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

Annotations already declare readOnly=true, idempotent=true, non-destructive, and closed-world, so the safety profile is covered. The description still adds value beyond that: aggregates describe the whole included set, and the recomputed median is explicitly not saved, which is a meaningful side-effect disclosure. It says nothing about permissions, rate limits, or pagination beyond the cursor hint.

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 trigger condition is front-loaded and the parameter notes are compactly backticked rather than buried. The middle sentence listing returned fields is dense but each item earns its place given there is no output schema; only the enum restatement for `platform` is redundant.

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?

This is a non-trivial analytical read with no output schema, and the description compensates fully: it describes the returned baseline components and the reel fields (id, published_at, views, read timestamp), plus pagination semantics. An agent has everything needed to decide to call it and interpret the result.

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 0%, so the description carries the burden and largely does: it clarifies that `handle` accepts @name, bare name, or profile link (well beyond the bare string type), and gives the 1-50 range for `limit` that the schema omits, plus how to page with `cursor`. The `platform` note merely restates the enum values, which keeps it from a 5.

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 a specific resource and scope — the views baseline ('usual views') for one author on one platform — and enumerates exactly what is returned: the x_factor rule, stored median, recomputed median, sample count, and the underlying reels. That is clearly distinguishable from siblings like get_author_reels or analysis_card, which return reels or analyses rather than the baseline definition.

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?

It opens with an explicit trigger ('Use this when you need to know what usual views means...') and adds real exclusions: it only covers already-tracked authors and never adds an author, refreshes metrics, or persists the recomputed value. It stops short of naming a sibling tool as the alternative for those other jobs, so it does not reach the top mark.

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