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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds crucial context beyond annotations: the paid nature ($1.00 per call from credit balance) and that results are grounded in live on-chain and market data. No contradiction with annotations.

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 three sentences: statement of purpose, return type, and cost/alternatives. Every sentence earns its place, front-loads the primary purpose, and avoids redundancy with annotations or schema.

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?

For an open-ended analysis tool with no output schema, the description covers the key aspects: what it does, when to use, what it returns ('written analysis'), and cost. It could have included an example prompt but is otherwise complete for selection and invocation.

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 schema description coverage at 100% and only one parameter (`prompt`) described as 'The question or analysis request, in plain language', the baseline is 3. The description adds usage context but does not enrich the parameter semantics beyond the schema's own description.

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 'Open-ended crypto and DeFi analysis from Einstein's full research stack' with a specific verb (analysis) and resource (research stack). It distinguishes itself from sibling tools by emphasizing 'open-ended' and 'spans several domains', making it a clear fallback for general questions.

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?

Explicit usage guidance is provided: 'use this when no more specific tool fits, or when the question spans several domains.' It also points to free alternatives via 'see list_einstein_capabilities', giving clear direction on when not to use this tool.

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