List scheduled catalysts (CPI, jobs, FOMC, GDP, large-cap earnings) in the next N days that move prediction-market prices BEFORE those markets resolve — a cross-event view across the whole calendar. Each entry is provenanced to its authoritative source (BLS, Fed, etc.). Use to find what scheduled events will reprice the prediction-market universe soon.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the tool lists scheduled catalysts, provides provenance to sources (BLS, Fed, etc.), and describes the effect on prediction-market prices. It does not mention output limits or pagination, but the behavior is well explained for a list operation.
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 two sentences with no extraneous information. It front-loads the core action and value proposition in the first sentence and adds provenance context in the second. Every word earns its place.
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 the tool's simplicity (one parameter, no output schema, no annotations), the description is nearly complete. It explains what the tool does, the parameter meaning, and what each entry includes (provenance). It could optionally detail the output structure further, but the current description is sufficient for a list tool.
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 defines a single 'days' parameter with type integer, default 30, and range. The description adds meaning by stating 'in the next N days,' clearly linking the parameter to the look-ahead window. This compensates for the 0% schema description coverage and provides essential context beyond the raw schema.
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 lists scheduled catalysts (CPI, jobs, FOMC, GDP, large-cap earnings) in the next N days, with the specific outcome of moving prediction-market prices before resolution. It distinguishes itself from sibling tools like list_events by emphasizing a cross-event calendar view and provenance to authoritative sources.
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 provides a clear use case ('Use to find what scheduled events will reprice the prediction-market universe soon') and implies the tool is for broad calendar discovery vs. single event or market-specific tools. However, it does not explicitly state when not to use it or compare to 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.
Each tool targets a distinct resource: events, markets, signals, or catalysts. Descriptions clearly separate 'get_event' (full event record) from 'get_market' (single market with trust metrics) and listing tools from detail fetchers. No ambiguity.
All tools follow a consistent 'verb_noun' pattern (get_event, get_market, get_signal, list_events, list_signals, list_upcoming_catalysts), with no mixing of conventions or inconsistent verbs.
With 6 tools, the set is well-scoped for the domain. Each tool serves a clear purpose without redundancy, and the count is appropriate for both detail and overview retrieval.
The server covers core retrieval needs for events, markets, signals, and catalysts. A minor gap is the lack of a direct list markets tool, but markets are accessible through events and get_market. Overall, the surface is reasonably complete for a read-only data service.
