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ks6573
by ks6573

get_hardware_profile

Read-onlyIdempotent

Analyze your hardware for any workload: provides specs, live pressure, overclocking capability, upgrade feasibility, and bottleneck analysis to help decide on upgrading or overclocking.

Instructions

Returns a full hardware profile for a given use-case: specs, live pressure, overclocking capability (where supported), upgrade feasibility per component, and workload-specific bottleneck analysis. Use this when the user asks about speeding up a specific task, upgrading their machine, or overclocking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
use_caseNoThe user's workload or goal, e.g. 'lightroom rendering', 'gaming', 'video editing', 'compiling code'
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful context about what the tool returns, including 'live pressure' and 'overclocking capability (where supported),' which helps set expectations. It does not contradict annotations.

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?

Two sentences, front-loaded with the main verb and resource, then a useful usage directive. No filler or redundant information. Every sentence adds value.

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 tool is complex and has no output schema, but the description covers the key return categories and usage scenarios. It doesn't explain nuances like whether the profile is real-time or cached, but given the annotations and simple schema, it is sufficiently complete for an agent to select and invoke it correctly.

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%, so the parameter 'use_case' is fully described in the schema with examples. The description adds slight context by linking the parameter to user intents like upgrading or overclocking, but it doesn't substantially enrich beyond the schema. Baseline 3 applies.

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 tool returns a 'full hardware profile' for a use-case, listing specific contents (specs, live pressure, overclocking capability, upgrade feasibility, bottleneck analysis). This distinguishes it from sibling tools like get_cpu_usage or get_device_specs, which cover narrower or different scopes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use the tool: 'when the user asks about speeding up a specific task, upgrading their machine, or overclocking.' This gives clear contextual guidance, though it does not name alternatives or explicitly state when not to use it.

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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