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

Annotations already cover the safety profile (readOnly, idempotent, openWorld). Beyond that, the description discloses two things an agent could not infer: provisional=true means detected live without calibration, and forward returns are RAW LONG P&L deliberately not signed by absorption side, so a negative number on a sell-absorption day is not a losing signal. That is exactly the interpretive context 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?

Front-loaded with the core resource, then caveats, which is the right order. Sentences are dense but each carries information; the trailing 'Pro.' token is unexplained waste and the middle sentence is long, costing a point.

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?

Covers what is returned (events with percentile, side, context quartile), the default date behavior, and the interpretation traps. With no output schema present, the description carries the return-shape burden and does so adequately for an agent to read results 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?

Schema description coverage is 100%, so the schema already documents date default, days range, limit and ticker format. The description restates the defaults ('date (default latest)', trailing per-day history) but adds no syntax or constraint detail beyond the schema. 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 a specific resource and scope: one ticker's absorption events for a date plus trailing per-day direction history. The 'One ticker's' scoping implicitly separates it from the market-wide absorption_market sibling, though that sibling is never named. An agent can tell what it returns without opening the 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 a concrete use case in quotes ('is NVDA being absorbed, and is that unusual?'), which frames the when-to-use condition clearly. It stops short of naming an alternative tool or stating when not to use it (e.g. for market-wide absorption, use absorption_market).

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