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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the null-per-bucket rule for brands without mentions in a bucket, the default 20 / max 50 cap, and the ordering semantics that explain how values are produced.

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?

Four tight sentences, front-loaded with what the metric is before covering scoping and edge cases. No filler, no restatement of the tool name, and each sentence earns its place.

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 the work of explaining the returned shape (a per-bucket value per brand series, null when no mentions), which is what an agent needs. The interval parameter is documented only in the schema, and the description never mentions the temporal bucketing that is central to a time-series tool, which is a modest gap.

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 baseline is 3; the description still adds meaning the schema does not, by explaining how brand_id, segments, and top_n interact (mutually exclusive scoping modes and fallback behavior). Default and max values for top_n are restated, which is mildly redundant with the schema.

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 names the specific metric ('average position of each tracked brand ... per bucket') and defines what position means (brand order in an answer, lower = more prominent, 1 = first named). This clearly separates it from the other time-series siblings by resource. It stops short of explicitly contrasting itself with get-visibility-time-series-tool or get-share-of-voice-time-series-tool, which is the only thing keeping it from a 5.

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 scoping sentence ('Scope by `brand_id` for one line; by `segments` ...; otherwise top `top_n`') is genuinely useful mode-selection guidance. However, it never says when to reach for this tool over the sibling time-series tools (sentiment, share of voice, visibility), so routing guidance is implied at best.

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