Identifies the machine's NVIDIA GPU and reports name, driver, memory, power limit, compute capability, max SM clock, plus matching roofline table entry when known.
Identify the GPU(s) in this machine via nvidia-smi: name, driver, memory, power limit, compute capability, max SM clock. Also returns the matching roofline table entry if known.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so the description carries the full burden. It usefully discloses the data source (nvidia-smi) and the exact fields returned, plus the conditional bonus return of a roofline table entry. It omits meaningful behavior: what happens on a machine without an NVIDIA GPU or without nvidia-smi installed, and whether the discovery is cached or live.
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?
Two tight sentences, front-loaded with the action and source, then the return fields. No filler and no repetition of the tool name.
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?
With no input schema and no output schema, the description must supply the return contract, and it does so by enumerating the reported attributes plus the conditional roofline entry. The main residual gap is failure behavior on non-NVIDIA or nvidia-smi-less hosts, which an agent would want to know before relying on it.
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?
The tool takes zero parameters, so there is nothing to disambiguate; baseline 4 applies. The description correctly frames it as a parameterless probe of the local machine.
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 and resource: 'Identify the GPU(s) in this machine via nvidia-smi', followed by an explicit enumeration of the returned attributes (name, driver, memory, power limit, compute capability, max SM clock). It is clear what the tool does, but only implicitly distinguishes itself from siblings like roofline or bench by noting that it merely returns a matching roofline entry rather than computing one.
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 rather than stated: an agent can infer this is the hardware-discovery step before roofline/bench work, but the description never says 'call this first' or when to prefer it over siblings. No exclusions or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.