Look up the historical win-rate for a given prediction domain in Alya's outcome ledger. Returns resolved count, wins, losses, win_rate, and last_resolved_at.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain prefix, e.g. 'freelance', 'prediction-market', 'equities'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must carry the burden. It implies a read operation by saying 'look up' and 'returns', but does not explicitly state that it is read-only, require authorization, or have side effects. The description is adequate but could be more explicit about safety and access constraints.
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 a single, well-structured sentence that immediately conveys the tool's purpose and return output. Every word adds value, with no redundant or vague phrasing.
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?
Despite lacking an output schema, the description explicitly lists all returned fields (resolved count, wins, losses, win_rate, last_resolved_at). For a simple lookup tool, this is nearly complete; missing details like data types or error handling are acceptable given the low complexity.
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?
The schema covers 100% of parameters with a description, but the description adds concrete examples ('freelance', 'prediction-market', 'equities') that illustrate valid values. This adds significant meaning beyond the schema's generic 'Domain prefix' text.
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 uses the specific verb 'look up' and clearly identifies the resource as 'historical win-rate for a given prediction domain in Alya's outcome ledger'. It enumerates the returned fields, making the tool's function distinct from sibling tools which handle different domains (e.g., celebrity info, trending demands). No ambiguity.
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 guidance is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description only states what the tool does without contextualizing its appropriate use relative to sibling tools.
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.