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

Annotations already cover readOnly/idempotent/no-open-world, and the description adds real value beyond them: the data source chain (provider history cache, else Web3Juice snapshots), that nothing is fetched, and how a missing result should be interpreted. Missing-data semantics are exactly the kind of disclosure annotations cannot carry.

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?

Two dense sentences, front-loaded with what the tool returns, then source behavior, then the edge-case rule. No filler and no repetition of the title.

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?

An output schema exists, so return fields need not be re-explained, yet the description still previews them for selection purposes. Combined with the source and null-history semantics, an agent has everything needed to call and interpret this tool correctly.

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 the description must compensate, and it does for windowDays by enumerating the three allowed values and the default, matching the schema's const-based anyOf. poolId is left uncharacterized (format, where to obtain it), which keeps this below a 5.

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?

States a specific verb+resource ('APY trend for one pool') and the output shape (median, low, high, latest, dated samples), which cleanly separates it from get_pool's current-state read. It never names a sibling explicitly, so differentiation is implied through 'history/trend' rather than stated.

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?

Explains the selection axis (7/30/90-day window with 30 as default) and adds a critical interpretation rule: 'No history means unknown, not zero.' It does not state when to prefer this over search_pools/compare_pools history-style queries, so it stops short of full when/when-not guidance.

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