A skill your agent uses when working in a TeamClu app checkout, changing its build or start declaration, or preparing to publish an app.

MITAuto-check passedDevOps & Cloud

Install Deploy App

skills CLI
$ npx skills add different-ai-studio/teamclu --skill deploy-app -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install different-ai-studio/teamclu deploy-app --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/different-ai-studio/teamclu.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/app/src/lib/skills/deploy-app .claude/skills/deploy-app && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deploy-app
GitHub stars
167
Token cost
~1.3k tokens
SKILL.md length
746 words
Files
1
Skills in repo
8
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when working in a TeamClu app checkout, changing its build or start declaration, or preparing to publish an app.

  • Works in 6 steps: Call manage_app status for the selected… → Call manage_app runtime_info filtered to… → Preserve the successful deployment's FC… → …
  • Working in a TeamClu app checkout
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Changing its build

What it does

Deploy App is an agent skill from different-ai-studio/teamclu. Use when working in a TeamClu app checkout, changing its build or start declaration, or preparing to publish an app.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: TeamClu, AI Agent Desktop Workspace. The licence is MIT.

When your agent uses it

  • Working in a TeamClu app checkout
  • Changing its build
  • Start declaration
  • Preparing to publish an app

Example prompts

  • “/deploy-app”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Call manage_app status for the selected app workspace. Read the current checkout declaration, live deployment, code revision, and source…
  2. Call manage_app runtime_info filtered to the app's language. Use the returned regional versions, image observations, layer availability…
  3. Preserve the successful deployment's FC runtime, interpreter command and version, args, layers, and port for an ordinary redeploy. A…
  4. Check the selected build machine and its tools. The build command runs there, possibly on Windows, while the function runs on…
  5. For a Gitea checkout, commit and push the exact app revision to its remote, then verify the selected checkout is clean and at the exact…
  6. Only when the user explicitly requested publishing, call manage_app deploy; review its preflight's exact changes through the existing…

What it can do on your machine

Read from SKILL.md and the folder at commit 8cd5e77. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deploy App loads about 1.3k tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 746 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from different-ai-studio/teamclu at commit 8cd5e77, republished under its MIT licence (© different-ai-studio). 746 words, ~1,321 tokens.

Download SKILL.mdSave it as .claude/skills/deploy-app/SKILL.md (or your agent's skills folder).
name
deploy-app
description
Use when working in a TeamClu app checkout, changing its build or start declaration, or preparing to publish an app.

Deploy a TeamClu app

The checkout declares the desired build and start behavior. The live deployment and regional capabilities are separate facts. Resolve both before making a deployment decision.

  1. Call manage_app status for the selected app workspace. Read the current checkout declaration, live deployment, code revision, and source status. Treat the session snapshot as a hint only.
  2. Call manage_app runtime_info filtered to the app's language. Use the returned regional versions, image observations, layer availability, verification status, and source errors. For a new app, select a TeamClu-deployable candidate from current facts and write every required startup field explicitly. Provider availability alone does not establish TeamClu compatibility. Do not guess a version, path, layer, or compatibility from a template or another region. If discovery times out or is incomplete, keep that uncertainty visible; it does not authorize silently switching to a familiar runtime. A routine redeploy may retain a verified, pinned live configuration when catalog discovery is unavailable and there is no provider drift.
  3. Preserve the successful deployment's FC runtime, interpreter command and version, args, layers, and port for an ordinary redeploy. A runtime, interpreter, or layer change is a migration: explain the exact fields and reason, obtain explicit migration intent, and use the preflight preview and native approval. Entry and port changes must also be visible in that preview. Never rewrite the checkout to a known-good version merely because discovery failed.
  4. Check the selected build machine and its tools. The build command runs there, possibly on Windows, while the function runs on linux/x86_64. Verify the declared output and entry exist, and that native dependencies target Linux/x86_64. The daemon's build response includes artifactVerification for the pinned revision: checked means the declared entry and recognizable native headers or local image metadata passed those checks; it does not prove the app starts. ZIP/JAR members are checked through EOF within fixed limits; nested, oversized, corrupt, or unreadable archives stay unknown. Tar and other compressed formats that the daemon cannot inspect also stay unknown. A wrong platform fails before archive upload or image push. unknown blocks automatic finalization; it names an opaque startup entry, unclassifiable native content, or unavailable image metadata. The desktop keeps the previous app live. Run an explicit test in the target Linux/x86_64 runtime before treating it as compatible. The current deploy path has no evidence override, so report the deployment as blocked rather than retrying or claiming it published. Keep build commands portable across selected machines.
  5. For a Gitea checkout, commit and push the exact app revision to its remote, then verify the selected checkout is clean and at the exact remote HEAD. A clean remote commit does not excuse a dirty selected checkout, even if the build would read remote content. Gitea deployment cannot use uncommitted or unpushed changes. For an imported checkout, use the platform's pinned content digest and its source checks.
  6. Only when the user explicitly requested publishing, call manage_app deploy; review its preflight's exact changes through the existing native approval. Do not bypass a rejected preview, drift, or approval. Deploy the pinned revision, then check manage_app status, the runtime configuration, live URL, health path, and changed behavior, including data/auth behavior when applicable. Report the revision and any verification limit.
Show full SKILL.md (209 more words)Show less

