search-inventorySearches active inventory in the authenticated workspace and can identify low-stock items without exposing internal cost or margin fields.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum items to return. | |
| query | No | Inventory name, SKU, or description. | |
| active | No | Filter by active state; defaults to true. | |
| low_stock | No | Only items at or below minimum quantity. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only and non-destructive, and the description adds useful behavioral context: workspace scoping and a data-exposure guarantee that cost/margin fields are not returned. It does not describe pagination or sort order, but that is not critical for this simple search tool.
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?
The description is a single front-loaded sentence that moves from verb and object to constraints and data restrictions. Every clause earns its place with no filler.
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 tool with four optional, fully documented parameters, the description covers purpose, scope, and an important output restriction. There is no output schema, but the explicit exclusion of cost/margin fields gives agents a meaningful picture of what results include and omit.
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 input schema has 100% parameter description coverage, so the description does not need to repeat parameter detail. It aligns with the active and low_stock parameters but adds no semantics beyond what the schema already provides.
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 uses a specific verb and resource ('Searches active inventory'), adds a distinct use case ('identify low-stock items'), and signals a data-boundary behavior ('without exposing internal cost or margin fields'). This is enough to separate it from sibling search tools even without naming an alternative.
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 provides clear context: use this for active inventory in the authenticated workspace, and specifically for low-stock identification. It does not name alternatives or explicit when-not conditions, but the scope is sufficiently clear among the sibling tools.
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.
Tool families are organized by resource and action (get/search/preview/reports), so most tools have a distinct purpose. A few near-overlaps exist—customer-service-requests vs search-service-requests and the many campaign preview/search tools—but descriptions generally clarify boundaries.
The set consistently uses kebab-case with recognizable prefixes like get-, search-, preview-, and reports-, making intent predictable. A few noun-phrase tools (complaint-recall-risk, customer-service-requests, operations-parts, jobs-today) break the verb-first pattern, but they remain readable and grouped.
45 tools is well beyond the 25+ threshold and creates a large surface for agents to navigate, even though the domain is broad. Many tools are narrow read-only variations (e.g., five preview-campaign tools, three reports-* tools), which inflates the count without adding fundamentally new capabilities.
As a read-only/insights server, the surface covers customers, jobs, quotes, invoices, leads, locations, service requests, reviews, campaigns, operations, and reporting with both search and detail access. Minor gaps exist—no get-* for campaign types or social drafts—but these align with the intentionally bounded, safe-read model.