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Load checkpoints now (slow, once)

preload_warmup
Idempotent

Force load Laya model checkpoints into memory to accelerate subsequent decision-making. Use when connecting via stdio or if server warmup was disabled.

Instructions

Force checkpoints into memory so later decisions are fast.

Rarely needed: the HTTP server warms up at start. Call it only if you connect over stdio or the server was started with warmup disabled. Loading downloads hundreds of MB the first time, so expect a slow call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsNoCheckpoints to keep resident: english, multilingual, typed-decisions

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: it downloads hundreds of MB on first use and will be slow. It does not describe memory-residency duration or failure modes, so it stops short of a 5.

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?

Three short sentences, zero waste. The core action is front-loaded, followed by the rarity caveat and the cost warning in descending order of importance.

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?

For a zero-required-parameter warmup tool with an output schema and full annotation coverage, the description covers what it does, when to use it, and its performance cost. Nothing an agent needs to decide whether and how to invoke it is missing.

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 description coverage is 100% and the single optional 'models' parameter is documented in the schema with its valid checkpoint values. The description adds no syntax, default, or selection guidance beyond what the schema already provides, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action and effect: 'Force checkpoints into memory so later decisions are fast.' That is a clear verb+resource+outcome. It does not explicitly contrast with any sibling, but the siblings (decide, route_request, server_status) are functionally distinct enough that differentiation is not critical.

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?

It gives explicit when-not guidance ('Rarely needed: the HTTP server warms up at start') and a precise triggering condition for when to use it ('only if you connect over stdio or the server was started with warmup disabled'). This is exactly the when/when-not structure that earns a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.