check_domain_availabilityCheck domain availability for a brand name. Returns status (available, parked, commercially used, or taken) for each TLD, plus .com variations (e.g., getbrand.com, brandhq.com).
| Name | Required | Description | Default |
|---|---|---|---|
| tlds | No | TLDs to check. Defaults to com/ai/app/io/co when omitted. | |
| brand_name | Yes | Brand name to check (e.g., "Moonlight Coffee") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only and non-destructive behavior. The description adds value by specifying the return statuses and .com variations, but doesn't disclose additional behavioral details like rate limits or data freshness.
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 clear, front-loaded sentences with no redundancy. Every word contributes meaning.
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 explains return statuses and .com variations, which is substantial. It could optionally mention that results are per-TLD, but the coverage is solid for a simple read-only tool.
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 description coverage is 100%, so parameters are well-documented. The description adds context about .com variations corresponding to the brand_name parameter, but doesn't go beyond what the schema already explains for tlds.
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 clearly states it checks domain availability for a brand name and lists return statuses. It is distinct from most trademark tools due to domain focus, but does not explicitly differentiate from the sibling check_brand_availability.
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?
Usage is implied: it's for domain availability checks. However, no explicit guidance is given on when to use this tool versus alternatives like check_brand_availability or web_research, and no exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly defined scopes, but several search/count tools overlap (search_trademarks, phonetic_search, run_knockout_search, get_similar_marks) and owner/firm analytics tools have similar boundaries. Descriptions help differentiate them, but the large set increases the chance of misselection.
All tool names follow a consistent lowercase snake_case verb_noun pattern (get_, search_, run_, analyze_, etc.). The only minor deviation is web_research, which is noun_verb, but it remains perfectly readable and consistent with the overall style.
61 tools is extreme for any server, far exceeding the 50+ threshold. Even for a comprehensive trademark platform, this number overwhelms agents with selection complexity and makes the toolset difficult to navigate.
Several tools launch asynchronous processes and instruct users to call status tools (get_prosecution_history_status, get_ttab_proceeding_analysis_status, get_office_action_research_status) that are not present in the toolset. Additionally, search_trademarks and phonetic_search reference list_marks_containing_term, which is also missing. These critical gaps cause agent failures when following the described workflows.