check_memory_serviceCheck health status and connectivity of the persistent memory backend service.
Returns: Dict with health status ('healthy' or error details).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds that the tool returns a dict with health status or error details, which is useful but does not go deeper into connectivity nuances or failure modes. No contradiction with 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 extremely concise: one sentence for purpose, one for return value. It is front-loaded and contains no filler or repetition.
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 no-parameter health check tool with rich annotations and an output schema, the description covers the essential purpose and return shape. An agent can select and invoke it correctly without additional context.
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, so the description is not required to explain parameter behavior. Baseline 4 applies since there is nothing missing in parameter documentation.
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 tool checks health status and connectivity of the persistent memory backend service. This distinguishes it from sibling tools like recall or remember, which operate on memory content rather than service health.
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 'health status and connectivity' makes the intended use obvious: diagnose whether the backend is reachable and operational. It does not explicitly list exclusions or alternatives, but the context is clear given the sibling tools are all memory operations rather than health checks.
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.
Each tool has a clearly distinct purpose: remember stores, recall searches semantically, recent_memories lists by recency, and check_memory_service monitors health. There is no meaningful overlap between the retrieval tools because one is query-driven and the other is time-driven.
Naming is inconsistent: remember and recall are bare verbs, recent_memories is a noun phrase, and check_memory_service uses a verb_noun pattern. A more consistent set would use e.g. remember, recall, list_recent_memories, check_service_health.
Four tools is well-scoped for a persistent memory service. Each tool covers a distinct, necessary operation without redundancy or bloat.
The core create/read and health-check operations are present, but there is no update or delete tool for managing stored memories. This creates a notable lifecycle gap, especially for correcting or removing outdated facts.