Custom environment, access, domain, data, files, and cron changes use their matching manage_app_* tools and the signed-in user's permissions. Never request or print secret values.

For TeamClu platform sign-in, organization roles, or protected pages and data endpoints, read the inherent app-auth skill before implementation. At release, verify its saved policies and report any auth acceptance limits.

Uninstalling a deployment

Only when the user explicitly requests uninstalling a deployment, call manage_app undeploy with an explicit app ID or name and obtain its native confirmation. This stops new gateway requests and cleans the FC function, HTTP trigger, origin domain mapping, build artifact and any legacy login client. It retains the App, code repository, sessions, database, uploaded files, auth policy and scheduled-job definitions. It does not delete the App or archive its repository.

An accepted operation is not a completed uninstall. Read manage_app status until undeploy_operation.status is succeeded; report individual failed steps and retry only when the user requests it. An unknown provider outcome remains fenced for operator reconciliation: do not force a new deploy or bypass the lock. After successful uninstall, use the normal deployment flow to publish again, retaining the last successful configuration as history. Verify retained data and platform login after redeployment; report real-account verification as pending when unavailable.

© different-ai-studio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/app/src/lib/skills/deploy-app of different-ai-studio/teamclu.

Open the folder on GitHubat commit 8cd5e77

Compare with similar skills

Deploy App next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Deploy App compared with similar skills
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Deploy App this skilldifferent-ai-studio/teamclu167—~1.3kAutomated safety check: PassMIT
Kubeshark Installerkubeshark/kubeshark12k—~3.6kAutomated safety check: NotesApache-2.0
GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb6.7k—~4kAutomated safety check: NotesApache-2.0
KubeSphere ServiceMesh Managerkubesphere/kubesphere17k—~2.4kAutomated safety check: PassCustom licence
Vercelremotion-dev/remotion63k—~1.2kAutomated safety check: PassCustom licence
AWS Cdk Developmentzxkane/aws-skills3672 repos~2.5kAutomated safety check: PassMIT

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Categories

Questions about Deploy App

What does Deploy App do?

A skill your agent uses when working in a TeamClu app checkout, changing its build or start declaration, or preparing to publish an app. Deploy App is an agent skill from different-ai-studio/teamclu. Use when working in a TeamClu app checkout, changing its build or start declaration, or preparing to publish an app.

When should I use Deploy App?

Deploy App fits situations like: working in a TeamClu app checkout; changing its build; start declaration; preparing to publish an app.

How do I install Deploy App in Claude Code?

Run `npx skills add different-ai-studio/teamclu --skill deploy-app -a claude-code`. Or copy the skill folder (packages/app/src/lib/skills/deploy-app in different-ai-studio/teamclu) into .claude/skills/deploy-app in your project. Claude Code loads it when a task matches its description.

How do I install Deploy App in Codex?

Run `npx skills add different-ai-studio/teamclu --skill deploy-app -a codex`. Or copy the skill folder (packages/app/src/lib/skills/deploy-app in different-ai-studio/teamclu) into .agents/skills/deploy-app in your project. Codex loads it when a task matches its description.

Can I use Deploy App in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add different-ai-studio/teamclu --skill deploy-app -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deploy-app, .gemini/skills/deploy-app, .github/skills/deploy-app and .opencode/skills/deploy-app in your project.

What does Deploy App need to run?

SKILL.md names no scripts, command-line tools or credentials: Deploy App is instructions for the agent only.

Does Deploy App access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Deploy App safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deploy App use?

Deploy App is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deploy App use?

About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Deploy App?

Skills that share tags, products or a category with Deploy App: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deploy App?

different-ai-studio (a GitHub organization) maintains it in different-ai-studio/teamclu, which has 167 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 9, 2026.

Source: different-ai-studio/teamclu on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.