete Korea overview without issuing multiple calls to siblings. The explicit cost and settlement disclosure ($0.08 USDC via x402) also signals a paid-versus-free trade-off against the sibling tools, though no alternative names or when-not-to-use exclusions are given.
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.