Free, date-stamped archive-depth check for one 6-digit KRX ticker. Shows report and brokerage counts, not report content or consensus.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | 6-digit KRX code, e.g. 005930 |
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, the description carries the full burden of behavioral disclosure. It adds useful context by saying the check is free, date-stamped, archive-depth, and limited to counts rather than content. However, it does not disclose whether authentication is needed, what the response shape looks like, or any limits/side effects. For a read-only preview tool this is acceptable but not comprehensive.
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 a single, tightly packed sentence with no filler. It front-loads the key facts (free, date-stamped, archive-depth, single ticker) and immediately clarifies the output scope and exclusions. 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 tool with one parameter, no output schema, and no nested objects, the description is largely complete: it states the input, what the output contains, and what it does not contain. A minor gap is the lack of any mention of response shape or error behavior, but that is less critical for such a simple preview check.
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 single parameter as a 6-digit KRX code with an example, so schema coverage is 100%. The description reinforces this by mentioning 'one 6-digit KRX ticker' but adds no additional semantic detail beyond what the schema provides. The 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 states a specific action (preview/check), a specific resource (archive-depth for one 6-digit KRX ticker), and the output (report and brokerage counts). It also usefully excludes report content and consensus, clarifying what the tool is not. However, it does not explicitly differentiate itself from the likely sibling preview_research_coverage, which may have an overlapping scope.
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 implies when to use the tool: for a quick, free, date-stamped count of reports and brokerages for a single ticker. 'Not report content or consensus' hints at what this tool is not for, but it does not explicitly name alternatives or state when to prefer another sibling tool. The guidance is present but left mostly to inference.
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.