Skip to main content
Glama

save_agent_note

Store persistent operational notes like printer quirks, calibration findings, or material preferences that survive across sessions. Use keys and scopes to organize knowledge for any printer.

Instructions

Save a persistent note or preference that survives across sessions.

Use this to remember printer quirks, calibration findings, material
preferences, or any operational knowledge worth preserving.

Args:
    key: Name for this memory (e.g., ``"z_offset_adjustment"``, ``"pla_temp_notes"``).
    value: The information to store.
    scope: Namespace — ``"global"``, ``"fleet"``, or use *printer_name* for printer-specific.
    printer_name: If provided, scope is automatically set to ``"printer:<name>"``.
    ttl_seconds: Optional time-to-live in seconds.  The note will be
        automatically excluded from queries after this duration.  Pass
        ``None`` (default) for notes that should never expire.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
scopeNoglobal
valueYes
ttl_secondsNo
printer_nameNo
Behavior4/5

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

No annotations, so description carries full burden. It explains persistence across sessions, TTL auto-expiry, and scope/printer_name interaction. Adequate disclosure for a storage tool.

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?

Docstring format with Args section is well-structured. First sentence conveys purpose. No wasted words; each 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?

With 5 params, no output schema, and no annotations, description provides complete coverage: purpose, parameter details, behavioral traits. Agent can confidently use it.

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 has 0% description coverage; description explains all five parameters: key, value, scope, printer_name, ttl_seconds. Adds meaning about scope override and TTL behavior.

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?

Description clearly states the tool saves persistent notes/settings. Provides specific use cases like printer quirks, calibration findings, distinguishing it from similar tools like delete_agent_note.

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

Usage Guidelines4/5

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

Explicitly says when to use it ('remember printer quirks...'), but does not specify when not to use it or alternatives. However, examples imply usage context, and siblings like delete_agent_note exist.

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/codeofaxel/kiln'

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