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memory_review_queue

Review pending memory maintenance proposals grouped by entity, with evidence. Overdue proposals expire automatically when listed.

Instructions

List pending maintenance proposals, grouped by entity, with evidence (§6.3).

Each group carries the subject entity and its proposals; each proposal includes its parsed payload (the evidence) so a reviewer sees what would change. Not fully read-only: overdue proposals lazily expire (are marked expired) as a side effect of listing. Returns a JSON string (the grouped list). Use memory_review_decide to act on a listed proposal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoFilter to one proposal kind: 'dedup_near' | 'summarize' | 'evict'. Omit (null) for all kinds.
limitNoMaximum number of proposals returned.
namespaceYesIsolation key for one memory store. Each namespace is a separate local SQLite file under LM_DATA_ROOT (default ~/.lean_memory); namespaces never see each other's facts. Use one per agent, project, or user whose memory must stay separate. Created on first access.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description proactively discloses the non-read-only nature: 'Not fully read-only: overdue proposals lazily expire (are marked expired) as a side effect of listing.' It also clarifies the return type (JSON string). This goes beyond the annotations, which only note readOnlyHint=false, and provides essential context without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the primary purpose, then adds critical side-effect information and a pointer to the next tool. Every sentence contributes value and there is no redundancy or filler, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and well-documented parameters, the description covers all necessary aspects: what it lists, how the data is structured, the side effect, the output type, and the relationship to sibling tools. It is complete for this list-with-side-effect utility.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and each parameter (kind, limit, namespace) already has a clear description in the schema. The tool description adds no additional parameter-level detail beyond the context of what the listing returns, so it meets the baseline but does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'List pending maintenance proposals, grouped by entity, with evidence.' It clearly distinguishes from siblings by mentioning the follow-up tool memory_review_decide for acting on proposals, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for use (reviewing pending proposals before deciding) and explicitly directs to memory_review_decide for the next step, which acts as an alternative. However, it does not explicitly state when not to use this tool or mention other alternatives like memory_maintenance_status, so it falls short of full explicit usage guidance.

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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