/metric-calculator
Compute well-defined metrics from existing formulas, datasets, or test outputs. Use as an explicit/manual helper when the metric definition is already known, not for choosing the overall analysis owner or dashboard strategy.
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill metric-calculator --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/metric-calculator
Context preview
The summary Claude sees to decide when to auto-load this skill.
Compute well-defined metrics from existing formulas, datasets, or test outputs. Use as an explicit/manual helper when the metric definition is already known, not for choosing the overall analysis owner or dashboard strategy.
SKILL.md
metric-calculator.SKILL.mdname: metric-calculator description: | Compute well-defined metrics from existing formulas, datasets, or test outputs. Use as an explicit/manual helper when the metric definition is already known, not for choosing the overall analysis owner or dashboard strategy. allowed-tools: Read, Write, Edit, Bash, Grep version: 1.0.0 license: MIT author: Jeremy Longshore <jeremy@intentsolutions.io>
Metric Calculator
Positioning
Treat this skill as an explicit/manual helper for narrow metric-computation work.
When to Use
Use this skill when:
- Calculating a named business, statistical, or QA metric from available data
- Converting raw counts into rates, ratios, deltas, or scorecards
- Verifying that a metric formula is implemented consistently across outputs
Not For / Boundaries
- Model evaluation strategy selection: use `evaluating-machine-learning-models`
- Full regression modeling ownership: use `scikit-learn`; causal analysis ownership: use `performing-causal-analysis`
- Chart design or presentation decisions: use `creating-data-visualizations`
Typical Outputs
- Metric definitions and formulas
- Reproducible calculation steps
- Sanity checks for units, denominators, and aggregation scope
Related Skills
- `evaluating-machine-learning-models` for ML benchmark metrics
- `creating-data-visualizations` after the numbers are finalized
VibeSkills is a general-purpose Skill that automatically routes local Skills and intelligently orchestrates harness workflows.
Repo: foryourhealth111-pixel/Vibe-Skills
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