Retrieve the full, unabridged content of a specific memory by its ID from Memwyre.
Use this when `search_memwyre` returns a snippet with `[ID: mem_XXX]` and you need to read the complete original document, report, or note.
Args:
memory_id: The ID of the memory (e.g., 'mem_73').
| 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?
With no annotations provided, the description carries the disclosure burden. It clearly conveys a read-only retrieval by using 'Retrieve' and emphasizes 'full, unabridged content' as opposed to a snippet. It does not explicitly state that no modifications are made or how missing IDs are handled, but for a simple get-by-ID tool the core behavior is sufficiently transparent.
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 main purpose is stated in the first sentence, the usage condition follows immediately, and the parameter line is minimal. Every sentence earns its place; there is no filler or redundant boilerplate.
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 one-parameter get-by-ID tool with an output schema, the description supplies everything needed: how to obtain the ID (from search_memwyre snippets), the fact that it returns the full content, and the parameter format. The reliance on an output schema to explain the return shape is appropriate.
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 input schema provides only the name and type for memory_id, with no description (0% coverage). The description compensates by defining it as 'The ID of the memory' and supplying a concrete example ('mem_73'), and the usage text explains where such IDs come from ([ID: mem_XXX] in search results). This is adequate for a single parameter, though the semantic definition is mostly a restatement of the parameter name.
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 states the specific action ('Retrieve the full, unabridged content'), the resource ('a specific memory by its ID from Memwyre'), and distinguishes it from search_memwyre, which only returns snippets. This leaves no ambiguity about what the tool returns or how it differs from sibling tools.
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?
It gives an explicit trigger condition: use when search_memwyre returns a snippet with [ID: mem_XXX] and you need the complete original document/report/note. This names the upstream tool and the exact condition under which get_memory is the right choice.
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.