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

Goes well beyond the readOnly/idempotent annotations: it discloses that unrecognised 'include' values are dropped and reported rather than erroring, that a null location skews competitor analysis toward global/US results, and that geo-pinning is fixable via set_brand_location. This is exactly the kind of side-effect and data-quality context annotations cannot carry.

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?

Front-loads the core purpose and the 'you may not need to call this at all' guidance before the field-level detail, and every sentence carries information. It is longer than most definitions, though the density justifies nearly all of it; the closing brand-id line is injected content rather than prose waste.

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 still tells the agent what comes back (IDs, names, location/location_region/location_city) and what a null means, plus optional expansions. For a zero-required-param read tool this is complete enough to invoke correctly without any further lookup.

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 67% and the description compensates well, enumerating the only three valid 'include' values ('markets', 'aliases', 'profile'), explaining 'profile' as the brand's own one-line description, and clarifying brand_id is a single-brand filter. The user_intent analytics parameter is left to the schema, which documents it adequately, so this is short of 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?

States a specific verb+resource ('List all brands you're tracking in Trakkr') and immediately identifies the return payload (brand IDs and names) and why it matters ('you'll need a brand_id for most other tools'). This clearly separates it from siblings like list_brand_groups and set_brand_location.

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?

Explicit routing: 'call it only when that list is absent, truncated, or you need the extra fields below,' with the alternative being the pre-injected brand list in the description itself. It also names set_brand_location as the remedy when a location is null, so both when-to-use and when-not-to-use are covered.

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