skills/contribute-skills-via-pr/SKILL.md
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
npx skillsauth add haoxuanlithuai/awesome_cognitive_and_neuroscience_skills contribute-skills-via-prInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill encodes the complete workflow for contributing a new skill to the NeuroAIHub/awesome_cognitive_and_neuroscience_skills repository via GitHub Pull Request. It covers SKILL.md format requirements, quality rules enforced by maintainers, the PR submission process, and the no-Git alternative.
Activate when the user:
awesome_cognitive_and_neuroscience_skillsThis skill was generated by AI from direct inspection of the NeuroAIHub/awesome_cognitive_and_neuroscience_skills repository (April 2026). Repository requirements may change — always check the current CONTRIBUTING.md before submitting. If you find errors, please open an issue.
Before writing, verify your skill does not duplicate an existing one. Current skills include (41 total):
eeg-preprocessing-pipeline-guide, erp-analysis, mne-python-guide, fmri-preprocessing-pipeline-guide, fmri-glm-analysis-guide, fmri-task-design-guide, brain-connectivity-modeler, neural-decoding-analysis, neural-population-analysis-guide, calcium-imaging-analysis-guide, lesion-symptom-mapping-guide, optogenetics-protocol-designer, spiking-network-model-builder, drift-diffusion-model, bayesian-cognitive-model-builder, act-r-model-builder, evidence-accumulation-selector, parameter-recovery-checker, signal-detection-analysis, cogsci-statistics, cogsci-power-analysis, cogsci-visualization, neuroimaging-power-guide, neuroimaging-sample-size-calculator, cognitive-paradigm-design, eeg-paradigm-designer, divergent-thinking-scoring, alternative-uses-task-designer, creativity-self-efficacy-mediation, reading-time-analysis, self-paced-reading-designer, sentence-stimulus-norming, infant-looking-time-designer, tom-task-selector, neuropsych-battery-selector, visual-search-array-generator, research-literacy, paper-to-skill, contribute-skill, verify-skill, share-case
Skill name may only contain lowercase letters, numbers, and hyphens. The name must match the folder name.
---
name: "my-skill-name"
description: "One-sentence summary of the domain knowledge encoded"
domain: "your-domain"
version: "1.0.0"
authors:
- "Your Name"
papers:
- "Author et al., Year"
dependencies:
required:
- research-literacy
review_status: "ai-generated"
---
Mandatory fields: name, description, review_status. All others are recommended.
## Research Planning Protocol
1. **State the research question** — ...
2. **Justify the method choice** — ...
3. **Declare expected outcomes** — ...
4. **Note assumptions and limitations** — ...
5. **Present the plan to the user and WAIT for confirmation** before proceeding.
## Verification Notice
> This skill was generated by AI from academic literature. All parameters,
> thresholds, and citations require independent verification before use in
> research. If you find errors, please open an issue at
> https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills/issues.
| Rule | Requirement |
|------|-------------|
| Skill name | Lowercase letters, numbers, and hyphens only. Must match the folder name. e.g., my-new-skill |
| Citations | All numerical parameters must have (Author, Year) |
| No page numbers | Use (Luck, 2014) NOT (Luck, 2014, p. 187) |
| Line limit | SKILL.md must be under 500 lines |
| Directory name | kebab-case, must match the name field in YAML frontmatter |
| Commit prefix | feat:, fix:, docs:, or refactor: |
# 1. Fork on GitHub, then clone your fork
git clone https://github.com/<your-username>/awesome_cognitive_and_neuroscience_skills.git
cd awesome_cognitive_and_neuroscience_skills
# 2. Create a feature branch
git checkout -b feat/<skill-name>
# 3. Create skill directory and add files
mkdir -p skills/<skill-name>
# copy your SKILL.md into skills/<skill-name>/SKILL.md
# optionally: mkdir skills/<skill-name>/references
# 4. Commit and push
git add skills/<skill-name>/
git commit -m "feat: add <skill-name> skill for <one-line description>"
git push origin feat/<skill-name>
# 5. Open PR on GitHub against the master branch
When opening the PR, all items must be checked:
name, description, review_status)(Author, Year) citationsfeat:, fix:, docs:, etc.)If you prefer not to use Git, use the contribute-skill meta-skill inside Claude Code:
community-skill labelMaintainers may request changes such as:
(Author, Year) citationsUse the verify-skill meta-skill to self-review your SKILL.md before submitting to catch common issues early.
tools
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 convert a library/tool/framework into reusable skill documentation. Also trigger when users say things like 'make a skill from this repo', 'turn this codebase into a skill', or 'I want a skill for [library name]'.
development
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 viewers, volume-to-surface mapping, FreeSurfer/fMRIPrep integration, ROI management, and surface analysis. Use this skill whenever the user mentions pycortex, `import cortex`, cortical surfaces, brain flatmaps, WebGL brain viewers, cortical surface mapping, or wants to visualize neuroimaging data on the cortex, even if they don't explicitly name pycortex.
development
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 decomposition, source localization, decoding/MVPA, statistical testing, simulation, and visualization. Use this skill whenever the user works with EEG/MEG/sEEG/ECoG/NIRS/eye-tracking data in Python, mentions MNE, or needs neurophysiological analysis guidance.
testing
Specifies display parameters, set sizes, target-distractor similarity, and randomization constraints for visual search experiments