spec: add errorbar-asymmetric specification

plots/errorbar-asymmetric/specification.md

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+# errorbar-asymmetric: Asymmetric Error Bars Plot
+
+## Description
+
+An asymmetric error bar plot displays data points with separate upper and lower error magnitudes, allowing different-sized bars extending above and below each point. This visualization is essential for representing skewed distributions, non-symmetric confidence intervals, or data where uncertainty differs in positive and negative directions. Common applications include percentile-based intervals, log-transformed data, and Bayesian credible intervals.
+
+## Applications
+
+- Scientific research presenting results with non-symmetric confidence intervals (e.g., 5th-95th percentile)
+- Financial forecasting showing different upside and downside risk projections
+- Clinical trials displaying treatment effects with asymmetric uncertainty bounds
+- Environmental monitoring reporting measurements with different detection limits above and below
+
+## Data
+
+- `x` (categorical or numeric) - Categories or positions on the x-axis
+- `y` (numeric) - Central values representing mean, median, or point estimates
+- `error_lower` (numeric) - Error magnitude extending below each point
+- `error_upper` (numeric) - Error magnitude extending above each point
+- Size: 3-20 data points for clarity
+
+## Notes
+
+- Error bars should have visible caps (horizontal lines at ends) to clearly mark the error range
+- Consider using different colors or markers when comparing multiple series
+- Include a legend or annotation explaining what the asymmetric bounds represent (e.g., "10th-90th percentile", "95% CI")
+- Useful for log-scale axes where symmetric intervals would appear asymmetric after transformation

plots/errorbar-asymmetric/specification.yaml

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+# Specification-level metadata for errorbar-asymmetric
+# Auto-synced to PostgreSQL on push to main
+
+spec_id: errorbar-asymmetric
+title: Asymmetric Error Bars Plot
+
+# Specification tracking
+created: 2025-12-30T17:27:52Z
+updated: null
+issue: 2781
+suggested: MarkusNeusinger
+
+# Classification tags (applies to all library implementations)
+# See docs/concepts/tagging-system.md for detailed guidelines
+tags:
+  plot_type:
+    - errorbar
+    - point
+  data_type:
+    - numeric
+    - categorical
+  domain:
+    - general
+    - statistics
+    - science
+  features:
+    - asymmetric
+    - uncertainty
+    - confidence-interval