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update to idc-index- 0.11.9
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CHANGELOG.md

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## [Unreleased]
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## [1.3.0] - 2026-02-10
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### Added
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- Digital pathology reference guide (`references/digital_pathology_guide.md`) with SM, ANN, and SEG query patterns, join examples, and pathology tool recommendations
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- `references/use_cases.md` - End-to-end workflow examples
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- Quick Navigation section in SKILL.md with decision triggers for when to load each reference
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- `idc-data-version` field in frontmatter metadata
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- Documentation for new `contrast_index` table (contrast bolus metadata for CT, MR, PT, XA, RF series)
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### Changed
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- Updated to idc-index 0.11.9 (IDC data version v23)
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- Reduced SKILL.md from 1,245 to 825 lines by extracting secondary content to reference files
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- Core Capabilities sections remain inline to ensure correct API pattern usage
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- Refactored detailed SM/ANN content from SKILL.md into `references/digital_pathology_guide.md`, keeping brief summaries with pointers in main skill
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- Updated to idc-index 0.11.8 (IDC data version v23)
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- Made IDC version (v23) more prominent in SKILL.md with verification guidance to prevent responses using older versions
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- Clarified distinction between `index_tables_guide.md` (structure/access) and `sql_patterns.md` (query examples)
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SKILL.md

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description: Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
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license: This skill is provided under the MIT License. IDC data itself has individual licensing (mostly CC-BY, some CC-NC) that must be respected when using the data.
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metadata:
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version: 1.2.0
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version: 1.3.0
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skill-author: Andrey Fedorov, @fedorov
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idc-index: "0.11.8"
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idc-index: "0.11.9"
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idc-data-version: "v23"
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repository: https://github.com/ImagingDataCommons/idc-claude-skill
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---
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| `seg_index` | 1 row = 1 DICOM Segmentation series | fetch_index() | Segmentation metadata: algorithm, segment count, reference to source image series |
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| `ann_index` | 1 row = 1 DICOM ANN series | fetch_index() | Microscopy Bulk Simple Annotations series metadata; references annotated image series |
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| `ann_group_index` | 1 row = 1 annotation group | fetch_index() | Detailed annotation group metadata: graphic type, annotation count, property codes, algorithm |
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| `contrast_index` | 1 row = 1 series with contrast info | fetch_index() | Contrast agent metadata: agent name, ingredient, administration route (CT, MR, PT, XA, RF) |
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**Auto** = loaded automatically when `IDCClient()` is instantiated
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**fetch_index()** = requires `client.fetch_index("table_name")` to load
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| `source_DOI` | index, analysis_results_index | Link by publication DOI |
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| `crdc_series_uuid` | index, prior_versions_index | Link by CRDC unique identifier |
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| `Modality` | index, prior_versions_index | Filter by imaging modality |
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| `SeriesInstanceUID` | index, seg_index, ann_index, ann_group_index | Link segmentation/annotation series to its index metadata |
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| `SeriesInstanceUID` | index, seg_index, ann_index, ann_group_index, contrast_index | Link segmentation/annotation/contrast series to its index metadata |
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| `segmented_SeriesInstanceUID` | seg_index → index | Link segmentation to its source image series (join seg_index.segmented_SeriesInstanceUID = index.SeriesInstanceUID) |
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| `referenced_SeriesInstanceUID` | ann_index → index | Link annotation to its source image series (join ann_index.referenced_SeriesInstanceUID = index.SeriesInstanceUID) |
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```
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If you see an older version, upgrade with: `pip install --upgrade idc-index`
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**Tested with:** idc-index 0.11.8 (IDC data version v23)
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**Tested with:** idc-index 0.11.9 (IDC data version v23)
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**Optional (for data analysis):**
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```bash

references/digital_pathology_guide.md

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# Digital Pathology Guide for IDC
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**Tested with:** IDC data version v23, idc-index 0.11.8
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**Tested with:** IDC data version v23, idc-index 0.11.9
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For general IDC queries and downloads, use `idc-index` (see main SKILL.md). This guide covers slide microscopy (SM) imaging, microscopy bulk simple annotations (ANN), and segmentations (SEG) in the context of digital pathology in IDC.
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references/index_tables_guide.md

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# Index Tables Guide for IDC
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**Tested with:** idc-index 0.11.8 (IDC data version v23)
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**Tested with:** idc-index 0.11.9 (IDC data version v23)
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This guide covers the structure and access patterns for IDC index tables: programmatic schema discovery, DataFrame access, and join column references. For the overview of available tables and their purposes, see the "Index Tables" section in the main SKILL.md.
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| `index` | `ann_index` | `index.SeriesInstanceUID = ann_index.SeriesInstanceUID` |
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| `ann_index` | `ann_group_index` | `ann_index.SeriesInstanceUID = ann_group_index.SeriesInstanceUID` |
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| `index` | `clinical_index` | `index.collection_id = clinical_index.collection_id` (then filter by patient) |
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| `index` | `contrast_index` | `index.SeriesInstanceUID = contrast_index.SeriesInstanceUID` |
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For complete query examples using these joins, see `references/sql_patterns.md`.
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references/sql_patterns.md

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# SQL Query Patterns for IDC
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**Tested with:** idc-index 0.11.8 (IDC data version v23)
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**Tested with:** idc-index 0.11.9 (IDC data version v23)
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Quick reference for common SQL query patterns when working with IDC data. For detailed examples with context, see the "Core Capabilities" section in the main SKILL.md.
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references/use_cases.md

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# Common Use Cases for IDC
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**Tested with:** idc-index 0.11.8 (IDC data version v23)
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**Tested with:** idc-index 0.11.9 (IDC data version v23)
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This guide provides complete end-to-end workflow examples for common IDC use cases. Each use case demonstrates the full workflow from query to download with best practices.
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