Get list of pending memories in the Memwyre Inbox.
Args:
workspace_name: Optional name of the workspace directory to filter inbox items.
| Name | Required | Description | Default |
|---|---|---|---|
| workspace_name | No |
| 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 full burden. It indicates a read operation ('Get list') but does not disclose side effects, permission requirements, behavior when inbox is empty, or pagination. The term 'pending' implies state but no detail on how items become pending or what actions affect them.
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?
Very concise, using two lines with an Args section. Every word earns its place, and the main action is front-loaded. Could be slightly more structured with headings, but for a single-parameter tool it's appropriately sized.
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?
Tool is simple (1 optional param) and has an output schema, so description needn't detail return values. However, with no annotations, it lacks behavioral context (e.g., safety, side effects). It covers the main purpose and filter but leaves open questions about what 'pending' means and how the list is ordered. Adequate but not thorough.
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?
Schema coverage is 0%, but the description compensates by explaining workspace_name: 'Optional name of the workspace directory to filter inbox items.' This adds meaning beyond the bare schema (string/null, default null), clarifying it is a filter and optional. However, it doesn't specify behavior when omitted or provided, but the core semantics are covered.
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?
Description clearly states the verb (Get), resource (list of pending memories), and specific scope (Memwyre Inbox). It distinguishes from broad siblings like list_memories by specifying 'pending memories in the Inbox', though it doesn't explicitly name alternatives. Slight ambiguity remains about what 'pending' means, but purpose is understandable.
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 guidance on when to use this tool versus siblings like list_memories or get_memory. It does not mention prerequisites, timing, or exclusions. The only hint is the unique 'Inbox' context, which is implied but not stated as a decision rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.