get_thermal_info
Retrieves current CPU and GPU temperatures to help monitor system thermals and detect overheating.
Instructions
Get CPU and GPU temperatures
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieves current CPU and GPU temperatures to help monitor system thermals and detect overheating.
Get CPU and GPU temperatures
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds nothing beyond the resource name — no mention of units, sensor source, refresh/liveness, or value format — so it earns only minimal credit given the annotation baseline.
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 front-loaded sentence with no filler. Every word earns its place for a no-param read tool.
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?
For a simple read tool with no params, no output schema, and safety annotations, the description covers the core purpose. However, with no output schema, it could have added expected return values (units, per-core vs package, availability when sensors are missing) and does not.
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?
There are zero parameters, which is the baseline-4 case. No parameter-level semantics are needed or expected.
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?
Specific verb 'get' and resource 'CPU and GPU temperatures' clearly state what the tool returns. It is reasonably distinguishable from siblings like get_cpu_info and get_gpu_info, though the description never clarifies whether those siblings already include temperature, leaving some overlap ambiguity.
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?
Usage is implied by the resource (thermal readings), but there is no explicit guidance on when to use this versus get_cpu_info or get_gpu_info, which likely surface related data. No exclusions or alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.