Add polars-bio skill for genomic interval operations and bioinformatics I/O

Adds a new skill covering polars-bio (v0.26.0), a high-performance library
for genomic interval arithmetic and file I/O built on Polars, Arrow, and
DataFusion. All code examples verified against the actual API at runtime.

SKILL.md covers overlap, nearest, merge, coverage, complement, subtract,
cluster, count_overlaps operations plus read/scan/write/sink for BED, VCF,
BAM, CRAM, GFF, GTF, FASTA, FASTQ, SAM, and Hi-C pairs formats.

References: interval_operations, file_io, sql_processing, pileup_operations,
configuration, bioframe_migration.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

scientific-skills/polars-bio/references/configuration.md

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+# Configuration
+
+## Overview
+
+polars-bio uses a global configuration system based on `set_option` and `get_option` to control execution behavior, coordinate systems, parallelism, and streaming modes.
+
+## set_option / get_option
+
+```python
+import polars_bio as pb
+
+# Set a configuration option
+pb.set_option("datafusion.execution.target_partitions", 8)
+
+# Get current value
+value = pb.get_option("datafusion.execution.target_partitions")
+```
+
+## Parallelism
+
+### DataFusion Target Partitions
+
+Controls the number of parallel execution partitions. Defaults to 1 (single-threaded).
+
+```python
+import os
+import polars_bio as pb
+
+# Use all available CPU cores
+pb.set_option("datafusion.execution.target_partitions", os.cpu_count())
+
+# Set specific number of partitions
+pb.set_option("datafusion.execution.target_partitions", 8)
+```
+
+**When to increase parallelism:**
+- Processing large files (>1GB)
+- Running interval operations on millions of intervals
+- Batch processing multiple chromosomes
+
+**When to keep default (1):**
+- Small datasets
+- Memory-constrained environments
+- Debugging (deterministic execution)
+
+## Coordinate Systems
+
+polars-bio defaults to 1-based coordinates (standard genomic convention).
+
+### Global Coordinate System
+
+```python
+import polars_bio as pb
+
+# Switch to 0-based half-open coordinates
+pb.set_option("coordinate_system", "0-based")
+
+# Switch back to 1-based (default)
+pb.set_option("coordinate_system", "1-based")
+
+# Check current setting
+print(pb.get_option("coordinate_system"))
+```
+
+### Per-File Override via I/O Functions
+
+I/O functions accept `use_zero_based` to set coordinate metadata on the resulting DataFrame:
+
+```python
+# Read with explicit 0-based metadata
+df = pb.read_bed("regions.bed", use_zero_based=True)
+```
+
+**Note:** Interval operations (overlap, nearest, etc.) do **not** accept `use_zero_based`. They read coordinate metadata from the DataFrames, which is set by I/O functions or the global option. When using manually constructed DataFrames, polars-bio warns about missing metadata and falls back to the global setting.
+
+### Setting Metadata on Manual DataFrames
+
+```python
+import polars_bio as pb
+
+# Set coordinate metadata on a manually created DataFrame
+pb.set_source_metadata(df, format="bed", path="")
+```
+
+### File Format Conventions
+
+| Format | Native Coordinate System | polars-bio Conversion |
+|--------|-------------------------|----------------------|
+| BED | 0-based half-open | Converted to configured system on read |
+| VCF | 1-based | Converted to configured system on read |
+| GFF/GTF | 1-based | Converted to configured system on read |
+| BAM/SAM | 0-based | Converted to configured system on read |
+
+## Streaming Execution Modes
+
+polars-bio supports two streaming modes for out-of-core processing:
+
+### DataFusion Streaming
+
+Enabled by default for interval operations. Processes data in batches through the DataFusion execution engine.
+
+```python
+# DataFusion streaming is automatic for interval operations
+result = pb.overlap(lf1, lf2)  # Streams if inputs are LazyFrames
+```
+
+### Polars Streaming
+
+Use Polars' native streaming for post-processing operations:
+
+```python
+# Collect with Polars streaming
+result = lf.collect(streaming=True)
+```
+
+### Combining Both
+
+```python
+import polars_bio as pb
+
+# Scan files lazily (DataFusion streaming for I/O)
+lf1 = pb.scan_bed("large1.bed")
+lf2 = pb.scan_bed("large2.bed")
+
+# Interval operation (DataFusion streaming)
+result_lf = pb.overlap(lf1, lf2)
+
+# Collect with Polars streaming for final materialization
+result = result_lf.collect(streaming=True)
+```
+
+## Logging
+
+Control log verbosity for debugging:
+
+```python
+import polars_bio as pb
+
+# Set log level
+pb.set_loglevel("debug")   # Detailed execution info
+pb.set_loglevel("info")    # Standard messages
+pb.set_loglevel("warn")    # Warnings only (default)
+```
+
+**Note:** Only `"debug"`, `"info"`, and `"warn"` are valid log levels.
+
+## Metadata Management
+
+polars-bio attaches coordinate system and source metadata to DataFrames produced by I/O functions. This metadata is used by interval operations to determine the coordinate system.
+
+```python
+import polars_bio as pb
+
+# Inspect metadata on a DataFrame
+metadata = pb.get_metadata(df)
+
+# Print metadata summary
+pb.print_metadata_summary(df)
+
+# Print metadata as JSON
+pb.print_metadata_json(df)
+
+# Set metadata on a manually created DataFrame
+pb.set_source_metadata(df, format="bed", path="regions.bed")
+
+# Register a DataFrame as a SQL table
+pb.from_polars("my_table", df)
+```
+
+## Complete Configuration Reference
+
+| Option | Default | Description |
+|--------|---------|-------------|
+| `datafusion.execution.target_partitions` | `1` | Number of parallel execution partitions |
+| `coordinate_system` | `"1-based"` | Default coordinate system (`"0-based"` or `"1-based"`) |