Contributing To Awesome Claude logo

Contributing To Awesome Claude

Community
JSONbored
contributing-to-awesome-claude

Use when writing, testing, or preparing ANY contribution or pull request to the JSONbored/awesome-claude (HeyClaude) repo — adding a community content entry (agent/MCP server/skill/hook/command/rule/guide/collection/statusline), or making a platform/code change (website, registry package, MCP package, scripts). The repo has two separate review paths: a private, one-shot "HeyClaude submission gate" that decides single-file content PRs, and the shared gittensory-orb bot that posts an advisory readiness/linked-issue comment on platform/code PRs but does not itself merge or close content PRs. Unlike JSONbored/gittensory and JSONbored/metagraphed, a linked issue is OPTIONAL here — do not import their mandatory-linked-issue rule into this repo. Invoke for any "contribute to / open a PR against / submit an entry to / fix a bug in awesome-claude (HeyClaude)" task.

Overview

PublisherJSONbored
Repositoryawesome-claude
Skill namecontributing-to-awesome-claude
Stars
303
Forks
163
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Contributing To Awesome Claude 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/JSONbored/awesome-claude/tree/main/.claude/skills/contributing-to-awesome-claude
  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/JSONbored/awesome-claude.git /tmp/awesome-claude
mkdir -p .claude/skills
cp -r /tmp/awesome-claude/.claude/skills/contributing-to-awesome-claude .claude/skills/contributing-to-awesome-claude
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Contributing To Awesome Claude 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 Contributing To Awesome Claude 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 Contributing To Awesome Claude 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.

Contributing to awesome-claude (HeyClaude)

HeyClaude is a file-backed directory of Claude/AI workflow resources (content/<category>/<slug>.mdx) plus a website, registry package, and MCP package that serve that content. It has two kinds of contribution with two different review mechanisms — get the kind right first, everything else follows from it.

reference.md (next to this file) has the exhaustive command tables, the two-gate architecture in detail, the current Codecov numbers, and the content-PR pitfalls. Read it when a section below tells you to.


Step 0 — Which kind of contribution is this?

You are...Contribution typeReview mechanism
Adding/editing one content/<category>/<slug>.mdx entry (agent, MCP server, skill, hook, command, rule, guide, collection, statusline)Community contentPrivate HeyClaude submission gate (one-shot, aggressive)
Changing apps/web/**, packages/registry/**, packages/mcp/**, scripts/**, workflowsPlatform/codeStandard CI + the shared gittensory-orb bot (advisory)

These are handled by genuinely different systems (see reference.md §1). Do not mix them in one PR — CONTRIBUTING.md is explicit that a content PR touches exactly one content/<category>/<slug>.mdx file, and platform/code changes should stay separate from individual content imports.


If you're adding a content entry

  1. Read the schema and examples first: content/SCHEMA.md (required/optional fields per category) and examples/content/SUBMISSION_EXAMPLES.md (accepted vs. rejected/rerouted examples — read this before you draft anything non-trivial).
  2. One file, one PR. Add exactly one content/<category>/<slug>.mdx. Do not touch README.md, apps/web/public/data/**, apps/web/src/generated/**, apps/web/src/routeTree.gen.ts, or apps/web/public/downloads/** — those are maintainer-owned generated outputs and editing them in a content PR is a reject reason.
  3. Source-back everything. Canonical source/docs/repo URLs, not affiliate or tracking links. For hooks, MCP servers, skills, commands, and statuslines, fill safetyNotes (execution, install, writes, destructive actions, background workers, network access, account writes) and privacyNotes (local files, logs, credentials, telemetry, retained data) — use prerequisites only for setup requirements and disclosure only for commercial/listing status, not runtime safety.
  4. A linked issue is genuinely optional here. CONTRIBUTING.md says plainly: "a PR with no linked issue is fine." Filing your own issue and resolving it is fine too. What is not fine is multi-account farming (opening an issue on one account, "resolving" it from another) — see reference.md §4 for the exact contrast with gittensory/metagraphed's mandatory policy.
  5. Validate narrowly — a content PR does not need the full platform test suite:
    sh
    pnpm install --frozen-lockfile
    pnpm validate:content:strict
    Do not run generate:readme / generate:openapi or commit build output for a one-file content submission — those are build-time outputs regenerated by CI/deploy.
  6. Understand who actually decides your PR's fate. It is the private submission gate, not gittensory-orb — see the Step 1 architecture note below and reference.md §2 for the full disposition table.

