[Global Equities Screener] Screen Australian Securities Exchange (ASX) — ASX 200 + small-caps incl. mining juniors.
Args: criteria: filter dict (sector, market cap, 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?
The description adds context beyond the readOnlyHint and openWorldHint annotations by specifying the stock universe (ASX 200 + small-caps, mining juniors). However, it does not describe the return format, pagination, or any behavioral quirks like rate limits. For a screening tool, more detail on output would be beneficial.
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 extremely concise and front-loaded: the first sentence conveys the core purpose, and the second paragraph briefly lists arguments. Every word serves a purpose with no unnecessary fluff.
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?
The description covers the tool's purpose and parameter meanings, which is adequate for a simple screening tool. However, it lacks information about the output format or return values (no output schema). This could leave an agent uncertain about the result structure.
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?
With 0% schema description coverage, the description compensates by explaining 'criteria' as a filter dict with examples (sector, market cap, etc.) and 'limit' as max rows. This adds meaningful semantic guidance beyond the bare schema, though it could be more exhaustive.
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 the Australian Securities Exchange (ASX), specifically ASX 200 and small-caps including mining juniors. This distinguishes it from other exchange-specific screeners like screen_brazil_b3, making the purpose specific and unambiguous.
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 explicitly indicates the geographic scope (Australia ASX) and the type of stocks covered. This helps an agent choose this tool over alternatives like finance__screen_stocks or other exchange screeners. However, it does not provide explicit when-not-to-use guidance or mention specific 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.