Skip to main content
Glama

store_episodic_memory

Logs timestamped events (ideas, notes, tasks, papers, meetings, agent runs) and indexes them for vector search, enabling chronological retrieval of past activities.

Instructions

Store an event in episodic memory and index it for vector search.

Logs a time-stamped EVENT (something that happened) and indexes it for vector
search. For a distilled, timeless concept/definition use store_semantic_memory;
for a human-curated palace note use add_memory_entry.

Episodic memory is a chronological log of things that happened — ideas,
notes, papers read, tasks completed, agent runs.

Args:
    content: The text content of the event to remember.
    event_type: One of 'idea', 'note', 'task', 'paper', 'meeting', or
        'agent_run'.
    session_id: Current pipeline session ID (optional).
    metadata: JSON string with extra fields such as title, tags, or source.

Returns:
    A single TextContent confirming the stored event (its row id and type),
    or an error message if the database is missing, fastembed is not
    installed, or the write fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
event_typeNonote
session_idNo
metadataNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so the description carries full burden. It describes logging a time-stamped event and indexing for vector search, mentions possible errors (database missing, fastembed not installed), and return format. However, it does not discuss write permissions, idempotency, or concurrency. Still, it clearly communicates the non-trivial side effect of indexing.

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 well-structured: a concise first sentence stating purpose, followed by usage guidance, then Args and Returns sections. No redundant or vague statements. Every sentence adds value.

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 4 parameters, 1 required, and no output schema provided, the description covers purpose, usage, parameter details, and return values. It also references sibling tools and error scenarios, making it complete for an AI agent to select and invoke the tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must explain parameters. It includes an 'Args' section that explains each parameter: content (required), event_type (with enumerated values), session_id (optional), metadata (JSON string with extra fields). This adds critical meaning beyond the schema.

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 the tool's purpose: 'Store an event in episodic memory and index it for vector search.' It uses a specific verb ('store') and resource ('episodic memory'), and differentiates from siblings by naming store_semantic_memory and add_memory_entry as alternatives.

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?

Explicit guidance on when to use this tool vs alternatives: 'For a distilled, timeless concept/definition use store_semantic_memory; for a human-curated palace note use add_memory_entry.' Also defines episodic memory as a chronological log.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SVerITG/Metis_PH'

If you have feedback or need assistance with the MCP directory API, please join our Discord server