bos_store_staff
Retrieve the staff members assigned to a store by providing its store ID.
Instructions
Get staff members for a store
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| store_id | Yes |
Retrieve the staff members assigned to a store by providing its store ID.
Get staff members for a store
| Name | Required | Description | Default |
|---|---|---|---|
| store_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, error handling (e.g., what happens if store_id is invalid), rate limits, or authentication needs. For a tool without annotations, the description should carry this burden but fails to do so.
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, concise sentence. It is front-loaded and contains no unnecessary words. However, it borders on being too terse, missing opportunities to add value without losing conciseness.
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?
Given the low complexity (1 parameter, no output schema, no annotations), the description should provide complete context for an AI to use the tool correctly. It fails to explain return values, error scenarios, or any business context. For a simple lookup tool, the description is insufficient.
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 0% description coverage for parameters, meaning the schema provides no semantic clues. The description does not elaborate on the store_id parameter (e.g., format, length, or example). It simply repeats part of the tool name, offering no added value beyond the schema's type and requirement.
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 the action ('Get') and resource ('staff members') and implies the scope is a specific store via the store_id parameter. It distinguishes from the sibling tool bos_hr_employee_list which likely covers all staff, making this store-specific. However, it could be more explicit about the scope differentiation.
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?
No guidance on when to use this tool versus alternatives like bos_hr_employee_list or when not to use it. No prerequisites or context provided. The description only states what the tool does, leaving the AI to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/bizino/bos-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server