Bio Digital Pathology Wsi
全切片病理图像 WSI 处理 skill。用于 H&E/IHC/mIF whole-slide image 的组织检测、tile extraction、stain normalization、slide QC、tile-level 特征、病理 ML 数据集准备和报告交接。
Install
$ agentstack add skill-onescience-ai-oneskills-digital-pathology-wsi ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-onescience-ai-oneskills-digital-pathology-wsi) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
全切片病理图像处理
使用边界
用于 SVS/NDPI/MRXS/OME-TIFF 等 WSI 的 tile 提取、组织 mask、颜色标准化、QC 和病理图像机器学习交接。若是单张显微图像或细胞核分割，读取 ../bioimage-segmentation/SKILL.md。
可复用资源
onescience-coder/assets/bio_cell_imaging_templates/wsi_tile_plan.yaml：slide manifest、tile size、magnification、tissue filter、stain normalization 和 QC 模板。references/wsi_processing_qc.md：WSI 维度、level、MPP、tile 策略、颜色和数据泄漏风险。
推荐流程
- 建 slide manifest：case、slide id、stain、scanner、MPP、label、split。
- Slide QC：空白、模糊、折叠、pen mark、组织比例、扫描 level。
- Tissue mask：低倍图阈值或模型，确定 tile inclusion rule。
- Tile extraction：tile size、overlap、magnification、背景过滤、坐标记录。
- 预处理：stain normalization、颜色增强、artifact filter。
- 输出：tile manifest、QC report、thumbnail overlay、case-level split 和 ML 交接。
交接物
bio_task_family: cell-imaging-cytometry
cell_task: digital-pathology-wsi
slide_manifest:
stain_and_scanner:
tile_strategy:
tissue_detection:
stain_normalization:
qc_filters:
case_split:
expected_outputs:
execution_entry:禁止事项
- 不要按 tile 随机划分训练/测试；必须按 patient/case/slide 防泄漏。
- 不要在未固定 magnification/MPP 时比较 morphology feature。
- 不要丢失 tile 到 slide/case 的坐标和层级映射。
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: onescience-ai
- Source: onescience-ai/OneSkills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.