If you're making a platform/code change

  1. Trace an existing analogue in apps/web/src/, packages/registry/src/, or packages/mcp/ before writing new code — the repo has a strong existing house style per surface.
  2. Scope your validation to the surface you touched — see reference.md §3 for the exact command lists AGENTS.md prescribes per change type (README, submission/API, or general platform).
  3. Codecov is enforcing, not informational, on code changes. codecov/patch requires 70% coverage of your changed lines (5% threshold), and codecov/project compares against your PR's own base commit (target: auto, 1% threshold). Both post a real pass/fail status — see reference.md §5 for the exact codecov.yml values and what's ignored (tests/, **/*.test.ts, **/*.config.ts, apps/web/src/generated, apps/web/public/data, integrations).
  4. Regenerate what you invalidate, then commit it — see reference.md §3 for the exact regen command per surface (README, OpenAPI, etc.). Keep generated-artifact churn out of PRs that don't need it; external contributors especially should leave generated output out unless a maintainer asks for it.
  5. gittensory-orb reviews your PR, but advisory only. It posts a readiness score, linked-issue/no-issue check, and coverage-evidence comment — useful signal, but it is not the merge authority for platform PRs either; ordinary CI + maintainer review is (see reference.md §2).

Common pitfalls (both paths)

  • Editing generated files. README.md, apps/web/public/data/**, apps/web/src/generated/**, apps/web/src/routeTree.gen.ts are maintainer-owned outputs. Hand-editing them (in either a content or platform PR) is flagged/rejected.
  • Requesting HeyClaude host your ZIP/MCPB. Community package uploads for hosting at /downloads/... are not accepted — link the source repo, an install command, or copyable source content instead. Maintainer-built download artifacts are a separate, post-review, maintainer-only path.
  • Bringing gittensory/metagraphed's mandatory-linked-issue habit here. It does not apply — see reference.md §4.
  • Missing safety/privacy notes on a risk-bearing entry (a hook, MCP server, skill, command, or statusline that executes code, writes files, calls out to third parties, or runs in the background). Generic boilerplate is a common review nit; be specific about what the resource can actually do.
  • Multi-account issue/PR farming. Explicitly against policy and is a permanent, cross-repo block per CODE_OF_CONDUCT.md — not a gray area.
  • Chasing a review. CONTRIBUTING.md warns that pinging for status on a queued submission deprioritizes it (adds ~5 days to the manual queue) rather than speeding it up.

When you need the exact command lists, the full two-gate disposition tables, or the current Codecov numbers verified against the live codecov.yml, read reference.md in this skill directory.

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 Contributing To Awesome Claude AI skill do?

Use when writing, testing, or preparing ANY contribution or pull request to the JSONbored/awesome-claude (HeyClaude) repo — adding a community content entry (agent/MCP server/skill/hook/command/rule/guide/collection/statusline), or making a platform/code change (website, registry package, MCP package, scripts). The repo has two separate review paths: a private, one-shot "HeyClaude submission gate" that decides single-file content PRs, and the shared gittensory-orb bot that posts an advisory readiness/linked-issue comment on platform/code PRs but does not itself merge or close content PRs. U...

Why use Contributing To Awesome Claude on TypingMind?

Because you install it once and use it with any model. Contributing To Awesome Claude 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 Contributing To Awesome Claude in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JSONbored/awesome-claude/tree/main/.claude/skills/contributing-to-awesome-claude. 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 Contributing To Awesome Claude?

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 Contributing To Awesome Claude?

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

Is the Contributing To Awesome Claude AI skill free?

Yes. It is published on GitHub by JSONbored 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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