Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/fmriprep-tool)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/fmriprep-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/fmriprep-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/fmriprep-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/fmriprep-tool.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 | $0.00096 | $0.02072 |
| Opus 5 | $0.00048 | $0.01036 |
| Sonnet 5 | $0.00019 | $0.00414 |
| Haiku 4.5 | $0.00010 | $0.00207 |
Grade A, and why
fmriprep-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 11d 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, check=True) How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fMRIPrep Tool
Overview
fMRIPrep is a robust, standardized preprocessing pipeline for BIDS-compliant functional and anatomical MRI data. It performs best-practice steps including anatomical segmentation, functional motion correction, susceptibility distortion correction, coregistration, normalization to standard space, and generates comprehensive QC reports.
This skill serves as the NeuroClaw interface-layer wrapper for fMRIPrep and strictly follows the hierarchical design:
- Check whether fMRIPrep and its dependencies (Docker or Singularity) are installed.
- If missing → invoke
dependency-plannerto generate a safe installation plan. - Detect input BIDS dataset structure and confirm output directory.
- Generate a clear, numbered execution plan with exact command, flags, estimated runtime, and risks.
- Present the plan and wait for explicit user confirmation (“YES” / “execute” / “proceed”).
- On confirmation → delegate the entire pipeline execution to
claw-shell. - After completion, summarize outputs, highlight QC reports, and suggest next steps (e.g., feeding results into analysis or paper-writing).
Research use only.
Quick Reference
| Task | Recommended Command / Approach | Typical Runtime (per subject) |
|---|---|---|
| Full fMRIPrep pipeline | fmriprep bids_dir output_dir participant --fs-license-file license.txt |
2–8 hours |
| Anatomical only | --anat-only |
30–90 min |
| Functional only (after anat) | --bold-only |
1–4 hours |
| Use FreeSurfer recon-all | --fs-subjects-dir /path/to/fs |
+2–6 hours |
| Skip susceptibility distortion | --ignore fieldmaps |
Reduces time |
| Low memory mode | --mem-mb 8000 --nthreads 4 |
For limited resources |
| Generate detailed QC reports | Default behavior (outputs in sub-*/figures/ and reports/) |
Included |
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.
- 11d ago First seen · 228 lines · 96 tokens per session scan A 8a463617afe6
fmriprep-tool is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (84 stars, last pushed 4d ago), licensed MIT. It adds 96 tokens to every session and 2,072 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.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…