GitHub organization
Agent skills by NeuroAIHub
- skills
- 59
- repository
- 1
Repositories by NeuroAIHub
Skills by NeuroAIHub, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Toolbox for markerless animal pose estimation with DeepLabCut. | NeuroAIHub/ | 1k | — | ~1.7k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 2 | 2.Fmriprep Preprocess task-based or resting-state fMRI data with fMRIPrep — a robust, BIDS-App preprocessing pipeline built on FSL, ANTs, FreeSurfer, AFNI, and Nilearn. | NeuroAIHub/ | 1k | — | ~4.1k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 3 | Domain-validated pipeline guidance for EEG/MEG data analysis using MNE-Python: data loading, preprocessing (filtering, ICA, re-referencing), epoching, ERP/ERF computation, time-frequency… | NeuroAIHub/ | 1k | — | ~2.3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 4 | Domain-validated guidance for network neuroscience analysis using netneurotools: datasets, brain network metrics, connectivity consensus, modularity, spatial statistics, null models, and cortical… | NeuroAIHub/ | 1k | — | ~2.6k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 5 | Submission-grade Nature/high-impact journal figure workflow for Python or R. | NeuroAIHub/ | 1k | 1 repo | ~1.3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 6 | Domain-validated guidance for cortical surface visualization and brain surface rendering of fMRI data using pycortex: data types (Volume, Vertex, Dataset), 2D cortical flatmaps, 3D WebGL brain… | NeuroAIHub/ | 1k | — | ~1.6k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 7 | Guide AI agents to write beautifully formatted, well-illustrated Markdown reports with proper structure, diagrams, and compatibility across GitHub and Obsidian. | NeuroAIHub/ | 1k | — | ~2.6k | Automated safety check: Warn | AGPL-3.0 | 5 days ago |
| 8 | Convert a GitHub repository or local codebase into a well-structured Claude Code skill with progressive disclosure. | NeuroAIHub/ | 1k | — | ~2.5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 9 | Guides ACT-R cognitive model construction: chunk types, production rules, subsymbolic parameters, and model validation | NeuroAIHub/ | 1k | — | ~3.7k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 10 | Domain-validated guidance for designing Alternative Uses Task (AUT) experiments measuring divergent thinking, with parameters for AI-augmented and traditional conditions | NeuroAIHub/ | 1k | — | ~3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 11 | Coordinate iterative evidence and reliability reviews between BrainPilot's Principal Investigator and Auditor. | NeuroAIHub/ | 1k | — | ~467 | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 12 | Domain-validated pipeline guidance for calcium imaging data analysis: motion correction, ROI extraction, neuropil correction, spike inference, and quality control | NeuroAIHub/ | 1k | — | ~4.4k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 13 | Domain-specific statistical power analysis guidance for cognitive and neuroscience research, encoding effect size priors and sample size recommendations by modality | NeuroAIHub/ | 1k | — | ~3.4k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 14 | Domain-validated guidance for SEM-based mediation analysis of creative self-efficacy and moderation by baseline creativity in AI-augmented creativity research | NeuroAIHub/ | 1k | — | ~3.5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 15 | Curate BrainPilot Trace Events into human-readable research Episodes, appropriately granular nodes, and direct dependson relationships. | NeuroAIHub/ | 1k | — | ~1.1k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 16 | Domain-validated multi-dimensional scoring system for divergent thinking tasks, including fluency, flexibility, originality, and automated semantic distance methods | NeuroAIHub/ | 1k | — | ~3.5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 17 | Expert guidance on selecting, fitting, and evaluating drift-diffusion models for two-choice response time data in cognitive science | NeuroAIHub/ | 1k | — | ~3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 18 | 18.Erp Analysis Domain-validated pipeline and parameter guidance for event-related potential analysis, from preprocessing through statistical testing | NeuroAIHub/ | 1k | — | ~2.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 19 | Advises on when to use DDM vs. An agent skill from NeuroAIHub/BrainPilot. | NeuroAIHub/ | 1k | — | ~4.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 20 | Domain-validated guidance for fMRI preprocessing decisions: motion correction, slice timing, spatial normalization, smoothing, confound regression, and quality control | NeuroAIHub/ | 1k | — | ~4.7k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 21 | Guides fMRI task design: block vs. An agent skill from NeuroAIHub/BrainPilot. | NeuroAIHub/ | 1k | — | ~4.2k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 22 | Designs habituation and preferential-looking paradigms with age-appropriate timing parameters and exclusion criteria | NeuroAIHub/ | 1k | — | ~4.5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 23 | Domain-validated methods and decision logic for neural decoding, RSA, temporal generalization, and encoding models in systems neuroscience | NeuroAIHub/ | 1k | — | ~4.9k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 24 | Guides dimensionality reduction and latent-variable analysis of neural populations (PCA, GPFA, dPCA) | NeuroAIHub/ | 1k | — | ~4.5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 25 | Sample-size planning for fMRI/EEG studies using effect-size benchmarks and simulation-based power | NeuroAIHub/ | 1k | — | ~5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 26 | Guides parameter recovery studies to validate model identifiability before trusting fitted parameter values | NeuroAIHub/ | 1k | — | ~3.