Appllama App Design Skill
Appllama/appllama-skills
Build native-feeling, benchmark-quality mobile app screens (Expo / React Native).
Run the pre-release end-to-end sweep of every user-facing surface — the 33 samples under samples/ (booted from their packaged artifacts and driven in a real browser via chrome-devtools MCP), the…
$ npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Atmosphere/atmosphere release-sample-sweep --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Atmosphere/atmosphere.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/release-sample-sweep .claude/skills/release-sample-sweep && rm -rf skills-srcUse ~/.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/
Install the "release-sample-sweep" agent skill from https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweep into .claude/skills/release-sample-sweep/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "release-sample-sweep", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweepType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Atmosphere/atmosphere release-sample-sweep --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Atmosphere/atmosphere.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/release-sample-sweep .agents/skills/release-sample-sweep && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "release-sample-sweep" agent skill from https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweep into .agents/skills/release-sample-sweep/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "release-sample-sweep", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Atmosphere/atmosphere release-sample-sweep --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Atmosphere/atmosphere.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/release-sample-sweep .cursor/skills/release-sample-sweep && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "release-sample-sweep" agent skill from https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweep into .cursor/skills/release-sample-sweep/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "release-sample-sweep", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Atmosphere/atmosphere.git --path .claude/skills/release-sample-sweep--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Atmosphere/atmosphere release-sample-sweep --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Atmosphere/atmosphere.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/release-sample-sweep .gemini/skills/release-sample-sweep && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "release-sample-sweep" agent skill from https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweep into .gemini/skills/release-sample-sweep/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "release-sample-sweep", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Atmosphere/atmosphere release-sample-sweepInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Atmosphere/atmosphere.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/release-sample-sweep .github/skills/release-sample-sweep && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "release-sample-sweep" agent skill from https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweep into .github/skills/release-sample-sweep/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "release-sample-sweep", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Atmosphere/atmosphere release-sample-sweep --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Atmosphere/atmosphere.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/release-sample-sweep .opencode/skills/release-sample-sweep && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "release-sample-sweep" agent skill from https://github.com/Atmosphere/atmosphere/tree/main/.claude/skills/release-sample-sweep into .opencode/skills/release-sample-sweep/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "release-sample-sweep", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
release-sample-sweepRun the pre-release end-to-end sweep of every user-facing surface — the 33 samples under samples/ (booted from their packaged artifacts and driven in a real browser via chrome-devtools MCP), the…
Release Sample Sweep is an agent skill from Atmosphere/atmosphere. Run the pre-release end-to-end sweep of every user-facing surface — the 33 samples under samples/ (booted from their packaged artifacts and driven in a real browser via chrome-devtools MCP), the Expo/React Native client, and the atmosphere CLI. Use before cutting a release, and after any change to the Console bundle, a shared module, atmosphere.js, the CLI, or several samples at once. Covers preconditions, the keyless Ollama backend, the per-sample launch/drive/collect/teardown loop, the evidence ledger, the fix…
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts, reference files and assets (for example `assets/ledger-template.md`, `references/cli-sweep.md` and `references/driving-recipes.md`).
It sits in Mobile, covering Cross-platform mobile apps, Browser testing and LLM inference and serving. It works with Chrome DevTools, Model Context Protocol, Expo and Ollama. The repository describes itself as: Portable AI agent runtime for the JVM. One @Agent class runs on Spring AI, LangChain4j, Anthropic, or 9 more behind one SPI. Token streaming, tool calls, human approvals, and… The licence is Apache-2.0.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 13671cf. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
gitollamacurljavaclaudeFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git and curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
LLM_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Release Sample Sweep loads about 4.2k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 161 tokens; SKILL.md has 1,972 words of instructions outside code blocks.
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.
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); the scripts in this folder are not scanned.
The full file from Atmosphere/atmosphere at commit 13671cf, republished under its Apache-2.0 licence (© Atmosphere). 1,972 words, ~4,191 tokens.
