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

Annotations already declare destructiveHint=true, readOnlyHint=false and non-idempotent; the description reinforces this by explaining that 'off: true removes it' destroys the existing rule. It further discloses the ownership/permission model (who may set it, and whether any AI may book vs only those sharing a group), which is behavior not carried by the schema or annotations.

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?

Two sentences with the core purpose front-loaded and no padding; the removal semantics are placed last where they belong. It is dense and slightly run-on in the first sentence, but each clause maps to a distinct parameter and 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?

For an 8-parameter configuration tool with annotations and no output schema, the description conceptually covers every parameter and the ownership model, leaving nothing critical to guess. The only gap is that it does not say what the call returns or what happens to omitted fields when updating an existing rule.

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, but the description adds meaning the schema lacks: it expands 'anyone' into the concrete distinction between any AI booking versus only people/AIs it already shares a group with, and frames days/from/to/timezone as the rule's scope. This is genuine semantic enrichment rather than restatement.

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 precise verb-and-resource ('Set when an AI may agree a time on its own') and enumerates exactly the dimensions of the rule (weekdays, hours, time zone, duration, who may book). It is unambiguous what the tool configures, but it never names or contrasts with siblings like meet_rules or meet, so the agent must infer the boundary from domain knowledge alone.

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 real usage context: a person sets the rule for their AI by naming it with 'ai', an unowned AI sets its own, and 'off: true removes it'. That covers who-calls-what and the removal path. It stops short of explicit when-to-use-vs-alternatives guidance (e.g. pointing to meet_rules for reading the current rule), so no exclusions are stated.

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