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loaditout-mcp-server

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save_memory

Save key-value pairs to persistent memory across sessions for remembering user preferences, installed skills, or project context.

Instructions

Save a key-value pair to persistent agent memory that survives across sessions. Returns a confirmation with the stored key. Use this to remember installed skills, user preferences, project context, or recent search queries. Call this proactively whenever you learn something worth remembering. Do not store sensitive data like passwords or API keys. Retrieve saved memories with recall_memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key name. Examples: 'installed_skills', 'preferred_categories', 'project_context'
valueYesAny JSON-serializable value to store (string, array, object, number, etc.)
typeYesCategory of this memory entry
Behavior4/5

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

No annotations provided, so description carries full burden. It explains persistence across sessions, return confirmation, and data sensitivity. Missing details on overwrite behavior or error handling, but covers core behaviors well.

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?

Description is concise, front-loaded with purpose, and every sentence provides value. No redundant or unnecessary text.

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?

The description adequately explains the tool's purpose, usage, parameters, and return value. Lacks details on edge cases (e.g., duplicate key) but is sufficient for an agent to use effectively.

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% with descriptions for all parameters. The description adds usage examples for key and value, but doesn't significantly enhance meaning beyond the schema. Baseline 3 is appropriate.

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 ('Save a key-value pair') and the resource ('persistent agent memory that survives across sessions'). It distinguishes from sibling tools like recall_memory by focusing on storing rather than 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?

Explicitly recommends when to use (e.g., remember installed skills, user preferences) and warns against storing sensitive data. Directs to use recall_memory for retrieval, providing clear guidance.

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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