Skip to main content
Glama

Note a Memory

note

Record durable decisions, findings, or corrections into memory mid-task for future recall. Designed for storing user preferences and lessons, not transient chatter.

Instructions

Record a decision, finding, or correction into memory mid-task so it can be recalled in future sessions. Returns {ok, noted}. The text is captured as a candidate and deduped against existing knowledge by the background pipeline. Use when the user states a durable preference or you learn something worth keeping; not for transient chatter. To retrieve memories use recall.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe lesson to remember, as one self-contained sentence, e.g. 'The user prefers Conventional Commits with no body.'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
notedNo
Behavior4/5

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

Annotations are all false, providing no behavioral hints. The description compensates by disclosing that the text is captured as a candidate and deduped against existing knowledge by a background pipeline, and that it returns {ok, noted}. This adds value beyond annotations.

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 extremely concise: two sentences plus a usage line. Every sentence adds value, no fluff. Front-loaded with the core purpose.

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 tool's simplicity (one required parameter, no enums, no nested objects), the description is complete. It explains the return format, the dedup pipeline, and the appropriate use cases. No gaps.

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 coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond the schema's parameter description, which already provides good formatting guidance: 'the lesson to remember, as one self-contained sentence, e.g. ...' Thus no additional value from the description's text.

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: 'Record a decision, finding, or correction into memory mid-task so it can be recalled in future sessions.' It uses a specific verb 'Record' and resource 'memory', and distinguishes from sibling 'recall' by indicating that this tool is for recording, not retrieving.

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 usage guidance is provided: 'Use when the user states a durable preference or you learn something worth keeping; not for transient chatter. To retrieve memories use `recall`.' This tells the agent when to use, when not to use, and names the alternative tool.

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/writerslogic/cogmem'

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