explain_memoryExplains why a memory exists or matched a query whenever the user asks why something was saved there or why it was retrieved.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Natural-language question or search text. | |
| memory_id | Yes | Exact XMemo memory reference shown by search or recall. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / additionalPropertiesAdded value: +falseInput schema / properties / include_embeddingRemoved value: -{
- "default": false,
- "description": "Whether to include embedding/vector metadata in the returned explanation.",
- "title": "Include Embedding",
- "type": "boolean"
-}Input schema / properties / output_jsonRemoved value: -{
- "default": false,
- "description": "Return a machine-readable JSON response instead of a human-readable summary.",
- "title": "Output Json",
- "type": "boolean"
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and side effects. The description adds the behavioral context of explaining memory rationale, but does not disclose additional traits such as output format or limitations; the output schema covers return structure. This is adequate given the strong annotation coverage.
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, front-loaded sentence that clearly states the action and condition. There is no redundancy or filler, making it highly concise and well-structured.
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?
The tool is simple with robust annotations and an output schema. The description covers purpose and usage, the schema covers parameters, and the annotations cover safety. A minor gap is the lack of an explicit prerequisite that memory_id must come from a prior search/recall, but the schema property description already states that, so the overall context is complete.
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?
Both parameters (memory_id and query) have descriptive schema entries providing full coverage at 100%. The tool description does not add extra parameter-level detail, so the baseline score of 3 is appropriate.
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's function with a specific verb ('Explains') and resource ('why a memory exists or matched a query'). It distinguishes itself from sibling search/recall tools by focusing on the reasoning behind memory behavior rather than listing or retrieving memories.
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 description gives an explicit usage condition: 'whenever the user asks why something was saved there or why it was retrieved.' This clearly signals when to invoke, though it does not explicitly name alternative tools or exclusions, which would have made it a 5.
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.
Multiple memory-retrieval tools (recall, search_memory, recall_context, read_memory, memory_overview) have overlapping purposes; detailed descriptions help but an agent could easily pick the wrong one. Similarly, ledger/open_ledger and todo/open_todo_board split text vs UI interaction, and forget overlaps with todo delete_all and ledger deletion.
Most tools follow a verb_noun snake_case pattern (read_memory, update_memory, search_memory, open_ledger). However, several tools use bare nouns or verbs (forget, ledger, project, todo, recall, remember) and memory_overview is noun_noun, creating inconsistent conventions.
19 tools is on the heavy side for the apparent scope, and the surface includes several pairs that duplicate the same domain in text vs UI form (ledger/open_ledger, todo/open_todo_board). Still, the count is defensible given the combined memory, project, TODO, and ledger coverage.
Memory has full lifecycle coverage (remember, read, search/recall, update, forget, restore), and TODO and Ledger workflows are largely complete. Minor gaps exist—no explicit project deletion and no pure text list-projects tool—but core workflows do not dead-end.