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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavior: a ~60,000 character cap, truncation of long arrays to their most recent rows, the fact that the cut is reported under `windowed`, and that scalars/summary fields are never dropped. That 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?

Three sentences, zero filler. The purpose and path examples come first, then filtering semantics, then the truncation caveat — a well front-loaded structure that puts the most decision-relevant facts early.

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 carries the return-value burden and does so reasonably: it describes arrays, scalars, summary fields, and the `windowed` marker. It stops short of describing the overall response envelope or where summary fields live, leaving a small gap for a tool whose output shape matters.

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 coverage is 100%, so the schema baseline is 3, but the description adds meaning beyond it by specifying that `since`/`until` filter on the row's `date` (or `year`) field and that the cap interacts with the `tail` parameter's default behavior. It stops short of documenting formats the schema already states.

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 gives a specific verb and resource ('Read one published dataset (the JSON behind a chart)') and grounds it with four concrete path examples, so an agent knows exactly what this returns. It never names the sibling that produces those paths (search_charts), so it does not fully differentiate itself from the discovery tools.

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?

Usage is only implied: you supply a dataset path and read it back. There is no explicit statement of when to prefer this over get_latest or annual_returns, and no prerequisite guidance beyond the schema's note that paths come from search_charts.

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