get_signal_accuracy

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Explains how signals are logged and checked after 7 days. Discloses return fields (accuracy %, avg return, breakdown). No annotations provided, so description carries burden well.

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?

Well-structured: purpose first, then mechanism, use cases, args, returns. Every sentence adds value, no redundancy.

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?

Covers purpose, mechanism, use cases, param details, and return values. Output schema exists, so return details are sufficient. All aspects addressed for an analysis 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?

Adds meaning to all 3 parameters (source filters with allowed values, symbol as NSE, days as look-back). Schema has 0% coverage, so description compensates effectively.

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?

Clearly states the tool shows accuracy of FinStack signals backed by real outcome data. Differentiates from siblings like get_signal_history by focusing on accuracy metrics.

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?

Provides explicit use cases (prove accuracy, compare sources, find best stocks). Lacks explicit when-not-to-use or alternatives, but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.