suggest_gpu_layersDetermines the GPU offload layers for a local GGUF model within a VRAM budget and flags when CPU offloading is needed.
在显存预算内建议最大的 GPU offload 层数；放不下时提示需要 CPU 混合。
| Name | Required | Description | Default |
|---|---|---|---|
| ctx_len | No | ||
| model_id | Yes | ||
| budget_gb | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It does disclose one useful behavior beyond structured data: the graceful degradation to CPU offload when the budget is exceeded. However, it says nothing about defaults (budget_gb=7, ctx_len=8192), whether the recommendation is advisory only, or any auth/permission needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single dense sentence, front-loaded with the core action and followed by the edge-case behavior. No filler, though the compression leaves semantic gaps that hurt other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be described. But for a computation tool with three undocumented parameters and no stated relationship to estimate_vram/start_server, the description leaves an agent guessing about inputs and workflow placement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% across 3 parameters. The description implies the budget_gb parameter via '显存预算' but never explains its units/default, and ctx_len — which materially changes layer sizing — is entirely unmentioned in both schema and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: suggesting the maximum number of GPU offload layers, constrained by a VRAM budget, plus the CPU-mixing fallback when it doesn't fit. That is far more precise than a tautology, but it never distinguishes itself from sibling tool estimate_vram, which an agent could easily confuse for this calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to call this versus estimate_vram or start_server, and no prerequisite info (e.g., must the model be listed/loaded first). The only conditional content is an output behavior ('says CPU mixing is needed'), not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.