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 27 | Guides analysis of eye-tracking reading measures including first fixation, gaze duration, regression path, and total reading time | NeuroAIHub/ | 1k | — | ~4.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 28 | Domain-validated decision logic, formulas, and interpretation guidelines for applying Signal Detection Theory to cognitive science data | NeuroAIHub/ | 1k | — | ~4k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 29 | Assists building spiking neural network simulations: neuron models, connectivity, plasticity rules | NeuroAIHub/ | 1k | — | ~5.1k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 30 | Audit whether method discovery, comparison, representative real-data validation, collapse diagnostics, pruning, and selection evidence support claims of suitability or superiority. | NeuroAIHub/ | 1k | — | ~1.7k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 31 | Advises on functional/effective connectivity methods: PPI, DCM, Granger causality, graph theory | NeuroAIHub/ | 1k | — | ~6k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 32 | Domain-specific statistical modeling guidance for cognitive science and neuroscience, encoding when and how to apply mixed models, correction methods, Bayesian approaches, and effect size reporting | NeuroAIHub/ | 1k | — | ~5.3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 33 | One-command skill contribution — generate a SKILL.md from your domain expertise and submit to GitHub Issues for maintainer review | NeuroAIHub/ | 1k | — | ~2.3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 34 | Step-by-step guidance for contributing a new skill to the NeuroAIHub/awesomecognitiveandneuroscienceskills repository via GitHub Pull Request, including SKILL.md format requirements, quality rules… | NeuroAIHub/ | 1k | — | ~1.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 35 | Guides EEG preprocessing: filtering, artifact rejection (ICA/ASR), re-referencing, interpolation | NeuroAIHub/ | 1k | — | ~5.9k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 36 | Domain-validated guidance for fMRI General Linear Model specification: HRF modeling, design matrix construction, contrast definition, confound regression, and statistical inference | NeuroAIHub/ | 1k | — | ~5.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 37 | Advises on lesion-symptom mapping methods: VLSM, disconnection analysis, network lesion mapping | NeuroAIHub/ | 1k | — | ~5.3k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 38 | Simulation-based sample-size planning for neuroimaging studies using effect-size maps | NeuroAIHub/ | 1k | — | ~5.2k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 39 | Interactive skill that guides extraction of research paradigms and methodological techniques from cognitive science papers into structured, reusable skills | NeuroAIHub/ | 1k | — | ~6k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 40 | Expert guidance for designing self-paced reading experiments: region segmentation, timing parameters, comprehension probes, and spillover analysis | NeuroAIHub/ | 1k | — | ~5.2k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 41 | Specifies norming procedures for linguistic stimuli including cloze probability, plausibility ratings, acceptability judgments, and lexical controls | NeuroAIHub/ | 1k | — | ~5.8k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 42 | 42.Share Case One-command community case sharing — capture research context from your session and submit to GitHub Discussions | NeuroAIHub/ | 1k | — | ~1.9k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 43 | 43.Share Usage Generate and share anonymized skill usage statistics to help the community understand which skills are most valuable | NeuroAIHub/ | 1k | — | ~3.2k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 44 | Domain knowledge for building extracellular electrophysiology pipelines with SpikeInterface: loading data with extractors, preprocessing, running spike sorters, post-processing via SortingAnalyzer… | NeuroAIHub/ | 1k | — | ~6.5k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 45 | Selects Theory of Mind tasks matched to target population, age, and construct with psychometric guidance | NeuroAIHub/ | 1k | — | ~5.7k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 46 | 46.Verify Skill Interactive skill verification — assess accuracy of parameters, citations, and methodology through structured expert review | NeuroAIHub/ | 1k | — | ~3.2k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 47 | Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions | NeuroAIHub/ | 1k | — | ~3.9k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
| 48 | Domain-specific visualization best practices for cognitive and neuroscience data, encoding plot type selection, color standards, and publication formatting | NeuroAIHub/ | 1k | — | ~4.6k | Automated safety check: Pass | AGPL-3.0 | 5 days ago |
Questions, answered from the data.
What is the best skill by NeuroAIHub?
Deeplabcut from NeuroAIHub/BrainPilot ranks first of the 59 skills by NeuroAIHub listed here, with the highest score: its repository has 1k GitHub stars, its SKILL.md loads about 1.7k tokens and it passes the automated safety check with no findings. Next come Fmriprep and Mne Python Guide.
Are NeuroAIHub's skills official?
None yet. All 59 skills by NeuroAIHub listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.