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mimir_remember

Destructive

Save or update persistent facts, decisions, and conventions across sessions. Idempotent with optional encryption and conflict detection.

Instructions

Store or update an entity by (category, key). Idempotent — call as often as you want, same key returns an update. Optional always_on=true injects entity into every mimir_context. Optional certainty (0.0-1.0) is used by mimir_conflicts for typed-entity conflict detection. Use this for saving facts, decisions, architecture notes, and conventions. When encryption is enabled, body_json is encrypted at rest with AES-256-GCM.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesUnique key within the category, e.g. 'use-postgres-16' or 'deployment-strategy'
tagsNoTags for categorization and cross-referencing
typeNoEntity type: 'insight', 'architecture', 'decision', 'reference', 'convention'insight
statusNoEntity status: 'active', 'draft', 'deprecated'active
agent_idNoAgent identity (v1.2.0). Tracks which agent wrote this entity. Used for agent attribution and context filtering.
categoryYesEntity category: 'decision', 'architecture', 'convention', 'insight', or custom
body_jsonYesJSON object with the entity body — store content, summary, and any custom fields here
importanceNoInitial importance 0.0–1.0 — sets the starting decay score
topic_pathNoHierarchical topic path, e.g. 'architecture/database/postgres'
workspace_hashNoWorkspace scope identifier (v1.2.0). Empty = global. Entities with a workspace_hash are invisible to recall queries scoped to a different workspace.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoEntity ID, e.g. 'mem-a1b2c3d4e5f6'
keyNoEntity key
actionNo'created' for new entities, 'updated' for existing ones
categoryNoEntity category
Behavior5/5

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

The description adds significant behavioral details beyond the annotations: idempotency, encryption at rest (AES-256-GCM) when enabled, and the effect of always_on=true injecting into mimir_context. This complements the destructiveHint annotation.

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 concise, consisting of four clear sentences. It front-loads the core function and immediately follows with key behaviors and use cases. No unnecessary words.

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 complexity (10 parameters, 3 required), the description covers essential aspects: idempotency, encryption, always_on, certainty usage, and appropriate use cases. An output schema exists, so return values need not be described. It could mention behavior on conflict or error, but overall it is adequate.

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

Parameters4/5

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

Schema coverage is 100% so the schema already documents all parameters. The description adds context for key parameters (e.g., key as unique within category, body_json as JSON object) and explains the purpose of optional fields like always_on and certainty. It does not cover every parameter in detail but provides meaningful usage guidance.

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 'Store or update an entity by (category, key)' and lists specific use cases such as saving facts, decisions, architecture notes, and conventions. This distinguishes it from sibling retrieval or deletion tools.

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 explicitly mentions when to use the tool ('for saving facts, decisions, architecture notes, and conventions') and describes optional parameters like always_on and certainty. However, it does not explicitly state when not to use it or mention alternatives.

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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