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Save a quick agent observation, preference, or decision as a searchable vector for later retrieval, without needing full document processing.

Instructions

Store a lightweight agent observation as a searchable vector. Use when the agent wants to save a quick preference, decision, or observation without needing full document processing. Faster than remember for short notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoOptional tags for filtering (e.g. ['preference', 'user-123'])
textYesThe observation or note to store (minimum 5 characters)
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the note is stored as a searchable vector and that it is faster than 'remember' for short notes. However, it does not mention return behavior, potential failures, or limits beyond the minimum characters, leaving some behavioral gaps.

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 two sentences, front-loads the core purpose, and follows with usage context. Every word adds value, with no repetition or fluff. It is appropriately sized for a simple tool.

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?

For a simple two-parameter tool with no output schema, the description covers the what, when, and how it compares to a sibling tool. It does not explain the return value, but this is not critical for a store operation. It is sufficiently complete for the tool's simplicity.

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% as both 'text' and 'tags' have descriptions. The description adds no additional parameter-level meaning beyond the schema, earning the baseline score of 3. It does not elaborate on tag format or constraints beyond what is already present.

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 specifies the verb 'Store' and the resource 'lightweight agent observation as a searchable vector'. It distinguishes from the sibling 'remember' by noting it is for quick notes and avoids full document processing, making the purpose unambiguous.

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 agent wants to save a quick preference, decision, or observation without needing full document processing.' It also names the alternative 'remember' and compares performance ('Faster than remember for short notes'), clearly indicating when to use this tool versus 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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