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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is settled; the description adds that the output is personalized ('this person's state: on or off, configured or not, the level') and localized ('in the person's language'), plus a deep link, which are behavioral facts not in the annotations. It does not mention error behavior for an invalid insert id, which is the main remaining gap.

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 core claim is front-loaded in the first clause, and the long enumeration of returned fields is justified because no output schema exists. However, it is a single run-on sentence with a nested parenthetical and a very long comma list, which is harder to scan than a short structured breakdown would be.

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 and one enum parameter, the description carries the full burden of describing returns and does so exhaustively: static metadata, configuration schema plus current values, and per-user state including a deep link. Nothing an agent needs to call this and interpret the result is missing.

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% and the single parameter already carries an enum and the note 'The insert id (from list_inserts)'. The description repeats the same provenance hint without adding format, casing, or fallback guidance, so the schema does the heavy lifting and 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?

The description states a specific verb+resource ('Everything about ONE insert') and immediately disambiguates scope by defining an insert ('an optional extra page of the briefing') and pointing to the sibling that enumerates them ('the list is in list_inserts'). It also enumerates the returned facets (usage, frequency, placement, data sources, AI levels, configuration fields, personal state), so an agent knows exactly what it gets.

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 gives two explicit use cases: 'explain an insert' and 'prepare configure_insert', naming the primary alternative sibling and its relationship. It also implicitly routes ID discovery to list_inserts. It lacks an explicit 'do not use this to change settings' exclusion, but the forward pointer to configure_insert covers the main confusion risk.

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