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

Annotations already cover the read-only/idempotent safety profile, and the description adds genuinely useful context beyond them: a null value means no data rather than an error, and an api:read scope is required. It does not mention rate limits, pagination, or limits on timeseries length, so it is not fully complete.

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 front-loaded paragraph that opens with what is returned, then modes, symbol format, null semantics, and auth — the highest-value information comes first. It is dense but nearly every clause carries operational meaning; the only soft spot is the parenthetical feature-family list.

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 7-parameter tool with no output schema, the description covers the essential call-shaping facts: mode semantics, identifier format with a cross-tool source of truth, null-vs-error behavior, and required scope. An agent could invoke it correctly without further clarification.

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 only 43% schema coverage the description does real work: it explains all three mode values, defines instrument_id format (bare Hyperliquid symbols or dex-prefixed HIP-3 symbols, matching scan_markets output), and ties universe_id to outlier universes like hl_top50. It leaves start/end as only implicitly timeseries-scoped, without restating the ISO 8601 format or range inclusivity.

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 resource — pre-computed quantitative features — and enumerates the families it covers (returns, realized vol, z-scores, funding, OI deltas), and explicitly delegates the full enumeration to the schema. This clearly distinguishes it from raw-data siblings like get_bars, get_prices, and get_market_regime.

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 per-mode routing guidance: snapshot for the latest value, timeseries for history, outliers for top-N extreme instruments in a universe. It also tells the agent to source instrument ids from scan_markets. It stops short of stating when to prefer a sibling over this tool (e.g. versus get_bars for raw series).

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