quantification-metrics-validation-checklist
Sub-skill of quantification-metrics: Validation Checklist.
Best use case
quantification-metrics-validation-checklist is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of quantification-metrics: Validation Checklist.
Teams using quantification-metrics-validation-checklist 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/validation-checklist/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How quantification-metrics-validation-checklist Compares
| Feature / Agent | quantification-metrics-validation-checklist | 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 quantification-metrics: Validation Checklist.
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
# Validation Checklist ## Validation Checklist Before finalizing metrics: - [ ] Calculations are mathematically correct - [ ] Assumptions are clearly documented - [ ] Units are consistent throughout - [ ] Ranges account for uncertainty - [ ] Comparable to industry benchmarks - [ ] Evidence or sources cited where applicable - [ ] Results pass reasonableness test - [ ] Potential biases acknowledged - [ ] Limitations stated if any - [ ] Updated with actual data when available
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