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 qsiprep-toolgit 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/qsiprep-tool)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/qsiprep-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/qsiprep-tool/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/qsiprep-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/qsiprep-tool.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 93 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
- medium MCP Rug Pull · line 150 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00120 | $0.02937 |
| Opus 5 | $0.00060 | $0.01469 |
| Sonnet 5 | $0.00024 | $0.00587 |
| Haiku 4.5 | $0.00012 | $0.00294 |
Grade A, and why
qsiprep-tool 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 — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QSIPrep Tool (Interface Layer)
Overview
QSIPrep is a BIDS-App pipeline for diffusion MRI (DWI) preprocessing that emphasizes:
- Robust distortion/motion/eddy-current correction
- Interoperable derivatives for downstream modeling (DTI/DKI/CSD, tractography, connectome, etc.)
- Strong QC reporting (HTML)
This skill is the NeuroClaw interface-layer wrapper for QSIPrep and strictly follows the NeuroClaw safety pattern:
- Check whether QSIPrep is available (preferred: Docker/Singularity image; alternative: conda).
- If missing → invoke
dependency-plannerto produce an installation plan. - Verify inputs (must be BIDS-compliant; detect DWI + fieldmaps/reverse-PE b0 if present).
- Generate a clear numbered plan with exact commands, runtime/resource estimates, and risks.
- Wait for explicit user confirmation (“YES” / “execute” / “proceed”).
- On confirmation → delegate all commands to
claw-shell. - Summarize outputs (derivatives paths + QC report location) and suggest next steps.
Research use only.
What QSIPrep Typically Does (High-Level)
- Validates BIDS layout (or skips if requested)
- Creates brain mask(s)
- Denoising (optional), Gibbs unringing (optional)
- Susceptibility distortion correction (e.g., reverse phase-encoded b0 via topup-style approach)
- Eddy-current + motion correction (FSL eddy family behavior within containerized workflow)
- Gradient/bvec handling (rotation after motion correction)
- Coregistration to anatomical (and optionally standard space outputs)
- Produces derivatives + QC HTML reports
Quick Reference
| Task | Recommended Approach | Typical Output |
|---|---|---|
| Standard DWI preprocessing | QSIPrep BIDS-App participant |
derivatives/qsiprep/sub-*/dwi/*preproc_dwi.nii.gz |
| Multi-subject run | --participant-label sub-001 sub-002 ... |
per-subject derivatives |
| HPC / cluster | Singularity .sif execution |
same derivatives |
| QC | Default QSIPrep reports | derivatives/qsiprep/sub-*/figures/*.html |
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 · 320 lines · 120 tokens per session scan A 0a7426a49d21
qsiprep-tool is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (85 stars, last pushed 6d ago), licensed MIT. It adds 120 tokens to every session and 2,937 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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