Delete a memory or document by ID from Memwyre.
Args:
memory_id: The ID of the item (e.g., 'mem_1' or 'doc_5').
| Name | Required | Description | Default |
|---|---|---|---|
| memory_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that the tool deletes an item but does not mention that deletion is irreversible, whether special permissions are needed, or what side effects may occur on associated data.
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 short, front-loaded with the action and object, and contains no filler. Every sentence contributes useful information, and the parameter explanation is compact.
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 simple single-parameter tool, the description covers the core invocation details and examples. However, it lacks behavioral warnings about destructiveness and does not clarify how delete_memory differs from discard_memory, leaving some contextual gaps.
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 schema only defines memory_id as a string, while the description adds concrete meaning by explaining it is an item ID and giving format examples like 'mem_1' or 'doc_5'. This helps an agent form a valid argument despite the 0% schema description coverage.
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 action and target: 'Delete a memory or document by ID from Memwyre.' It is specific about the resource and operation, but it does not differentiate the tool from siblings such as discard_memory, which could be confused with deletion.
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 guidance about when to use this tool versus alternatives like discard_memory, update_memory, or save_memory. The description gives no context about prerequisites, situations suited for deletion, or cases where a sibling should be used.
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.
Most tools map cleanly to distinct operations such as semantic search, date search, inbox approval/discard, and tag listing. The main ambiguity is between save_memory and upsert_memory, both of which can create memories with similar arguments; get_memory/get_document and delete_memory/discard_memory are also distinguishable mainly by ID prefix or inbox state.
The names are consistently lowercase snake_case and verb-first, which makes the set fairly predictable. Minor deviations include search_by_date breaking the verb_noun pattern, get_inbox/get_all_tags acting as list operations while list_memories uses 'list', and upsert_memory being an unusual verb.
At 13 tools, the surface is well-scoped for a memory/document vault: create, upsert, update, retrieve, list, semantic and date search, tags, and inbox workflow are all represented without excessive granularity or redundant filler.
The toolset covers the core memory lifecycle well, including save, upsert, update, get, search, list, delete, and inbox approval/discard. Minor gaps remain: update_memory only accepts mem_ IDs, so documents found via search have no document-specific update path, and workspace management is only handled through optional name strings.