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SkillsMP has collected 69 skills from NeuroAIHub/BrainPilot. Open a skill to review its source and details.
Showing 40 of 69 collected skills.
Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference. Use when claims depend on code, trained artifacts, evaluators, or deployable entry points.
Audit scientific data semantics, sample and label alignment, leakage, group splits, preprocessing boundaries, and train-to-inference transforms. Use for any result based on datasets, feature matrices, tensors, repeated observations, or learned preprocessing.
Audit numeric, artifact, log, citation, and cross-report claims against inspectable evidence. Use for reports, syntheses, benchmark claims, external citations, or conflicting Expert outputs.
Coordinate iterative evidence and reliability reviews between BrainPilot's Principal Investigator and Auditor. Use when PI needs to audit its own draft, an Expert result, or a multi-agent synthesis; when Auditor receives such a review task; or when a previous…
Audit whether method discovery, comparison, representative real-data validation, collapse diagnostics, pruning, and selection evidence support claims of suitability or superiority. Use for research-method selection, empirical evaluation, benchmarking,…
Create or update the canonical Markdown inventory of task-relevant research data. Engineer must invoke this skill before creating or updating any data inventory, data contract, or dataset-coverage summary that downstream agents will use.
Research a bounded factual, documentation, API, or literature question from authoritative sources and save a self-contained Markdown report with claim-level citations. Use for reading-heavy evidence gathering, not experiment execution or data analysis.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Use when executing implementation plans with independent tasks in the current session
Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions
Use when you have a spec or requirements for a multi-step task, before touching code
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Curate BrainPilot Trace Events into human-readable research Episodes, appropriately granular nodes, and direct depends_on relationships. Use when a report contains multiple settings, results, analyses, visualizations, findings, or conclusions; when Episode…
Domain knowledge for building extracellular electrophysiology pipelines with SpikeInterface: loading data with extractors, preprocessing, running spike sorters, post-processing via SortingAnalyzer, quality metrics, curation, comparison, visualization, and…
Preprocess task-based or resting-state fMRI data with fMRIPrep — a robust, BIDS-App preprocessing pipeline built on FSL, ANTs, FreeSurfer, AFNI, and Nilearn. Use this skill whenever the user asks to preprocess fMRI/BOLD data, run fMRIPrep on a BIDS dataset,…
Domain-validated guidance for network neuroscience analysis using netneurotools: datasets, brain network metrics, connectivity consensus, modularity, spatial statistics, null models, and cortical surface visualization. Use this skill whenever the user works…
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical…
Query Open Targets Platform for target-disease associations, drug target discovery, tractability/safety data, genetics/omics evidence, known drugs, for therapeutic target identification.
Checks whether the uv Python package manager is installed and installs it if missing. Ensures uv is on PATH. Use when another skill requires uv as a prerequisite.
Toolbox for markerless animal pose estimation with DeepLabCut. Covers single/multi-animal tracking, SuperAnimal pretrained models, 2D/3D pose estimation, keypoint labeling GUI, model training/evaluation, video analysis, and behavioral quantification. Use when…
One-command skill contribution — generate a SKILL.md from your domain expertise and submit to GitHub Issues for maintainer review
Step-by-step guidance for contributing a new skill to the NeuroAIHub/awesome_cognitive_and_neuroscience_skills repository via GitHub Pull Request, including SKILL.md format requirements, quality rules, and PR checklist
Interactive skill that guides extraction of research paradigms and methodological techniques from cognitive science papers into structured, reusable skills
Convert a GitHub repository or local codebase into a well-structured Claude Code skill with progressive disclosure. Use this skill whenever the user provides a GitHub URL or local repo path and asks to turn it into a skill, create a skill from a repo, or…
One-command community case sharing — capture research context from your session and submit to GitHub Discussions
Generate and share anonymized skill usage statistics to help the community understand which skills are most valuable
Interactive skill verification — assess accuracy of parameters, citations, and methodology through structured expert review
Domain-specific statistical power analysis guidance for cognitive and neuroscience research, encoding effect size priors and sample size recommendations by modality
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
Domain-specific visualization best practices for cognitive and neuroscience data, encoding plot type selection, color standards, and publication formatting
Core scientific methodology principles: research planning, method justification, assumption checking, and human-in-the-loop decision making for cognitive science and neuroscience
Domain-validated guidance for designing Alternative Uses Task (AUT) experiments measuring divergent thinking, with parameters for AI-augmented and traditional conditions
Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions
Domain-validated guidance for SEM-based mediation analysis of creative self-efficacy and moderation by baseline creativity in AI-augmented creativity research
Domain-validated multi-dimensional scoring system for divergent thinking tasks, including fluency, flexibility, originality, and automated semantic distance methods
Expert guidance on selecting, fitting, and evaluating drift-diffusion models for two-choice response time data in cognitive science
Advises on when to use DDM vs. LBA vs. race models for choice-RT data based on experimental design and research goals
Domain-validated decision logic, formulas, and interpretation guidelines for applying Signal Detection Theory to cognitive science data