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

Annotations already declare readOnly/idempotent/non-destructive and openWorld=false, so safety is covered. The description adds real behavioral value beyond that: results are capped at 15, ordered with subscriptions first and ranked by market presence, and an uncovered market returns an explanatory message naming the nearest covered markets.

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 dense sentences that are well front-loaded: the core listing behavior leads, filters follow, fallback behavior closes. The long inline parenthetical lists are information-rich rather than wasteful, though they make the second sentence somewhat run-on.

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 a read-only search with annotations covering safety, 100% schema coverage, and no output schema, the description covers ranking, result cap, filter semantics, and the empty-market fallback. It stops short of describing the returned brand fields, which is the only remaining gap with no output schema to back it up.

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: it supplies the FULL category enumeration (subscription, gift_card, streaming, music, sports, ai, productivity, audiobooks, anime, shopping, food, gaming, travel) which the schema truncates to 'such as', and restates the market formats. It adds marginal but genuine value over the schema.

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 ('List') and resource ('subscription brands ... through Fleek in a market') with the ranking and result cap spelled out. The scoping ('a business could offer its users in a market') makes it unmistakably distinct from the single-record get_brand sibling without naming it.

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?

Gives clear context on the three filter axes (market, category, free-text brand) so an agent knows how to narrow a catalogue listing. It does not, however, name when NOT to use it or point to alternatives like get_brand or shortlist_for_programme, so exclusions are missing.

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