Add a recall watch pattern for this API key. Same websearch syntax as search_product_recalls (AND, OR, -exclude, quoted phrases). Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| weight | No | optional weight 0-8, default 4 | |
| pattern | Yes | websearch pattern: unquoted words are AND, OR is or, -term excludes, quoted phrases match as a unit |
| Name | Required | Description | Default |
|---|---|---|---|
| weight | Yes | ||
| pattern | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey mutability and idempotency, so the description is not burdened with those. It adds useful context by requiring an API key and scoping the pattern to that key, and it references the search syntax behavior. No contradiction with 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 no wasted words. The core action is front-loaded, the syntax guidance is compact, and the auth requirement is stated directly.
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 simple two-parameter tool with an output schema, the description covers scope, syntax, and auth requirements. It could more explicitly connect to lifecycle siblings like remove_watch_pattern, but nothing essential is missing.
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 description does not need to explain parameters. It reinforces the pattern syntax but adds no new meaning beyond the schema's pattern description and does not mention the weight parameter.
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 specific action and resource: 'Add a recall watch pattern', and clarifies scope with 'for this API key'. This clearly distinguishes the tool from siblings like remove_watch_pattern and list_watch_patterns.
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?
The description gives clear context: it creates a watch pattern and references the websearch syntax used by search_product_recalls. It does not explicitly state when not to use it or name alternatives, so it stops short of a 5.
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 distinct roles, and the descriptions explicitly separate product lookup from recall search. However, the multiple recall search entry points (by query, UPC, image, and identifier) overlap enough that an agent could pick the wrong one without carefully reading the details.
Tool names consistently follow a snake_case verb_noun pattern such as add_, list_, remove_, search_, get_, create_, revoke_, and mark_. The single-word signup is the only minor deviation, but it does not undermine the overall naming system.
At 19 tools, the set is in the borderline-heavy range. The count is justified by the multiple subdomains like API key management, inventory, watch patterns, notifications, and recall searching, but it still feels slightly above the ideal well-scoped tool surface.
Core recall search, product lookup, inventory tracking, watch pattern management, notifications, and API key lifecycle are all covered well. Minor gaps exist such as no way to update a watch pattern or view account usage limits, but agents can generally work around them.