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

Annotations already declare readOnly, non-destructive, open-world and non-idempotent behavior, so the safety bar is low. The description adds genuinely useful context beyond that: IEX historical data as the source, the exact statistical output set, and access/rate-limit facts (small daily allowance without key, 100 calls/month tiers, $0.02 per call over x402). It does not address latency, data staleness, or result ordering.

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 opening sentence is a long run-on enumerating every returned statistic, which front-loads the substance but is hard to parse. The closing payment-tier and 'not investment advice' sentences occupy a meaningful share of the text relative to operational guidance.

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?

With no output schema, the description does an effective job of describing return contents (medians, percentiles, max adverse move, up/down counts, suggested stop). However, for a statistical tool it omits things an agent would want to set expectations: what happens when fewer than N releases exist, whether the 'suggested stop' is always computed, and the granularity/format of horizon arrays.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds a little meaning, notably that symbols may be ETF proxies for the futures roots and that the `price` parameter exists to express moves and the stop width in points, but it does not explain how `lookback` interacts with sparse release history.

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 states very specifically what is computed: percentage and point moves in ES/NQ/RTY/ZN at +5/+15/+30/+60 min after CPI, NFP, FOMC, PPI, retail sales, GDP and PCE releases, plus aggregate statistics. An agent knows exactly the resource and calculation. No sibling is named (e.g. event_gate), so the distinction from surrounding tools must be inferred.

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 title's parenthetical '(what happened last time)' hints at a historical-analysis use case, but there is no explicit when-to-use, when-not, or pointer to an alternative tool. The only conditional guidance is about access (key vs. no key), not about when the tool is the right choice.

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