Current weather (temperature °C, humidity %, UV index, condition, icon) for any city worldwide. Powered by Velene's miroir engine (OpenMeteo + Grok-fused). Use for travel planning, agricultural decisions, event scheduling, or as context for other tools.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | City name (e.g. 'Istanbul', 'Tokyo', 'New York') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses read-only nature ('current weather') and data source (Velene's miroir engine), but lacks details on update frequency, accuracy, or rate limits. Adequate but not thorough.
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?
Two sentences with no wasted words. Front-loaded with key output fields and use cases, making it easy to scan.
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 weather tool with one required parameter and no output schema, the description fully informs the agent of return fields and appropriate contexts. No gaps remain.
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 coverage is 100% with a clear city parameter description. Description adds value by stating 'any city worldwide', confirming global scope beyond schema examples, which aids parameter interpretation.
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?
Description clearly states the tool provides current weather data (temperature, humidity, UV index, condition, icon) for any city worldwide. Distinguishes from siblings as no other weather tools exist.
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?
Explicitly lists use cases (travel planning, agricultural decisions, event scheduling) and suggests use as context for other tools. No explicit when-not-to-use, but sibling analysis shows no alternatives, so partial guidance is acceptable.
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.
Most tools have distinct purposes and clear descriptions, but there is some potential confusion among the four Polymarket-related tools (categorize, edge, signals, top_traders) and among the multiple 'alya_' prefixed tools that query different data sources.
Naming patterns are mixed: some tools use 'alya_' prefix, others use action-based names like 'batch_calibrate' or 'image_gen', and YouTube tools all start with 'youtube_'. The inconsistency in prefixes and verb styles makes the set less predictable.
32 tools is high for an MCP server, and they span a wide, unrelated set of domains (Polymarket, YouTube, gemology, weather, earthquakes, health, celebrity, etc.), making the surface feel bloated and unfocused.
Each domain has incomplete coverage: Polymarket lacks trade execution, YouTube automation depends on external OAuth, health tools only offer diagnosis and drug interactions without follow-up, and other domains have minimal tooling. The server feels like a collection of one-off features rather than a coherent surface.