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 imaging-genetics-modelsgit 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/imaging-genetics-models)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/imaging-genetics-models"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/imaging-genetics-models/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/imaging-genetics-models"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/imaging-genetics-models.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Output Handling · line 41 Model output is used without validation or sanitization. Unvalidated output injected into downstream contexts (SQL, shell, HTML) enables injection attacks and arbitrary code execution.Fix: Validate and sanitize all model output before using it in downstream contexts. Use parameterized queries for SQL, shell quoting for commands, and HTML encoding for web output.
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 | $0.00114 | $0.01035 |
| Opus 5 | $0.00057 | $0.00517 |
| Sonnet 5 | $0.00023 | $0.00207 |
| Haiku 4.5 | $0.00011 | $0.00103 |
Grade A, and why
imaging-genetics-models 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 12d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Imaging Genetics Models Skill
Overview
imaging-genetics-models provides matrix-based association, polygenic scoring,
and multivariate genotype-imaging analysis. It also builds explicit PLINK2
commands without embedding or redistributing the external executable.
Supported modes
| Mode | Required arrays | Output |
|---|---|---|
association |
genotype, phenotype |
covariate-adjusted variant tests |
lmm |
above plus kinship |
kinship-aware variant tests |
prs |
genotype, weights |
subject polygenic score |
pls |
X, Y |
paired latent components |
cca |
X, Y |
canonical variates |
Population structure, ancestry, batch, age, sex, site, and relatedness must be handled before genetic effects are interpreted.
Installation
pip install numpy pandas scipy scikit-learn statsmodels joblib
For genome-wide command-line analyses, install PLINK2 separately and execute the generated command through NeuroClaw's audited shell workflow.
Workflows
1. Variant-imaging association
Create an NPZ bundle:
genotype: [subjects, variants]
phenotype: [subjects] or [subjects, phenotypes]
variant_id: [variants] (optional)
covariates: [subjects, covariates] (optional)
kinship: [subjects, subjects] (required only for `lmm`)
python skills/imaging-genetics-models/scripts/train_reference.py \
--input imaging_genetics.npz \
--model association \
--output-dir run_models_output/imaging_gwas
Use --model lmm when the bundle contains a kinship matrix.
2. Polygenic score
genotype: [subjects, variants]
weights: [variants]
subject_id: [subjects] (optional)
python skills/imaging-genetics-models/scripts/train_reference.py \
--input prs_bundle.npz \
--model prs \
--output-dir run_models_output/prs
3. PLS or CCA
X: [subjects, genetic features]
Y: [subjects, imaging phenotypes]
python skills/imaging-genetics-models/scripts/train_reference.py \
--input imaging_genetics.npz \
--model cca \
--components 3 \
--output-dir run_models_output/cca
What ships with it
1 file 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.
- 12d ago First seen · 155 lines · 114 tokens per session scan A e763284fcfff
imaging-genetics-models is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (85 stars, last pushed 5d ago), licensed MIT. It adds 114 tokens to every session and 1,035 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 2026-08-30.
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…