Retrieve all stored user preferences, habits, and facts from personal memory. Returns a summary of saved context so AI assistants can recall personal information across sessions.
List all entries in personal memory. Returns summary of stored user preferences, habits, and facts.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden, but it is a read-only, parameterless listing so there is little risk to disclose. It does add useful context about what is returned (preferences, habits, facts), though it says nothing about ordering, volume, or pagination.
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 short sentences, front-loaded with the core action and followed by what is returned. Nothing is padded, though the second sentence is arguably redundant with the first.
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 zero-parameter read tool with no output schema, the description gives enough to call it correctly and sketches the return contents. It could note ordering or result size, but nothing essential to invocation is missing.
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 per the rubric the baseline is 4. The description introduces no parameter confusion and the empty schema makes semantics moot.
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 and resource ("List all entries in personal memory") and clarifies scope as the full personal memory store. It distinguishes itself implicitly from get_context (singular retrieval) but never names or contrasts with that sibling, so it falls short of a 5.
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?
There is no explicit when-to-use guidance. The phrase "List all entries" weakly implies bulk retrieval versus the singular get_context, but the description never states when to choose this over get_context or the workflow_* siblings, leaving the agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.