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n24q02m

Mnemo - Persistent AI Memory

by n24q02m

memory

Destructive

Store and search persistent AI memories to recall user preferences, decisions, and facts. Use actions like add, update, and delete to maintain information across sessions.

Instructions

[DEPRECATED — use the granular tools (add_memory, search_memory, ...) instead; this composite tool will be removed in a future release]

Legacy dispatcher for backward compatibility. Use specialized tools (add_memory, search_memory, etc.) instead.

Persistent memory store. Actions: add|search|list|update|delete|export|import|stats|restore|archived|consolidate.

ACTION GUIDE — when to use each:

  • add: Store NEW information. Requires 'content'. Use when saving preferences, decisions, facts for the first time. Example: action='add', content='User prefers dark mode', category='preference', tags=['ui']

  • search: Find existing memories by natural language query. Requires 'query'. Use BEFORE add to avoid duplicates. Example: action='search', query='dark mode preference'

  • update: Modify an EXISTING memory by ID. Requires 'memory_id' (from search/list results). Use when a fact changes. Example: action='update', memory_id='abc123', content='User now prefers light mode'

  • list: Browse all memories, optionally filtered by category. No query needed.

  • delete: Remove a memory by ID. Requires 'memory_id'.

  • stats: Show database statistics (total memories, categories, embedding status).

  • export: Export all memories to JSONL format.

  • import: Import memories from JSONL data. Requires 'data'.

  • archived: List archived memories. Optionally filter by limit.

  • restore: Restore an archived memory by ID. Requires 'memory_id'.

  • consolidate: Summarize and consolidate similar memories in a category using LLM. Requires 'category'.

WORKFLOW: search -> not found? -> add. Found outdated? -> update (with memory_id from results). PROACTIVE: save user preferences, decisions, corrections, project conventions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
autoNo
dataNo
modeNomerge
nameNo
tagsNo
textNo
as_ofNo
depthNo
limitNo
queryNo
sinceNo
untilNo
actionYes
sourceNo
contentNo
categoryNo
entity_idNo
memory_idNo
importanceNo
context_typeNoconversation
min_importanceNo
include_archivedNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already set destructiveHint=true, but the description adds rich behavioral context: requirements per action (e.g., 'Requires content' for add), side effects (archived, restore), and the fact that it is a persistent store. No contradiction with annotations.

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

Conciseness3/5

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

The description is structured with sections (deprecation notice, action guide, workflow) and front-loaded with the deprecation warning. However, it is verbose and contains some repetition (e.g., 'Use specialized tools ... instead' appears twice). Could be more concise while retaining all information.

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

Completeness4/5

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

Given the tool's complexity (22 params, many actions, deprecation) and the presence of an output schema (so return values need not be described), the description covers the primary use cases well. It also explains the deprecation context and recommends granular alternatives. Missing details on less common parameters slightly reduce completeness.

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 0%, so the description must compensate. The action guide explains key parameters for main actions (e.g., action, content, memory_id, query, category), but 22 total parameters exist, and many optional ones (auto, mode, as_of, depth, etc.) are not explained. The description adds value for the most common parameters but is incomplete.

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 clearly states it is a legacy dispatcher for backward compatibility and lists all supported actions. It distinguishes itself from siblings by explicitly naming granular tools (e.g., add_memory, search_memory) and advising their use instead.

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

Usage Guidelines5/5

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

The description provides an explicit 'ACTION GUIDE' detailing when to use each action (e.g., 'Use BEFORE add to avoid duplicates' for search) and includes a workflow (search -> not found? -> add). It also directs users to use specialized tools instead of this composite one.

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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