Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add CUHK-AIM-Group/NeuroClaw --skill nibabel-skillgit clone --depth 1 https://github.com/CUHK-AIM-Group/NeuroClawWrote 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/skills/cuhk-aim-group/neuroclaw/nibabel-skill)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/nibabel-skill"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/nibabel-skill/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/skills/cuhk-aim-group/neuroclaw/nibabel-skill"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/nibabel-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00124 | $0.01779 |
| Opus 5 | $0.00062 | $0.00890 |
| Sonnet 5 | $0.00025 | $0.00356 |
| Haiku 4.5 | $0.00012 | $0.00178 |
Grade A, and why
nibabel-skill 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 9d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nibabel Skill
Overview
nibabel-skill is the NeuroClaw tool skill for low-level neuroimaging file I/O and geometry handling.
It is the right skill when the task is about reading or writing NIfTI data, checking image dimensions and affine matrices, extracting atlas-space coordinates, or interacting with FreeSurfer surface and annotation files.
This skill is intentionally narrower than nilearn-tool and brain-visualization:
nibabel-skillfocuses on file structures, affines, voxel/world coordinates, and surface geometry I/Onilearn-toolfocuses on signal processing, masking, ROI time series, and statistical image workflowsbrain-visualizationfocuses on final figure generation and mesh export workflows
The content is distilled from nibabel-centric patterns that appear repeatedly in rs-fMRI-Pipeline-Tutorial/, especially:
- NIfTI discovery and validation in the multimodal pipeline
- affine-based ROI center conversion in zALFF regional summaries
- FreeSurfer geometry and annotation loading for colored surface export
Agent Reference Rule
When the agent needs nibabel-based code, it should start from the curated snippets in skills/nibabel-skill/scripts/ instead of copying tutorial files with hard-coded paths.
Reference snippets available:
scripts/nifti_inspection_reference.py-> load NIfTI, inspect shape/dtype/affine, save a copied imagescripts/atlas_coordinate_reference.py-> compute atlas ROI centers and convert voxel coordinates to world coordinatesscripts/freesurfer_io_reference.py-> read FreeSurfer geometry/annotation and summarize mesh/color-table metadata
Quick Reference
| Task | What it does | Typical input | Expected output |
|---|---|---|---|
| NIfTI inspection | Loads an image and reports shape, dtype, affine, zooms | .nii / .nii.gz |
metadata summary |
| NIfTI save/export | Saves processed arrays back to NIfTI with an affine | array + affine | output image |
| Atlas coordinate extraction | Converts ROI voxel centers to atlas/world coordinates | labeled atlas NIfTI | CSV / printed coordinates |
| FreeSurfer surface I/O | Reads .pial, .white, .annot and summarizes geometry |
surface + annot files | geometry summary |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 184 lines · 124 tokens per session scan A 38fd841ee6f9
nibabel-skill is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (85 stars, last pushed 6d ago), licensed MIT. It adds 124 tokens to every session and 1,779 once invoked, about $0.0006 per session on Opus 5. 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 2026-09-03.
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