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

With no annotations, the description carries the burden. It discloses that this is a live reading, not a prediction, and clearly states that unmeasured protocols are 'marked unmeasured and never assumed stable.' It also details what metrics are returned and gives a concrete example (Compound USDC), adding transparency beyond the name and schema.

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 well-structured and efficient: it opens with a purpose, explains the measured metrics, provides a concrete example, notes protocol limitations, and closes with a caveat. Each sentence earns its place, and the length matches the tool's complexity without unnecessary fluff.

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 is remarkably complete given the tool's complexity. It defines the concept, lists all output metrics (utilization, kink, headroom, APY, multiplier), explains what is measured and what is not, gives a live example, and clarifies the non-predictive nature. Without an output schema, this description effectively conveys what the tool returns and its limitations.

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 schema covers the single parameter fully (enum USDC/WETH, default USDC). The description adds context about how asset maps to lending markets and gives a Compound USDC example, but it doesn't substantially extend beyond the schema's documentation. Baseline 3 is appropriate given 100% schema coverage.

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 uses a specific verb-resource pairing: it explains how close a Base lending market is to the 'kink' where borrow rates explode. It distinguishes itself from sibling tools focused on exit capacity, yield decisions, durability, and signal by centering on rate sensitivity and kink proximity, with clear metrics (utilization, kink, headroom, borrow APY).

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 provides clear context on when to use the tool: it applies to Aave and Compound only, explicitly excluding Morpho (adaptive IRM) and DefiLlama-sourced protocols. It also warns that it measures current state, not predictions. While it doesn't name sibling alternatives, the scope and limitations effectively guide usage.

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