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Github Issues

Community
AlexAI-MCP
github-issues

GitHub issue management — create, update, label, milestone, and link issues to PRs via gh CLI or curl fallback.

Overview

PublisherAlexAI-MCP
Repositoryhermes-CCC
Skill namegithub-issues
Stars
134
Forks
22
Bundled files
Instructions only
LicenseMIT
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 AlexAI-MCP on GitHub. Read the source before you install it.

Installation

Install the Github Issues 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/AlexAI-MCP/hermes-CCC/tree/master/skills/github-issues
  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/AlexAI-MCP/hermes-CCC.git /tmp/hermes-CCC
mkdir -p .claude/skills
cp -r /tmp/hermes-CCC/skills/github-issues .claude/skills/github-issues
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github Issues 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 Github Issues 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 Github Issues 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.

GitHub Issues

Full issue lifecycle management using the gh CLI. Every command has a curl fallback for machines without gh.

Prerequisites

  • GitHub CLI: gh auth login (or set GH_TOKEN env var)
  • curl fallback: set GITHUB_TOKEN and know your OWNER/REPO
bash
export OWNER=myorg
export REPO=myrepo
export GITHUB_TOKEN=ghp_...

List Issues

bash
# Open issues
gh issue list

# Filter by label, assignee, state
gh issue list --state open --label bug --assignee @me

# All states
gh issue list --state all --limit 50

# curl fallback
curl -H "Authorization: token $GITHUB_TOKEN" \
  "https://api.github.com/repos/$OWNER/$REPO/issues?state=open&per_page=20"

View an Issue

bash
gh issue view 123

# Open in browser
gh issue view 123 --web

# curl fallback
curl -H "Authorization: token $GITHUB_TOKEN" \
  "https://api.github.com/repos/$OWNER/$REPO/issues/123"

Create an Issue

bash
gh issue create \
  --title "Fix null pointer in auth module" \
  --body "Steps to reproduce:\n1. ...\n2. ..." \
  --label "bug,priority:high" \
  --assignee @me

# Interactive
gh issue create

# curl fallback
curl -X POST \
  -H "Authorization: token $GITHUB_TOKEN" \
  -H "Content-Type: application/json" \
  "https://api.github.com/repos/$OWNER/$REPO/issues" \
  -d '{"title":"Fix null pointer","body":"...","labels":["bug"]}'

Edit an Issue

bash
# Add label
gh issue edit 123 --add-label "priority:high"

# Remove label
gh issue edit 123 --remove-label "needs-triage"

# Change assignee
gh issue edit 123 --add-assignee username

# Set milestone
gh issue edit 123 --milestone "v2.0"

# Change title
gh issue edit 123 --title "New title"

Comment on an Issue

bash
gh issue comment 123 --body "Looking into this now."

# curl fallback
curl -X POST \
  -H "Authorization: token $GITHUB_TOKEN" \
  -H "Content-Type: application/json" \
  "https://api.github.com/repos/$OWNER/$REPO/issues/123/comments" \
  -d '{"body":"Looking into this now."}'

Close / Reopen an Issue

bash
gh issue close 123
gh issue close 123 --reason "completed"
gh issue close 123 --comment "Fixed in #456"

gh issue reopen 123

Search Issues

bash
gh issue list --search "error in production"
gh issue list --search "label:bug created:>2024-01-01"

# GitHub search syntax
gh issue list --search "is:open is:issue assignee:@me"

Link Issues to PRs

Reference issues in PR body or commits:

Fixes #123
Closes #456
Resolves #789

GitHub auto-closes linked issues when PR merges.


Bulk Operations

bash
# Close all issues with a label
gh issue list --label "wontfix" --json number --jq '.[].number' | \
  xargs -I{} gh issue close {} --reason "not planned"

# List issues as JSON
gh issue list --json number,title,labels,assignees --limit 100

Milestones

bash
# List milestones
gh api repos/$OWNER/$REPO/milestones

# Create milestone
gh api repos/$OWNER/$REPO/milestones \
  --method POST \
  -f title="v2.0" \
  -f due_on="2024-06-01T00:00:00Z"

Labels

bash
# List labels
gh label list

# Create label
gh label create "priority:high" --color FF0000 --description "Urgent"

# Clone labels from another repo
gh label clone owner/source-repo

Issue Templates

Create .github/ISSUE_TEMPLATE/bug_report.md:

markdown
---
name: Bug Report
about: Report a bug
labels: bug
---

## Description
## Steps to Reproduce
## Expected vs Actual
## Environment

Frequently asked questions

What does the Github Issues AI skill do?

GitHub issue management — create, update, label, milestone, and link issues to PRs via gh CLI or curl fallback.

Why use Github Issues on TypingMind?

Because you install it once and use it with any model. Github Issues 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 Github Issues in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AlexAI-MCP/hermes-CCC/tree/master/skills/github-issues. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Github Issues?

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 Github Issues?

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

Is the Github Issues AI skill free?

Yes. It is published on GitHub by AlexAI-MCP under the MIT 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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