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

Annotations already declare readOnly, idempotent, non-destructive, closed-world. The description adds genuinely useful behavior beyond that: indicators mix daily/monthly cadence so each reading carries its own date, and USD price is derived from AUD at the daily AUDUSD rate with a 1-2% deviation from global quotes. This data-provenance caveat is exactly the kind of context annotations cannot convey.

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?

A single well-structured paragraph, front-loaded with the indicator list before the routing guidance and the caveats. Dense but every sentence carries information; the caveat sentences are longest but they are the highest-value content.

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?

No output schema exists, so the description carries the burden of describing return values — and it does, listing the four indicators, their percentile zones, per-reading dates, and the AUD/USD price fields. For a zero-parameter read tool it is complete.

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 tool takes no parameters, so the baseline is 4. There is nothing to document, and the description correctly spends no space on inputs.

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 and enumerates exactly which four indicators are returned (MVRV Z-Score, Risk Metric, 200-week MA ROC, Pi Cycle Bottom ratio). It explicitly distinguishes itself from the sibling get_cycle_model_reading, so an agent can route without opening either schema.

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?

Gives an explicit when-to-use ('asks about a specific on-chain or valuation indicator or wants the components behind a cycle view') and names the alternative (get_cycle_model_reading) with the condition that selects it. Nothing is left to inference.

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