knowmind_stats
Retrieve current statistics of the tenant corpus, including counts of memories, edges, and chunks.
Instructions
Aktuelle Statistik des Tenant-Korpus: Memories, Edges, Chunks.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve current statistics of the tenant corpus, including counts of memories, edges, and chunks.
Aktuelle Statistik des Tenant-Korpus: Memories, Edges, Chunks.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds that the stats cover Memories, Edges, and Chunks, providing context beyond 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?
The description is a single sentence that immediately conveys the purpose and scope. No wasted words.
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 no parameters or output schema, the description explains what the tool does and what it covers. It could mention if the stats are real-time or aggregated, but it is sufficiently complete for a simple stat tool.
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?
There are no parameters, so schema coverage is 100%. The description does not need to add parameter meaning, and it sufficiently describes what the tool returns.
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 specifies 'Aktuelle Statistik des Tenant-Korpus: Memories, Edges, Chunks', which clearly states the verb (returns statistics), resource (tenant corpus), and scope (Memories, Edges, Chunks). This distinguishes it from sibling tools like knowmind_store_memory or knowmind_upload_document.
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 explicit when-to-use or alternatives are given. However, context signals (no parameters, readOnlyHint) imply it is for getting an overview. The sibling list provides indirect differentiation, but no direct guidance.
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/Schubeler-Consulting/knowmind'
If you have feedback or need assistance with the MCP directory API, please join our Discord server