Skip to main content
Glama
GonzaloTorreras

ai-dememory

Record Memory Outcome

memory.outcome

Record whether a memory was useful by assigning a good or bad outcome, optionally targeting a specific memory by ID or the last seen memory, and adding a note.

Instructions

Record good/bad usefulness feedback for a memory or last seen memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
lastNo
noteNo
outcomeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
outcomeYes
strengthYes
memory_idYes
created_atYes
note_recordedYes
reward_factorYes
target_sourceYes
lifecycle_updatedYes
negative_outcomesYes
positive_outcomesYes
Behavior3/5

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

Annotations already convey readOnlyHint=false and destructiveHint=false, so the description's 'record feedback' is consistent but adds little extra context. No details on side effects, authentication, or rate limits are provided.

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 a single, concise sentence that immediately conveys the core functionality. No wasted words.

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

Completeness3/5

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

The description captures the basic purpose but leaves significant gaps, such as how id and last interact, what 'note' is for, and the exact effect of recording an outcome. The presence of an output schema does not excuse the lack of parameter context.

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

Parameters2/5

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

Schema coverage is 0%, but the description does not explain any of the four parameters (id, last, note, outcome). For example, it could clarify that 'last' selects the most recent memory when true, or that 'note' is optional. The omission forces reliance on schema alone.

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 action (record), the resource (memory or last seen memory), and the possible outcomes (good/bad usefulness feedback). It effectively distinguishes from sibling tools like memory.review_recommendation_outcome, which deals with review recommendations.

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

Usage Guidelines3/5

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

The description implies when to use (to give feedback), but provides no explicit guidance on when not to use or alternatives. Given many siblings, it could clarify that it's for direct memory feedback, not for review recommendations.

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/GonzaloTorreras/ai-dememory'

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