Latest Korean brokerage equity research across all covered companies, newest first — company and KRX ticker, target price, rating, brokerage, analyst, and a one-line English summary of each report. Facts and summaries only; the report PDF stays with its publisher and source_url links back to it. Optional ?limit=20 (max 50). Costs $0.02 in USDC per call, settled via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max reports (default 20, max 50) |
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 full burden and handles it well. It discloses the output ordering, the fact that only facts and summaries are returned, that the PDF stays with the publisher, that source_url links back to the report, and the exact cost and settlement method.
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 dense but not bloated; every clause contributes scope, return fields, behavioral caveats, or cost. The sentence listing fields is a bit long, but it remains readable and front-loads the core purpose before the caveats and cost.
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 simple one-parameter list tool with no output schema, the description covers the return fields, ordering, link behavior, and cost. It does not specify pagination beyond the limit, but the tool is simple enough that nothing essential is missing for a correct invocation.
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 schema already documents the only parameter, limit, with a description and max value. The tool description restates this as 'Optional ?limit=20 (max 50)', adding only the default value and query-string form. Since schema coverage is 100%, a baseline of 3 is appropriate.
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 identifies the resource: latest Korean brokerage equity research across all covered companies, ordered newest first. It enumerates the exact fields returned, which distinguishes it from ticker-specific or consensus siblings by scope and ordering.
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 'across all covered companies, newest first' establishes a clear context for when to use this tool: to get a broad, chronological feed of the latest research. It does not explicitly name alternatives or state when not to use it, but the all-companies scope makes the intended use evident.
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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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.