Retrieve department IDs from configured org-structure metadata, enabling alert filtering by group. Useful for targeting specific agents and computers.
List departments configured in Teramind - org-structure metadata used to group agents/computers. Department IDs from this response are usable as filters on teramind_list_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure, but it only reveals that department IDs appear in the response. It does not state that the operation is read-only/safe, whether results are paginated, what fields a department record contains, or what happens when no departments exist. The description adds the filter-usage hint but leaves the behavior largely implicit.
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 tight sentences with no filler: the first states the action and domain meaning, the second delivers a concrete downstream use case. Every clause earns its place, and the most important information (what the tool lists) is front-loaded.
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 parameterless list tool with no output schema, the description explains the resource, its purpose, and a realistic calling context (generating filter IDs for alerts). The main remaining gap is the response shape beyond 'department IDs' and any pagination or auth considerations, but the description is otherwise sufficient for an agent to invoke it correctly.
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 tool has zero parameters and the schema is empty, so there is nothing for the description to document. Per the baseline for parameterless tools, a score of 4 applies; the description needs to convey no parameter semantics because none exist.
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?
Description uses a specific verb-resource pair ('List departments configured in Teramind') and clarifies what departments are (org-structure metadata for grouping agents/computers). It also differentiates from the sibling teramind_get_department by framing this as the list variant, and gives the response a distinct purpose via the filter hint for teramind_list_alerts.
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?
Provides clear context: the tool's output (department IDs) is meant to be consumed as filter values by teramind_list_alerts, which tells an agent when this list is useful. It does not explicitly state exclusions or alternate choices (e.g., when to prefer teramind_get_department), so it stops short of full when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.