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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: completed UTC daily closes only, signal contents, and a per-call x402/USDC price on Base mainnet.

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 front-loaded with the regime summary, then supplies precise signal details, freshness, and pricing. Every sentence adds relevant information without repetition or filler.

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 a one-parameter, read-only signal tool with no output schema, the description covers signal categories, data freshness, and cost. It does not specify exact response fields, but gives enough context for an agent to select and invoke it 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?

There is one parameter, top_n, with 100% schema description coverage; the schema already documents its default, bounds, and purpose. The description's 'point-in-time top-N' adds interpretive context but no syntax or range details beyond the schema, so the baseline 3 applies.

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?

Names the specific dataset and enumerates its components: BTC/ETH trend vs 20/50-day MAs, breadth, breakout watchlist, and R1 gate/entry signals. This distinguishes it implicitly from backtest/validation siblings, though it does not explicitly name alternatives.

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 'Daily crypto market regime' framing and 'Completed UTC daily closes only' constraint imply a daily overview use case and freshness boundary. However, there is no explicit when-to-use/when-not guidance or named alternative such as backtest, universe_snapshot, or token_check.

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