.claude/skills/release-sample-sweep/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.Before a release, every user-facing surface is exercised the way a user exercises it. This skill is that procedure written down.
Three surfaces, three drivers — all three are release gates:
| Surface | What | Driver |
|---|---|---|
| Samples (33) | samples/*, booted from packaged artifacts | chrome-devtools MCP, or the wire protocol for the headless ones |
| Expo client (1) | samples/spring-boot-ai-classroom/expo-client/ | iOS simulator MCP — it is a native app, chrome-devtools cannot reach it |
| CLI | atmosphere run / new / compose / import / checkpoint + its four distributions | Shell, then chrome-devtools against what atmosphere run booted |
release-4x.yml.modules/spring-boot-starter/frontend/),
since the Console is both the shipped sample UI and the validation surface.modules/cpr, modules/ai, modules/spring-boot-starter, modules/admin).CI builds and tests modules; this sweep exercises packaged artifacts in a browser. The gap between those is where the real bugs live:
| Sweep | Bug found | Why CI was green |
|---|---|---|
| 2026-06-30 | quarkus-ai-chat would not start — OTel api/common version skew from a Dependabot bump | Module tests never boot the sample's fast-jar |
| 2026-07-17 | spring-boot-orchestration-demo crashed on every tool turn — the sample pom hardcoded langchain4j-open-ai:1.15.0 while the reactor manages 1.17.0 | The module built against 1.17.0; only the sample's own jar bundled 1.15.0 |
scripts/release-gate-samples.sh automates the boot-and-assert half of this in
CI. This sweep is the browser half on top of it — the layer that sees
rendering, streaming, transport headers, tool cards, and console errors.
Step 0 Preconditions — build everything, start Ollama, free the ports, open the ledger
Step 1a Samples — 33 samples: launch → drive → collect → verdict → teardown
Step 1b Expo client — the RN client in the iOS simulator
Step 1c CLI — atmosphere run/new/compose/import/checkpoint + distributions
ALL OF PHASE 1 IS COLLECT-ONLY. Do not fix anything mid-sweep.
Step 2 Triage — classify every finding, rank by blast radius
Step 3 Fix — root-cause fix + a regression test per issue, in the right
suite, each proven to bite
Step 4 Re-test — the failed surfaces in full, plus the blast-radius subset
of already-passing ones
Step 5 Report — vault report, CI green, memory updatedStep 1 is deliberately fix-free. Fixing mid-sweep changes the artifact under test and invalidates every sample already verified against the old one. The one exception: a defect that blocks the sweep itself from continuing — fix it, say so in the ledger, and note which already-passed samples were re-run.
curl is allowed only for
port readiness and for headless wire protocols (A2A/MCP/REST) that serve no
HTML. A "works via curl" claim skips the whole JS layer and is a false pass./atmosphere/console/ (Spring
Boot samples redirect / there). A sample that needs a bespoke page instead
of the Console is itself a finding.image node with a
src is a rendered screenshot; the same base64 in a StaticText node means
nothing rendered it. "Server started", "HTTP 200", and "bytes present in the
DOM" are not passes.java -jar (or quarkus-run.jar), never
spring-boot:run / quarkus:dev. Both historical bugs above existed only
at artifact level.pkill -f. Never touch a port or process the sweep
did not start — if a port is occupied, move to another port. The same rule
covers the machine's network: never run networksetup, never take an
interface down, never touch VPN/DNS/proxy settings. The host's Wi-Fi carries
every session the maintainer has open, and a sweep interrupted mid-toggle can
leave the machine offline indefinitely. Any assertion that needs real network
loss is recorded PARTIAL with its unit coverage cited — see
references/expo-sweep.md.git status --porcelain # must be clean
git rev-parse --short HEAD # record this SHA in the ledger
grep -m1 '<version>' pom.xml # record the version under test
./mvnw install -DskipTests -Pfastinstall # full reactor: framework + every sample jar
./scripts/sync-console-bundle.sh --check # the Console you will drive must be current
ollama list # qwen2.5:3b + qwen2.5:7b-instruct-q4_K_M
curl -s -o /dev/null -w '%{http_code}\n' http://localhost:11434/v1/modelsLLM backend is local Ollama, keyless. Use qwen2.5:3b for streaming
samples and qwen2.5:7b-instruct-q4_K_M for tool-heavy agents — 3b emits
invalid tool-call arguments and Ollama answers 400. Note real-ollama is a
CI-harness alias only; AiConfig matches the literal local.
