Retrieve all AnythingLLM workspaces with slug, name, chat model, chat mode, and topN settings. Use it to inspect available workspaces before managing chats, documents, or embeddings.
List all AnythingLLM workspaces (slug, name, chatModel, chatMode, topN).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a safe read by saying 'List' and discloses which fields come back, but says nothing about pagination, ordering, result size limits, or whether all workspaces are always returned. Adequate but not rich.
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?
A single tight sentence with the verb and scope front-loaded and no filler. The parenthetical field list is compact and earns its place by previewing the response shape.
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 zero parameters, no annotations, and no output schema, the description does the useful work of enumerating returned fields so the agent knows what it gets. It stops short of covering pagination or ordering behavior for a list operation.
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 takes zero parameters, so there is nothing to disambiguate; per the rubric a 0-param tool baselines at 4. The description's field list is informative but does not map to any input arguments.
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?
States a specific verb (List) and resource (all AnythingLLM workspaces), and even enumerates the fields returned (slug, name, chatModel, chatMode, topN). The 'all' scope cleanly distinguishes it from the sibling get_workspace, which is singular.
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 phrase 'List all' implies discovery/enumeration usage, but the description never says when to prefer this over get_workspace or when a slug lookup is more appropriate. No prerequisites or exclusions are stated, so context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.