hardware-assessment-output-schema-v10

Sub-skill of hardware-assessment: Output Schema (v1.0).

5 stars

Best use case

hardware-assessment-output-schema-v10 is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of hardware-assessment: Output Schema (v1.0).

Teams using hardware-assessment-output-schema-v10 should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/output-schema-v10/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/operations/devops/hardware-assessment/output-schema-v10/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/output-schema-v10/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How hardware-assessment-output-schema-v10 Compares

Feature / Agent	hardware-assessment-output-schema-v10	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Sub-skill of hardware-assessment: Output Schema (v1.0).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Output Schema (v1.0)

## Output Schema (v1.0)


Both scripts produce identical JSON structure:

```json
{
  "schema_version": "1.0",
  "script_version": "1.0.0",
  "platform": "linux|windows",
  "timestamp": "ISO-8601",
  "cpu": {
    "model": "Intel Xeon E5-2630 v3 @ 2.40GHz",
    "architecture": "x86_64",
    "sockets": 2,
    "cores_per_socket": 8,
    "total_cores": 16,
    "threads_per_core": 2,
    "total_threads": 32,
    "max_mhz": "3200.0000",
    "l3_cache": "40 MiB"
  },
  "memory": {
    "total_kb": 32810676,
    "total_gb": "31.3",
    "type": "DDR4",
    "speed": "2133 MT/s"
  },

*See sub-skills for full details.*

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