The launcher scrubs ambient LLM env (LLM_API_KEY, LLM_BASE_URL,
LLM_MODE, LLM_MODEL, and the provider keys) from every sample it boots, so
the sweep is reproducible on any machine. SWEEP_KEEP_ENV=1 inherits instead.
If you boot a sample by hand, scrub them yourself — a maintainer's profile
routinely exports these.
Always read the resolved endpoint out of the boot log before driving:
grep 'AI config:' target/sweep/<sample>.logExpect mode=local … endpoint=http://localhost:11434/v1. Anything else means
the sample is not talking to Ollama and the turn's result says nothing about
this build. An explicit LLM_BASE_URL outranks the mode by design, so an
inherited one silently redirects a "local" run to a remote provider — that is
what happened on the 2026-08-07 shakedown before the scrub existed.
Do not use a paid key. The paid-LLM lane is retired; quota starvation is what made the 2026-06 sweep report nine samples as plumbing-only.
Do not use embacle (embacle-server --provider claude_code) for
tool-calling samples — it applies the host CLI's own configuration to
responses and its tool-call fidelity is inconsistent. It is only useful to
demonstrate "a capable model completes this flow cleanly", then stop it.
Ports: the sweep runs on the 9101+ block so it never collides with the
samples' own defaults or the Playwright fixture's 8080–8104. Assignments are
in references/sample-matrix.md.
Open the ledger at claude_docs/sample-sweep-<YYYY-MM-DD>.md (a gitignored
symlink into the vault, so it survives context compaction). Template:
assets/ledger-template.md. Write each row as you finish that sample,
never in a batch at the end.
Work through references/sample-matrix.md in order. For each sample:
# 1. Launch (the helper refuses to boot if the port is already answering)
.claude/skills/release-sample-sweep/scripts/sweep-sample.sh start <sample> \
--port <9101+n> --ready-path <path> --env LLM_MODE=local --env LLM_MODEL=qwen2.5:3bnew_page on the drive URL. Never reuse
the previous sample's page: stale state and leftover console noise both
corrupt the evidence.take_snapshot. Confirm the Console mounted and the transport
badge reads what the matrix expects (Connected · websocket /
· webtransport / · grpc / · ag-ui). A transport that silently fell back
is a finding.references/driving-recipes.md.wait_for the expected text/element, then
re-take_snapshot and confirm the node type (see non-negotiable #3).list_console_messages — every error and warning, verbatimlist_network_requests — any non-2xx/failed requestsweep-sample.sh warnings <sample> — server-side WARN/ERROR/exception/SLF4J
Record warnings even when the sample passes. The warning inventory is half
the value of the sweep and is what the next release's triage starts from.close_page, then
sweep-sample.sh stop <sample>. The helper verifies the port is actually
released; if it is not, stop and investigate before the next sample claims it.samples/spring-boot-ai-classroom/expo-client/ is a native Expo/RN app. It is
not a Maven module, not in cli/samples.json, and unreachable by the
Playwright suites — this sweep is its only gate. It links atmosphere.js by
file path, so it is also the only pre-release check that the client library's
./react-native export works in a real RN runtime.
Driven with the iOS simulator MCP, not chrome-devtools. Full procedure,
including the SERVER_URL port trap and the AppState/NetInfo assertions nothing
else covers: references/expo-sweep.md.
