Verified POTUS statement events, nothing newer than 15 minutes ($0.25).
RETURNS: the same complete payload as the live tier, including the full verification and market-attribution blocks. GUARANTEED MAX STALENESS: 900 seconds. PRICE: $0.25 USDC. Appropriate for attribution and research rather than reaction. NOT A PREDICTION: verified observation, no edge claim.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No | ||
| payment_signature | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: guaranteed max staleness of 900 seconds, price of $0.25 USDC, and that it returns the same payload as the live tier including verification and market-attribution blocks. This provides sufficient behavioral context.
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 compact and front-loaded with essential info: purpose, staleness, price. It then details return payload and usage. However, it could be more structured with parameter explanations.
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 complexity (3 params, no output schema, no annotations), the description covers purpose and behavior but omits parameter semantics, making it incomplete for an agent to use without additional context.
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% and the description does not explain any of the three parameters (limit, since, payment_signature). An agent has no guidance on how to use these inputs, which is a critical gap for correct invocation.
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 it provides 'Verified POTUS statement events' with a maximum staleness of 15 minutes. It distinguishes from siblings by specifying the time delay and price, but lacks explicit comparison to similar tools like sygnl47_events_1m or sygnl47_events_live.
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 guides usage by stating 'Appropriate for attribution and research rather than reaction' and clarifies it is 'verified observation, no edge claim.' This implies appropriate contexts, though it does not explicitly list excluded scenarios.
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 has a distinct purpose, with clear differentiation between SYGNL/47 event tiers (live, 1m, 15m, archive), subscription management, and auxiliary tools like backtesting and regime detection. No overlapping functionality.
Most tools follow a descriptive underscore pattern, with 'sygnl47_' prefix for event and subscription tools, and 'get_' for data retrieval. Some variation in verb prefixes (audit, check, estimate) but overall predictable and readable.
21 tools is slightly high but justified by the tiered data access model for SYGNL/47 events and supporting infrastructure. The count covers core functionality without being excessive.
The tool set covers the stated domain well: event monitoring at different recency, backtesting, regime detection, and subscription management. Minor gaps like historical pricing data are not central to the server's focus.