skills/share-case/SKILL.md
One-command community case sharing — capture research context from your session and submit to GitHub Discussions
npx skillsauth add haoxuanlithuai/awesome_cognitive_and_neuroscience_skills share-caseInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
This meta-skill captures a researcher's experience using any skill in this repository and submits it as a structured case to GitHub Discussions. It handles all formatting and submission so users never need to leave their terminal or know Git.
Activate when the user:
Before starting the case sharing process, you MUST:
For detailed methodology guidance, see skills/research-literacy/SKILL.md.
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.
This skill supports two submission methods:
Direct submission via gh CLI (Recommended)
gh CLI installed and authenticatedgh auth status to checkgh auth loginManual submission via web browser
gh CLI requiredThe skill will check for gh availability and let the user choose their preferred method.
GitHub Discussions must be enabled on the repository. The skill submits to the "Show & Tell" category.
Present these questions using multiple-choice format:
Q1: Which skill did you use?
Q2: What was your research scenario?
Q3: How helpful was the skill? (1-5)
Q4: What was most valuable? (select all that apply)
Extract the following from the current conversation:
Format each as a concise paragraph. Do NOT include raw conversation transcripts — synthesize into readable summaries.
Display the complete case preview using the format below.
First, check gh CLI availability:
gh auth status 2>&1
Then present submission options using AskUserQuestion:
If gh is available:
If gh is NOT available:
You MUST wait for explicit user confirmation before proceeding to Step 4.
Based on the user's choice in Step 3:
gh CLICreate a GitHub Discussion in the "Show & Tell" category.
First, get repository and category IDs:
gh api graphql -f query='
{
repository(owner: "HaoxuanLiTHUAI", name: "awesome_cognitive_and_neuroscience_skills") {
id
discussionCategories(first: 10) {
nodes {
id
name
}
}
}
}'
Then create the discussion:
gh api graphql -f query='
mutation {
createDiscussion(input: {
repositoryId: "REPO_ID",
categoryId: "SHOW_AND_TELL_CATEGORY_ID",
title: "Community Case: SKILL_NAME",
body: "CASE_BODY_HERE"
}) {
discussion {
url
}
}
}'
On success, display the Discussion URL:
✅ Case shared successfully!
🔗 Discussion URL: [URL]
Thank you for contributing to the community!
On failure, fall back to Option B.
Save the case locally to the current directory as case-skill-name-YYYYMMDD.md
Open the GitHub Discussions page:
xdg-open "https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell" 2>/dev/null || \
open "https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell" 2>/dev/null || \
echo "Please open: https://github.com/HaoxuanLiTHUAI/awesome_cognitive_and_neuroscience_skills/discussions/new?category=show-and-tell"
✅ Case saved to: case-skill-name-YYYYMMDD.md
🌐 Opening GitHub Discussions in your browser...
📋 Next steps:
1. Title: "Community Case: [Skill Name]"
2. Copy the content from case-skill-name-YYYYMMDD.md
3. Paste it into the discussion body
4. Click "Start discussion"
Thank you for contributing to the community!
The submitted Discussion body uses this format:
## Community Case: [skill-name]
### Quick Info
- **Skill used**: `[skill-name]`
- **Scenario**: [selected option from Q2]
- **Rating**: [stars from Q3, e.g., ⭐⭐⭐⭐]
- **Most valuable**: [selected options from Q4]
### Research Context
> [User's research question and experimental setup — synthesized from conversation]
### What the Skill Suggested
- [Key recommendation 1]
- [Key recommendation 2]
- [Key recommendation 3]
### What I Actually Did & Result
> [User's experience applying the recommendations and the outcome]
### User's Tips
> [Optional: Additional insights the user wants to share with the community]
---
*Submitted via the `share-case` meta-skill.*
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.
development
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