[Global Equities Screener] Screen Korea's KOSPI exchange (Samsung, SK Hynix, Hyundai, LG, etc.).
Args: criteria: filter dict (industry, market cap, P/E, etc.) limit: max rows to return
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| criteria | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and openWorldHint. The description adds the specific exchange context but does not disclose further behavioral traits such as data freshness, rate limits, pagination, or output format. It is consistent with annotations but adds minimal value beyond them.
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 very concise: a purpose line and two parameter lines. Every sentence is useful, and it is front-loaded with the main action. No unnecessary words.
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?
Given the tool's role as a stock screener with no output schema, the description explains parameters but misses critical details: what the output looks like, how to formulate complex criteria (e.g., operators, available fields), and any data source limitations. The openWorldHint suggests dynamic results but lacks specificity.
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?
Schema description coverage is 0%, so the description compensates by explaining 'criteria' as a filter dict with examples (industry, market cap, P/E) and 'limit' as max rows. This adds meaningful context beyond the schema's bare types, though it could list more specific filter keys.
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 the tool screens Korea's KOSPI exchange, naming example companies (Samsung, SK Hynix, etc.) and using a specific verb+resource. Among many sibling screeners for different exchanges, this differentiates by exchange and country.
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 usage for KOSPI stocks via the exchange name and example companies, but does not explicitly state when to use this tool versus alternatives (e.g., other exchange screeners). No when-not-to-use guidance or mention of alternatives.
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.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.