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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so 'Read-only' is largely redundant. However the description adds substantial context beyond annotations: the shape and provenance semantics of the topics field (source labels like 'Added by you', 'Only for', or a market name) and the Pro-plan gating on the mutating siblings.

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?

Usage guidance is front-loaded and the mutating alternatives are stated compactly. The long parenthetical unpacking the topics field is dense but every clause carries information; there is little padding.

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?

An output schema exists, so return values need not be documented, yet the description still previews the response's key contents. Combined with the trigger condition, the sibling routing, and the plan gating, an agent has everything needed to call this correctly.

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?

The single brandSlug parameter is fully documented in the schema (100% coverage), including the omit-to-use-workspace-default behavior. The description adds no parameter-level detail, so the baseline of 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 names a specific read operation (returning the brand's tracking configuration) and enumerates its contents: plan, markets, rivals, Custom topics, and notification switches. This distinguishes it clearly from siblings like parse_get_brand, parse_get_topic, and parse_what_changed.

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 states the trigger condition ('Use when the user asks what is being tracked or wants to change it') and explicitly routes mutation intent to parse_add_topic, parse_remove_topic, parse_correct_rival, and parse_set_notification, noting they are gated to the Pro plan. Both when-to-use and when-to-use-something-else are covered.

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