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

No annotations, so description carries burden. Discloses free nature and no payment, but omits side effects or confirmation. Adequate for simple input.

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?

Single, well-structured sentence with key info front-loaded. No waste.

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?

Completeness is good for a simple feedback tool: explains purpose, parameters, usage context. Lacks return value info but acceptable without output schema.

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?

With 0% schema description coverage, description adds meaning: score range 1-10, pros/cons as text. However, doesn't mention that score is required while others optional.

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 it's a feedback/rating tool for after trading on signals. Distinguishes from sibling tools like evaluate_symbol or scan_* by focusing on user-submitted rating.

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 context ('after trading on our signals') but no explicit when-not-to-use or alternative tools. Lacks exclusions.

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