Returns active memory totals, synaptic weight distribution, and Mushroom Body health statistics to assess associative memory state and diagnose learning issues.
Returns total active memories, synaptic weight distribution, and health statistics of the Mushroom Body.
| 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?
No annotations are provided, so the description carries the full behavioral burden. The verb 'Returns' implies a non-mutating read, and the enumerated outputs give the agent a sense of the result shape, but nothing is said about cost, side effects, or state changes (contrasted with the sibling reset_memory, which clearly mutates).
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 that front-loads the return payload. No filler, no restatement of the tool name.
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 no parameters, no output schema, and no annotations, the description is the only source of information about results, and it names the three returned categories. It is nearly complete for such a simple tool, though the meaning of 'Mushroom Body' and 'synaptic weight distribution' remains domain jargon an agent may not resolve.
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 the baseline of 4 applies. The description correctly reflects that this is a parameterless snapshot call, leaving nothing ambiguous on the input side.
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 clear verb ('Returns') and enumerates the specific payload: total active memories, synaptic weight distribution, and health statistics. This distinguishes it from siblings like query_associative_memory and remember_code_outcome. It stops short of explicitly naming which sibling it replaces, so a 4 rather than 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?
No statement of when this tool should be used versus check_code_reflex, query_associative_memory, or reset_memory. The diagnostic character of the tool is only inferable from the listed return values; there is no explicit triggering condition or exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.