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/fracture-eval.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/fracture-eval)<a href="https://agentmods.dev/commands/zhangreling02-ai/3dslicer-claude-bridge/fracture-eval"><img src="https://agentmods.dev/badge/commands/zhangreling02-ai/3dslicer-claude-bridge/fracture-eval/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/fracture-eval"><img src="https://agentmods.dev/badge/commands/zhangreling02-ai/3dslicer-claude-bridge/fracture-eval.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 | $0.00988 |
| Opus 5 | $0.00000 | $0.00494 |
| Sonnet 5 | $0.00000 | $0.00198 |
| Haiku 4.5 | $0.00000 | $0.00099 |
Grade A, and why
fracture-eval 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 10d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/fracture-eval - Vertebral Fracture Evaluation
Automated vertebral fracture detection and classification.
Description
Detects and classifies vertebral fractures using CT and/or X-ray data. Applies AO Spine, Denis, and Genant classification systems. Includes osteoporosis screening and canal compromise assessment.
Usage
/fracture-eval # Auto-detect modality and evaluate
/fracture-eval ct # CT-specific pipeline
/fracture-eval xray # X-ray-specific pipeline
Instructions
When the user invokes this command:
1. Inventory available data
Call list_scene_nodes() to identify CT volumes, X-ray volumes, and existing segmentations.
Determine modality:
- If
$ARGUMENTSspecifies "ct" or "xray", use that pipeline - If not specified, auto-detect from loaded volumes
- If both CT and X-ray available, run CT pipeline (more comprehensive)
2. CT Pipeline
2a. Segment spine
segment_spine(input_node_id=<ct_id>)
2b. Detect fractures
detect_vertebral_fractures_ct(
volume_node_id=<ct_id>,
segmentation_node_id=<seg_id>,
classification_system="all"
)
2c. Osteoporosis screening
assess_osteoporosis_ct(
volume_node_id=<ct_id>,
segmentation_node_id=<seg_id>,
levels=["L1"]
)
2d. Canal assessment (if burst fracture detected)
If any fracture has AO type A3, A4, B, or C (posterior wall or canal involvement):
measure_spinal_canal_ct(
volume_node_id=<ct_id>,
segmentation_node_id=<seg_id>,
levels=<fractured_levels>
)
2e. Screenshots
capture_screenshot(view_type="sagittal") # Sagittal at fracture level
capture_screenshot(view_type="axial") # Axial at fracture level
2f. CT Report
VERTEBRAL FRACTURE EVALUATION (CT)
FRACTURES DETECTED: [count]
Per level:
[LEVEL]:
Genant: Grade [0-3] ([morphology]) - [height loss %]
AO Spine: [Type] - [description]
Denis: [stability status]
Canal compromise: [% if applicable]
Posterior elements: [status]
OSTEOPOROSIS SCREENING:
L1 trabecular HU: [value]
Classification: [normal/osteopenia/osteoporosis]
Screw pullout risk: [LOW/MODERATE/HIGH]
CANAL STATUS (if burst):
Retropulsion: [mm]
Canal compromise: [%]
Neurological risk: [assessment]
CLINICAL SUMMARY:
Most severe: [level] [AO type]
Stability: [STABLE/UNSTABLE]
Recommendation: [conservative/surgical]
If osteoporotic: [cement augmentation consideration]
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.
- 10d ago First seen · 145 lines · 0 tokens per session scan A abe4632470d8
fracture-eval 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 988 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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