web_search
Search the live web in Turkish or English and return a synthesized answer with sources. Powered by Alya's research engine.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Output language | |
| query | Yes | Search query |
Search the live web in Turkish or English and return a synthesized answer with sources. Powered by Alya's research engine.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Output language | |
| query | Yes | Search query |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions 'synthesized answer with sources' and 'powered by Alya's research engine', but does not disclose limitations, rate limits, or response structure. Adequate but not detailed.
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 concise sentences with no redundancy. Each sentence provides essential information: action and language scope, followed by the engine branding.
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?
With 2 simple parameters fully described in schema, the description covers core functionality. Lacks details on result format or pagination, which are not critical for a synthesized answer tool. Nearly complete.
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 covers 100% with clear descriptions for both parameters (query and lang). Description adds no extra meaning beyond the enum values for lang (tr/en), so baseline 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 the tool's purpose: 'Search the live web' with language constraints. It distinguishes from siblings by mentioning the live web and Turkish/English, setting it apart from other tools like agent_registry or alpaca_paper_status.
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 live web search in Turkish/English, but does not explicitly state when not to use or provide alternatives. However, no sibling tool overlaps, so the implied usage is clear.
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.