Live market regime: STABLE/VOLATILE + confidence + position_scalar ($0.005).
Validated variance detector: VOLATILE predicts ~2x forward volatility with ~90% persistence. Use for position sizing / risk gating, NOT direction.
| Name | Required | Description | Default |
|---|---|---|---|
| payment_signature | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses that it is a variance detector predicting forward volatility with persistence, and that it should not be used for direction. This is 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?
Extremely concise: two short paragraphs with essential information front-loaded. Every sentence adds value.
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?
The description explains the output structure but omits documentation for the payment_signature parameter. With one undocumented parameter and no output schema, it is adequate but incomplete.
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 input schema has one parameter 'payment_signature' with 0% description coverage. The description does not mention this parameter at all, leaving its purpose and usage unexplained.
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 returns the live market regime (STABLE/VOLATILE) with confidence and position_scalar. The name 'get_regime_current' distinguishes it from siblings like get_regime_history, but the description does not explicitly differentiate.
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 advises 'Use for position sizing / risk gating, NOT direction.' This provides clear when-to-use and when-not-to-use guidance, though it does not mention sibling tools for directional analysis.
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.