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 hcppipeline-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/hcppipeline-tool)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/hcppipeline-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/hcppipeline-tool.svg" alt="Measured on agentmods" 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 | $0.00106 | $0.02279 |
| Opus 5 | $0.00053 | $0.01140 |
| Sonnet 5 | $0.00021 | $0.00456 |
| Haiku 4.5 | $0.00011 | $0.00228 |
Grade A, and why
hcppipeline-tool scanned grade A with 1 finding 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 8d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run(cmd, env=env, check=True) How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HCP Pipeline Tool
Overview
The HCP Pipelines are the official, highly optimized preprocessing pipelines developed by the Human Connectome Project. They provide state-of-the-art processing for structural (T1w/T2w), functional (task/resting-state fMRI with ICA-FIX), and diffusion MRI (topup + eddy + bedpostx + probtrackx + MSMAll surface alignment).
This skill serves as the NeuroClaw interface-layer wrapper for the HCP Pipelines and strictly follows the hierarchical design:
- Check whether HCP Pipelines and dependencies are installed.
- If missing → invoke
dependency-plannerto generate a safe installation plan. - Detect input data (preferably BIDS or HCP-style organized) and confirm processing stages.
- Generate a clear, numbered execution plan with exact commands, flags, estimated runtime, and risks.
- Present the plan and wait for explicit user confirmation (“YES” / “execute” / “proceed”).
- On confirmation → delegate all pipeline stages to
claw-shell. - After completion, summarize outputs and suggest next steps (e.g., connectivity analysis via
fmri-skillorfsl-tool).
Research use only.
Quick Reference
| Task | Recommended Pipeline Stage | Typical Runtime (per subject) |
|---|---|---|
| Structural preprocessing | PreFreeSurfer + FreeSurfer + PostFreeSurfer | 4–12 hours |
| Functional preprocessing | fMRIVolume + fMRISurface + ICA-FIX | 2–6 hours |
| Diffusion preprocessing | DiffusionPreprocessing + bedpostx + probtrackx | 6–24 hours |
| Surface-based registration | MSMAll | 2–4 hours |
| Full HCP-style multimodal pipeline | All stages combined | 12–36+ hours |
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.
- 8d ago First seen · 217 lines · 106 tokens per session scan A 5e46935b6045
hcppipeline-tool is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (83 stars, last pushed 2d ago), licensed MIT. It adds 106 tokens to every session and 2,279 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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