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memory_save

Save lessons, insights, or notes to persistent memory that endures across sessions, enabling the AI to learn and improve over time.

Instructions

Save a learning, insight, or note to persistent memory. Memory survives across sessions and helps the AI improve over time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesType of memory (lesson, mistake, insight, skill_update, user_preference, research)
contentYesThe actual memory content to save
tagsNoComma-separated tags for searchability (e.g. "seo,google,reviews")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions persistence across sessions but fails to clarify whether this is an insert or upsert operation, any size limits, or what happens to existing data with the same category/content. The behavioral traits are insufficiently specified.

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 consists of two concise sentences that front-load the core purpose. Every word contributes meaning without redundancy or excessive length.

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?

An output schema exists but its details are not shown; the description does not reference return values. While the schema covers parameters, the description lacks context on categories, example usage, or integration with other memory tools. It is minimally complete for a simple create operation.

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?

The input schema already provides 100% coverage with descriptions for all three parameters. The tool description adds no additional meaning beyond what the schema offers, so it meets the baseline for this dimension.

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 verb 'Save' and the resource 'learning, insight, or note to persistent memory', distinguishing it as a tool for creating new memories. Among sibling tools like memory_recall and update_memory, this purpose is specific and unambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as update_memory or upsert_memory_node. The agent is left to infer that 'save' implies creating new entries, but explicit differentiation is missing.

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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