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Version Check

CommunityPopular
ykdojo
version-check

Recommend which Claude Code version to run, or whether to update. Use when asked which Claude Code version is best/safe, whether to update now, whether a recent release is buggy, or what changed since the installed version.

Overview

Publisherykdojo
Repositoryclaude-code-tips
Skill nameversion-check
Stars
10.1K
Forks
815
Bundled files
Instructions only
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 ykdojo on GitHub. Read the source before you install it.

Installation

Install the Version Check 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/ykdojo/claude-code-tips.git /tmp/claude-code-tips
mkdir -p .claude/skills
cp -r /tmp/claude-code-tips/skills/version-check .claude/skills/version-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Version Check 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 Version Check 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 Version Check 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.

Claude Code version check

The goal is a recommendation: stay put, update, or pin to a specific version. Claude Code ships latest very frequently (often 1-2x/day), so "best version" is a moving target and the answer is usually a range, not a single build.

Heuristics (read first)

  • stable lags latest and is NOT an LTS. The npm stable dist-tag is just a pointer that trails latest by a handful of patch releases. It can even sit behind an important fix release, so "stable" does not mean "most bugs fixed." Don't blindly recommend @stable.
  • Quiet version = good sign. If nobody is complaining about a recent release, that's a positive signal. A loud pile-on about a specific build is the thing to avoid.
  • Version comparisons are the strongest signal. Posts where people compare builds ("X broke Y, rolled back to Z") tell you exactly which release to avoid.
  • Stay ~a day behind the bleeding edge. Avoid a release that's only a few hours old - let others surface same-day regressions first.
  • But a same-day release is fine when the tracker is quiet and it fixes something you're carrying. If a few hours have passed with no cluster of issues, and the changelog shows it fixing a regression that's live in your installed range, taking it is usually better than waiting. Say plainly what you're trading: a few hours of field time instead of a day.
  • The real lever is when you update, not stable-vs-latest. Default Claude Code auto-updates to latest constantly, which is how you drift onto a same-day regression.

1. What's installed vs what's published

bash
claude --version
npm view @anthropic-ai/claude-code dist-tags --json

dist-tags shows latest, stable, and next. Compare against the installed version to see how far ahead/behind each pointer is.

Recent releases and their timestamps (to see how fast things are shipping):

bash
npm view @anthropic-ai/claude-code time --json | python3 -c "import sys,json;d=json.load(sys.stdin);print('\n'.join(f'{k}: {v}' for k,v in list(d.items())[-8:]))"

2. Scan the changelog for regressions in the gap

Fetch the changelog and read the entries between the installed version and latest. Look for "Fixed ... regression in X" lines - if a recent build introduced a regression that has not yet been fixed, that's the one to avoid.

bash
curl -sL https://raw.githubusercontent.com/anthropics/claude-code/main/CHANGELOG.md | awk '/## <LATEST>/,/## <INSTALLED>/'

(Substitute the two version numbers.) A release that is mostly "Fixed …" after a noisy one is usually a safe landing spot.

3. Community sentiment (valuable - do this, don't skip it)

GitHub issues (primary - reliable and fetchable)

The most dependable signal. Search recent open bug reports, sorted by reactions:

bash
gh api -X GET search/issues \
  -f q="repo:anthropics/claude-code is:issue is:open created:>=<DATE> label:bug" \
  -f sort=reactions -f per_page=25 \
  --jq '.items[] | "\(.created_at[:10]) +\(.reactions.total_count) c\(.comments) #\(.number) \(.title)"'

(Set <DATE> to ~3 days before today.) A version regression shows up as a cluster of high-reaction issues filed right after a release. Single reports with 0-1 reactions are noise, not a signal - the tracker always has a steady trickle of those.

Cross-reference titles against the changelog gap: if a top issue is already addressed by a fix/flag in latest, that build is safer, not riskier. Mostly minor or server-side (API 500/529) issues = quiet release = good sign.

To judge a release that's only hours old, drop label:bug and is:open and set the date to today - you want everything filed since it shipped, before anyone has triaged or labeled it.

Also check whether the issues are even about the CLI. Clusters about Claude Desktop or the VS Code extension say nothing about whether a Claude Code CLI build is safe.

Reddit (secondary - reachable via the DuckDuckGo hop)

r/ClaudeAI version-comparison threads are valuable, but Reddit now hard-blocks every direct automated route - curl (host + container), the WebSearch crawler (denied by user-agent), AND a cold Playwright navigation (network-security challenge page). The reliable way in is the reddit-fetch skill's DuckDuckGo-hop unlock: navigate Playwright to a html.duckduckgo.com/html/?q=site:reddit.com/r/ClaudeAI+... result redirect once, which sets a session cookie, then direct .json navigation works:

https://www.reddit.com/r/ClaudeAI/search.json?q=claude+code+update+broke+OR+regression&restrict_sr=on&sort=new&t=week&limit=25

Apply the heuristics above: a positive or quiet recent-update thread is reassuring; a high-score "X is broken" thread names the build to skip.

4. Test the claim instead of arguing about it

When the question is "do I actually need this release to get X" - usually a new model - just run it. A new model is server-side, so it often works on an older client; what the older client gets wrong is the metadata around it.

bash
claude -p "Reply with exactly: ok" --model <model-id> --output-format json 2>&1 \
  | python3 -c "import sys,json;u=json.load(sys.stdin)['modelUsage'];print(json.dumps({m:{'contextWindow':v['contextWindow'],'costUSD':v['costUSD']} for m,v in u.items()},indent=2))"

modelUsage is the honest answer: it names the model that actually served the turn (ignore the Haiku row, that's the background helper) and reports the contextWindow the client is applying. A new model responding on an old client but showing a 200000 window where the changelog promises 1000000 means the model works and the client is capping it - which is a concrete, checkable reason to update rather than a vague one.

Re-run the same command after updating to confirm the number moved.

5. Recommend

  • If the installed version is in the recent, well-received range and nothing in the gap regressed: stay put, don't chase a release that's only hours old.
  • If there's a known regression in a build, recommend the last good version and pin/rollback to it.
  • For anyone who's been burned: disable the auto-updater and update deliberately (the repo's setup script does this), rather than religiously tracking @stable.

Installing a specific version - check how it was installed first

npm install -g @anthropic-ai/claude-code@X.Y.Z is not universal. On a native install it fails with EEXIST: file already exists /Users/<you>/.local/bin/claude, because that path is a symlink into ~/.local/share/claude/versions/ that npm won't overwrite. Don't --force past it - that replaces the native launcher with an npm shim.

bash
ls -la "$(command -v claude)"   # symlink into ~/.local/share/claude/versions/ = native install
  • Native installclaude install X.Y.Z (same command for rollback)
  • npm installnpm install -g @anthropic-ai/claude-code@X.Y.Z

Either way, confirm with claude --version afterwards - a package manager reporting success is not the same as the launcher pointing at the new build.

Frequently asked questions

What does the Version Check AI skill do?

Recommend which Claude Code version to run, or whether to update. Use when asked which Claude Code version is best/safe, whether to update now, whether a recent release is buggy, or what changed since the installed version.

Why use Version Check on TypingMind?

Because you install it once and use it with any model. Version Check 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 Version Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ykdojo/claude-code-tips/tree/main/skills/version-check. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Version Check?

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 Version Check?

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

Is the Version Check AI skill free?

It is published on GitHub by ykdojo. Check the repository for licensing terms. 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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