The CLI is the documented Quick Start and ships as four distributions
(curl installer, npx, Homebrew tap, SDKMAN). CI covers list/info, argument
validation, the runtime overlays, and the installers — it never boots a sample
through atmosphere run and looks at the UI, and it has no coverage for
compose or checkpoint.
The manual pass closes that: atmosphere run → browser-driven, atmosphere new
→ scaffold + compile against Maven Central, plus the thin-coverage commands and
a post-publish check of the actually-shipped artifacts. Watch the jar cache —
a stale $ATMOSPHERE_HOME/cache/v<version> boots the previous release and fakes
a pass. Full procedure: references/cli-sweep.md.
With all samples tested, classify each finding before touching any code:
| Class | Meaning | Action |
|---|---|---|
| Framework bug | A module under modules/ is wrong | Fix + regression spec. Release-blocking. |
| Sample bug | Only that sample's code/pom/config is wrong | Fix + regression spec. Release-blocking if the sample ships. |
| Config/env | Sample needs a key, Docker, a collector | Not a bug — document the graceful-degradation behaviour and assert that |
| Model limitation | Small local model can't drive the flow | Prove with a capable model, record, no code change |
| Sweep environment | Port conflict, stale ~/.m2, half-built reactor | Fix the environment and re-run that sample |
Rank by blast radius: shared-module findings first (they can invalidate other samples' passes), then per-sample.
Every issue gets a test, but in the suite that can actually run it:
| Surface the issue is on | Regression home |
|---|---|
| Sample / Console / framework | Playwright spec → references/regression-specs.md |
| CLI | A case in cli/test-cli.sh (a Playwright spec is the wrong vehicle for a shell CLI) |
| Expo / React Native | An atmosphere.js vitest covering the ./react-native export path; if the defect is genuinely RN-runtime-only, name it in the report as manual-sweep-only rather than faking a gate |
For every issue in the framework-bug or sample-bug class:
references/regression-specs.md.SampleLangChain4jVersionLintTest,
which fails the build if any sample pom hardcodes a LangChain4j version.references/retest-subset.md.obsidian-writer skill →
Claude Outputs/Sample-Sweep-chrome-devtools-<date>.md. Promote the ledger:
full matrix with the evidence column, the issues-found-and-fixed section with
commit hashes, methodology caveats, and non-blocking follow-ups.ls samples/ (minus
shared-resources) and cli/samples.json, never from memory.| File | Use |
|---|---|
references/sample-matrix.md | Every sample: boot type, sweep port, drive surface, headline assertion, gating |
references/driving-recipes.md | chrome-devtools call sequences per surface class + browser-layer traps |
references/expo-sweep.md | Step 1b — the RN client in the iOS simulator |
references/cli-sweep.md | Step 1c — what CI already covers, the real gaps, and the CLI pass |
references/regression-specs.md | Where a Playwright spec lives, how to wire it into CI, how to prove it bites |
references/retest-subset.md | Blast radius → which passing samples to re-drive after a fix |
references/troubleshooting.md | Known traps: PNA, long-poll probes, stale jars, port collisions, Quarkus LLM config |
assets/ledger-template.md | The sweep ledger to copy into claude_docs/ |
scripts/sweep-sample.sh | Boot one sample from its packaged artifact on a sweep port and leave it running |
© Atmosphere, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 9 other files (scripts, references, assets) in .claude/skills/release-sample-sweep of Atmosphere/atmosphere.
Open the folder on GitHubat commit 13671cf
Release Sample Sweep 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Release Sample Sweep this skillAtmosphere/atmosphere | 3.8k | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Appllama App Design SkillAppllama/appllama-skills | 2.5k | 1 repos | ~5k | Automated safety check: Pass | MIT | |
| Appllama UsageAppllama/appllama-skills | 2.5k | 1 repos | ~1.6k | Automated safety check: Pass | MIT | |
| Agent Cdpgronxb/codex-relay | 679 | — | ~956 | Automated safety check: Pass | Apache-2.0 | |
| Flutter MCP Toolkit Maintain WebArenukvern/mcp_flutter | 386 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Radon MCPsoftware-mansion-labs/skills | 291 | — | ~665 | Automated safety check: Pass | None |
Appllama/appllama-skills
Build native-feeling, benchmark-quality mobile app screens (Expo / React Native).
