Borrowing it
Nothing to install: this file belongs to zhangreling02-ai/3dslicer-claude-bridge. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhangreling02-ai/3dslicer-claude-bridge/main/.claude/commands/onco-spine.mdgit clone --depth 1 https://github.com/zhangreling02-ai/3dslicer-claude-bridgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/zhangreling02-ai/3dslicer-claude-bridge/onco-spine)<a href="https://agentmods.dev/commands/zhangreling02-ai/3dslicer-claude-bridge/onco-spine"><img src="https://agentmods.dev/badge/commands/zhangreling02-ai/3dslicer-claude-bridge/onco-spine/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/zhangreling02-ai/3dslicer-claude-bridge/onco-spine"><img src="https://agentmods.dev/badge/commands/zhangreling02-ai/3dslicer-claude-bridge/onco-spine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01226 |
| Opus 5 | $0.00000 | $0.00613 |
| Sonnet 5 | $0.00000 | $0.00245 |
| Haiku 4.5 | $0.00000 | $0.00123 |
Grade A, and why
onco-spine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/onco-spine - Oncologic Spine Assessment
Comprehensive assessment of metastatic spinal disease with SINS scoring.
Description
Detects metastatic lesions in the spine, calculates SINS (Spinal Instability Neoplastic Score), and provides treatment recommendations. Combines CT (required) and MRI (optional, improves accuracy) data.
Usage
/onco-spine # Full oncologic spine assessment
/onco-spine thoracic # Focus on thoracic region
Instructions
When the user invokes this command:
1. Inventory available data
Call list_scene_nodes(). CT is required. MRI (T1 + T2/STIR) is optional but improves lesion characterization and benign/malignant differentiation.
If no CT is found:
Oncologic spine assessment requires CT data.
MRI is optional but recommended for improved lesion characterization.
Please load CT DICOM series first.
2. Segment spine
segment_spine(input_node_id=<ct_id>, region=<region_or_full>)
3. Detect metastatic lesions on CT
detect_metastatic_lesions_ct(
volume_node_id=<ct_id>,
segmentation_node_id=<seg_id>,
include_posterior_elements=true,
include_sins=true
)
4. MRI assessment (if available)
If MRI T1 and T2/STIR volumes are loaded:
detect_metastatic_lesions_mri(
t1_volume_id=<t1_id>,
t2_or_stir_volume_id=<t2_id>,
segmentation_node_id=<seg_id>
)
MRI adds:
- Better soft tissue characterization
- Epidural disease assessment
- Cord compression evaluation
- Benign vs malignant fracture differentiation
5. SINS score calculation
For each level with detected lesions:
calculate_sins_score(
volume_node_id=<ct_id>,
segmentation_node_id=<seg_id>,
target_levels=<affected_levels>
)
Note: SINS includes a clinical pain component (0-3 points). If not provided by the user, the tool reports the score range (minimum without pain, maximum with mechanical pain). Ask the user:
For complete SINS scoring, please provide:
- Does the patient have pain at the affected level(s)? (yes/no)
- If yes, is it mechanical (worse with movement) or non-mechanical?
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 162 lines · 0 tokens per session scan A b8609ec0152d
onco-spine is a command published in the GitHub repository zhangreling02-ai/3dslicer-claude-bridge (0 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,226 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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