Github Dashboard logo

Github Dashboard

OrganizationPopular
nexu-io
github-dashboard

GitHub repository analytics dashboard — stars, forks, contributors, issues, pull requests, recent activity, and top contributors. Use when the brief asks for a GitHub repo dashboard, open-source growth report, repository health page, or GitHub analytics view.

Overview

Publishernexu-io
Repositoryopen-design
Skill namegithub-dashboard
Stars
96.7K
Forks
11.2K
Bundled files
5
LicenseApache-2.0
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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nexu-io on GitHub. Read the source before you install it.

Installation

Install the Github Dashboard 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.
  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/nexu-io/open-design.git /tmp/open-design
mkdir -p .claude/skills
cp -r /tmp/open-design/design-templates/github-dashboard .claude/skills/github-dashboard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github Dashboard 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 Dashboard 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 Dashboard 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 Dashboard Skill

Create a single-screen GitHub repository analytics dashboard in the FlowAI / Soft Paper Workspace visual style: warm off-white canvas, white rounded panels, a fixed left sidebar, compact KPI cards, pastel pills, dense tables, and low-contrast hairlines.

Resource map

github-dashboard/
├── SKILL.md
├── example.html                         ← rendered reference dashboard
└── references/
    ├── template.html                    ← live-artifact-compatible HTML template
    ├── example-data.json                ← normalized public GitHub data shape
    ├── artifact-example.json            ← minimal live-artifact create input
    └── provenance-example.json          ← safe source/provenance example

When to use this skill

Use this when the user asks for a dashboard or report about a single GitHub repository, for example:

  • repository growth dashboard
  • open-source project health report
  • GitHub stars / forks / contributors analytics
  • issue and pull-request activity page
  • maintainer / contributor dashboard

If the user asks for refreshability, source auditability, or scheduled updates, produce the live-artifact source set (template.html, data.json, artifact.json, provenance.json) and follow the live-artifact contract. If they only need a visual artifact, produce a self-contained index.html.

Workflow

  1. Resolve repository scope

    • Parse owner/repo from the brief.
    • This v1 skill is scoped to one repository. If multiple repositories are requested, ask the user to pick the primary repository or create one dashboard per repository.
    • If the repo is missing, ask one concise question for the GitHub URL or owner/repo.
  2. Collect public GitHub data

    • Prefer GitHub CLI/API for public repository data when available.
    • Current stars/forks/watchers/open issue count: GET /repos/{owner}/{repo} (stargazers_count, forks_count, watchers_count, open_issues_count).
    • Contributors: paginate GET /repos/{owner}/{repo}/contributors?per_page=100&page=N, sort by contributions descending, and take the top N used by the dashboard. If only page 1 is available, label totals as first-page estimates.
    • Issues: use GitHub Search API (repo:{owner}/{repo} is:issue) for total counts, or paginate GET /repos/{owner}/{repo}/issues?state=all and filter out items with a pull_request field.
    • Pull requests: use GitHub Search API (repo:{owner}/{repo} is:pr) for total counts, or paginate GET /repos/{owner}/{repo}/pulls?state=all and count pages via the Link header.
    • Recent activity: combine the newest issues and pull requests, normalize them into display-ready rows, and cap the preview list at 5–10 items.
    • Growth/delta metrics: GitHub REST does not expose complete historical star/fork deltas. Use GraphQL, stargazer event snapshots, the Events API where available, or explicitly mark deltas as estimated/synthetic in provenance.json.
    • Do not store auth tokens, raw HTTP envelopes, cookies, rate-limit headers, or private metadata.
  3. Normalize into dashboard data

    • Required repository: name, fullName, url, description, language, license, created, lastUpdated.
    • Required metrics: stars, forks, contributors, issues, pull requests. Store display-ready totals plus small deltas or growth notes.
    • Required contributors: top 5–8 contributors with login, avatar, and contributions.
    • Required recentActivity: display-ready rows with title, typeText, typeClass, label, labelClass, author, authorAvatar, and updated. Do not rely on template conditionals for issue/PR switching.
    • Chart data can be synthetic only when GitHub does not expose the exact history; document the transformation in provenance.
  4. Apply the visual system

    • Use the active DESIGN.md tokens when present.
    • If no design system is provided, use the Soft Paper defaults reflected in references/template.html: #F2F2F0 canvas, white cards, #ECECEA borders, #0A0A0A ink, Geist/Inter typography, 256px sidebar, 48px topbar, and 16px card radius.
    • Keep color small and semantic: green for healthy metrics, amber for warning, blue for feature/PR labels, red only for defects or risk.
  5. Lay out the page

    • Shell: 256px sidebar + main panel, both white, rounded 16px, 1px hairline border.
    • Topbar: repo context on the left, refresh/export/action affordances on the right.
    • Header: repository name, description, and date/settings/actions row.
    • KPI strip: 5 compact cards for stars, forks, contributors, issues, PRs.
    • Main grid: 2fr/1fr split with a growth chart or activity table on the left and top contributors/health cards on the right.
    • Footer: provenance/last-updated note in small muted text.
  6. Write the artifact

    • For a static artifact, write one self-contained index.html with inline CSS and no external JS libraries.
    • For a live artifact, write template.html, data.json, artifact.json, and provenance.json; index.html is derived by the daemon.
    • Tag major regions with stable data-od-id values: sidebar, topbar, repo-header, kpi-strip, growth-chart, contributors, activity, provenance.

Visual rules

  • Light mode only.
  • 256px fixed sidebar on desktop; stack on narrow screens.
  • 4 or 5 KPI cards in the first row.
  • Use tabular lining numerals for all counts.
  • Avatars are circular, 28–32px in tables and contributor lists.
  • Tables use 13px body text, 11px uppercase column labels, 1px row dividers.
  • Cards use hairline borders and a barely visible shadow at most: 0 1px 2px rgba(10,10,10,.04), 0 1px 1px rgba(10,10,10,.02).
  • Do not use gradients except tiny workflow/repo icon placeholders.
  • Do not make the page look like GitHub itself. This is a custom operational dashboard, not a GitHub UI clone.

Self-check

  • Every metric has a source or a provenance note.
  • No private data or credentials are persisted.
  • Data labels are specific to the repository, not placeholders.
  • The screen still reads clearly at 50% zoom.
  • The dashboard uses at most one solid black primary action per area.
  • Status labels and issue/PR chips are pastel pills, not saturated badges.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Github Dashboard AI skill do?

GitHub repository analytics dashboard — stars, forks, contributors, issues, pull requests, recent activity, and top contributors. Use when the brief asks for a GitHub repo dashboard, open-source growth report, repository health page, or GitHub analytics view.

Why use Github Dashboard on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nexu-io/open-design/tree/main/design-templates/github-dashboard. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Github Dashboard?

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 Dashboard?

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

Is the Github Dashboard AI skill free?

Yes. It is published on GitHub by nexu-io under the Apache-2.0 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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