Appllama/appllama-skills
Use the Appllama MCP (mcp.appllama.io) well — research real top-grossing mobile apps, their screens, flows, and UI elements, then build from what you learn.
gronxb/codex-relay
Chrome DevTools Protocol CLI workflow for runtime, console, network, trace, memory, and JavaScript CPU profiling analysis.
Arenukvern/mcp_flutter
Maintains showcase/fluttertestapp and intentcall web targets (Chrome, web codegen, WebMCP bootstrap, web-showcase, webmcp verify, Chrome DevTools MCP).
software-mansion-labs/skills
Best practices for using Radon IDE's MCP tools when developing, debugging, and inspecting React Native and Expo apps.
hyodotdev/openiap
Run IAPKit local receipt-validation E2E with the dev.hyo.martie React Native or Expo examples, the compiled packages/kit server, real Convex, and Apple or Google sandbox purchases.
Atmosphere/atmosphere
Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries.
Atmosphere/atmosphere
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax.
Atmosphere/atmosphere
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more.
Atmosphere/atmosphere
Write well-formatted notes to the atmosphere-vault Obsidian knowledge base.
Atmosphere/atmosphere
Work the private register (Atmosphere/atmosphere-carnet) from a session — claim an issue before touching it so peers see who holds it and which session, release or close it when done, file new…
Atmosphere/atmosphere
A skill your agent uses when setting up the shared atmosphere-vault Obsidian vault on a new machine or for a new team member.
Categories
Run the pre-release end-to-end sweep of every user-facing surface — the 33 samples under samples/ (booted from their packaged artifacts and driven in a real browser via chrome-devtools MCP), the…. Release Sample Sweep is an agent skill from Atmosphere/atmosphere. Run the pre-release end-to-end sweep of every user-facing surface — the 33 samples under samples/ (booted from their packaged artifacts and driven in a real browser via chrome-devtools MCP), the Expo/React Native client, and the atmosphere CLI.
Release Sample Sweep fits situations like: tasks that involve Cross-platform mobile apps; tasks that involve Browser testing; tasks that involve LLM inference and serving.
Run `npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a claude-code`. Or copy the skill folder (.claude/skills/release-sample-sweep in Atmosphere/atmosphere) into .claude/skills/release-sample-sweep in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a codex`. Or copy the skill folder (.claude/skills/release-sample-sweep in Atmosphere/atmosphere) into .agents/skills/release-sample-sweep in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Atmosphere/atmosphere --skill release-sample-sweep -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/release-sample-sweep, .gemini/skills/release-sample-sweep, .github/skills/release-sample-sweep and .opencode/skills/release-sample-sweep in your project.
Going by SKILL.md and its folder, Release Sample Sweep needs a shell for the scripts in its folder, the command-line tools its instructions call (git, ollama, curl, java and claude) and credentials named LLM_API_KEY. Our summary lists: A Bash shell; Docker; A credential in LLM_API_KEY.
SKILL.md contains no URLs. Its commands use git and curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Release Sample Sweep is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 15k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Release Sample Sweep: Appllama App Design Skill (Appllama/appllama-skills, 2.5k stars), Appllama Usage (Appllama/appllama-skills, 2.5k stars), Agent Cdp (gronxb/codex-relay, 679 stars) and Flutter MCP Toolkit Maintain Web (Arenukvern/mcp_flutter, 386 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Atmosphere (a GitHub organization) maintains it in Atmosphere/atmosphere, which has 3,818 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 6, 2026.
Source: Atmosphere/atmosphere on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.