[Global Equities Screener] Screen Philippine Stock Exchange (PSE) — PSEi components and broader market.
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 discloses that it screens the PSEi and broader market, adding context beyond annotations (readOnlyHint, openWorldHint). However, it does not explain data freshness, real-time vs delayed, or any limitations. The behavioral context is slightly enriched but not comprehensively.
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 brief (two lines plus a list of args) with no fluff. It front-loads the purpose and then details parameters. Slightly informal structure but efficient. Could be more structured with clearer formatting.
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 no output schema, the description should explain return format or expected results. It does not, leaving a gap. For a low-complexity tool (2 optional params), it is adequate but not fully complete for an agent to understand what it will receive.
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%, but the tool-level description explains 'criteria' as a filter dict with examples (sector, market cap) and 'limit' as max rows. This adds essential meaning that the bare schema lacks. It compensates well for the absence of schema descriptions.
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 Philippine Stock Exchange (PSE) and mentions PSEi components and broader market, distinguishing it from sibling screeners for other exchanges. However, 'screen' is a bit vague; it could be more specific about the action (e.g., filter/find stocks).
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?
No explicit guidelines on when to use this tool versus alternatives. The name implies Philippines-specific screening, but there is no comparison to other global-equities-screener siblings or any 'when not to use' guidance. The usefulness must be inferred from the name alone.
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.