Contribute Skills Via Pr logo

Contribute Skills Via Pr

OrganizationPopular
NeuroAIHub
contribute-skills-via-pr

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

Overview

PublisherNeuroAIHub
RepositoryBrainPilot
Skill namecontribute-skills-via-pr
Stars
1.1K
Forks
74
Bundled files
Instructions only
LicenseAGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by NeuroAIHub on GitHub. Read the source before you install it.

Installation

Install the Contribute Skills Via Pr AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/01_Meta-Skills/contribute-skills-via-pr
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git /tmp/BrainPilot
mkdir -p .claude/skills
cp -r /tmp/BrainPilot/packages/skills/skills/01_Meta-Skills/contribute-skills-via-pr .claude/skills/contribute-skills-via-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Contribute Skills Via Pr in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Contribute Skills Via Pr on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Contribute Skills Via Pr is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Contribute Skills via PR

Purpose

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.

When to Use This Skill

Activate when the user:

  • Wants to contribute a skill to the NeuroAIHub community repository
  • Asks how to submit a PR to awesome_cognitive_and_neuroscience_skills
  • Wants to know the SKILL.md format or quality requirements for this repository
  • Asks about the review process or PR checklist for this repo

Research Planning Protocol

  1. State the contribution goal — What domain knowledge does the new skill encode? Is it a new skill, an improvement, or a verification?
  2. Check for overlap — Confirm the skill does not duplicate an existing one (see overlap checklist below).
  3. Declare the skill structure — Outline the sections and key parameters before writing.
  4. Note quality constraints — All numerical parameters need citations; no page numbers; under 500 lines.
  5. Present the plan and WAIT for user confirmation before writing the SKILL.md.

Verification Notice

This 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.

Step 1: Check for Overlap

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

Step 2: Write the SKILL.md

Required YAML Frontmatter

Skill name may only contain lowercase letters, numbers, and hyphens. The name must match the folder name.

yaml
---
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.

Required Sections (in this order)

  1. Purpose — What domain knowledge this skill encodes and why it is useful
  2. When to Use — Trigger conditions that activate this skill
  3. Research Planning Protocol — The standard 5-step preamble (copy template below)
  4. Verification Notice — The standard AI disclaimer (copy template below)
  5. Domain-specific content — The actual skill logic with cited parameters

Research Planning Protocol Template

markdown
## 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 Template

markdown
## 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.

Quality Rules

RuleRequirement
Skill nameLowercase letters, numbers, and hyphens only. Must match the folder name. e.g., my-new-skill
CitationsAll numerical parameters must have (Author, Year)
No page numbersUse (Luck, 2014) NOT (Luck, 2014, p. 187)
Line limitSKILL.md must be under 500 lines
Directory namekebab-case, must match the name field in YAML frontmatter
Commit prefixfeat:, fix:, docs:, or refactor:

Step 3: Submit via Git PR

bash
# 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

PR Template Checklist

When opening the PR, all items must be checked:

  • SKILL.md has required YAML frontmatter (name, description, review_status)
  • Includes Research Planning Protocol section
  • Includes Verification Notice section
  • All numerical parameters have (Author, Year) citations
  • Citations do not contain specific page numbers
  • SKILL.md is under 500 lines
  • Directory name uses kebab-case
  • Commit messages use conventional prefixes (feat:, fix:, docs:, etc.)

Alternative: No-Git Contribution

If you prefer not to use Git, use the contribute-skill meta-skill inside Claude Code:

  1. Say "contribute a skill" in Claude Code
  2. The meta-skill generates a SKILL.md interactively
  3. It submits the skill as a GitHub Issue with the community-skill label
  4. Maintainers review and merge on your behalf

After Submission

Maintainers may request changes such as:

  • Adding missing (Author, Year) citations
  • Removing page numbers from citations
  • Reducing line count if over 500
  • Clarifying the Research Planning Protocol or Verification Notice

Use the verify-skill meta-skill to self-review your SKILL.md before submitting to catch common issues early.

Frequently asked questions

What does the Contribute Skills Via Pr AI skill do?

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

Why use Contribute Skills Via Pr on TypingMind?

Because you install it once and use it with any model. Contribute Skills Via Pr is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Contribute Skills Via Pr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/01_Meta-Skills/contribute-skills-via-pr. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Contribute Skills Via Pr?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Contribute Skills Via Pr?

As many as you like. As long as a model supports skills, you can use Contribute Skills Via Pr with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Contribute Skills Via Pr AI skill free?

Yes. It is published on GitHub by NeuroAIHub under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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