Fly Io Deployer
LeoYeAI/openclaw-master-skills
Deploy and operate Node, Python, Go, Rust, Elixir, and Docker apps on Fly.io with production-grade fly.toml authoring, Machines API orchestration, region selection (latency vs sovereignty vs…
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
$ npx skills add GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GreptimeTeam/greptimedb greptimedb-development-docker-image --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/GreptimeTeam/greptimedb.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/greptimedb-development-docker-image .claude/skills/greptimedb-development-docker-image && 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 "greptimedb-development-docker-image" agent skill from https://github.com/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-image into .claude/skills/greptimedb-development-docker-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "greptimedb-development-docker-image", 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/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-imageType 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 GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GreptimeTeam/greptimedb greptimedb-development-docker-image --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GreptimeTeam/greptimedb.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/greptimedb-development-docker-image .agents/skills/greptimedb-development-docker-image && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "greptimedb-development-docker-image" agent skill from https://github.com/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-image into .agents/skills/greptimedb-development-docker-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "greptimedb-development-docker-image", 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 GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GreptimeTeam/greptimedb greptimedb-development-docker-image --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GreptimeTeam/greptimedb.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/greptimedb-development-docker-image .cursor/skills/greptimedb-development-docker-image && 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 "greptimedb-development-docker-image" agent skill from https://github.com/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-image into .cursor/skills/greptimedb-development-docker-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "greptimedb-development-docker-image", 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/GreptimeTeam/greptimedb.git --path .agents/skills/greptimedb-development-docker-image--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 GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GreptimeTeam/greptimedb greptimedb-development-docker-image --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GreptimeTeam/greptimedb.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/greptimedb-development-docker-image .gemini/skills/greptimedb-development-docker-image && 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 "greptimedb-development-docker-image" agent skill from https://github.com/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-image into .gemini/skills/greptimedb-development-docker-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "greptimedb-development-docker-image", 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 GreptimeTeam/greptimedb greptimedb-development-docker-imageInstalls 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 GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/GreptimeTeam/greptimedb.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/greptimedb-development-docker-image .github/skills/greptimedb-development-docker-image && 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 "greptimedb-development-docker-image" agent skill from https://github.com/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-image into .github/skills/greptimedb-development-docker-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "greptimedb-development-docker-image", 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 GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install GreptimeTeam/greptimedb greptimedb-development-docker-image --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GreptimeTeam/greptimedb.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/greptimedb-development-docker-image .opencode/skills/greptimedb-development-docker-image && 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 "greptimedb-development-docker-image" agent skill from https://github.com/GreptimeTeam/greptimedb/tree/main/.agents/skills/greptimedb-development-docker-image into .opencode/skills/greptimedb-development-docker-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "greptimedb-development-docker-image", 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.
greptimedb-development-docker-imagePackages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
The skill follows GreptimeDB's documented development-image procedure: build greptime with Cargo's nightly profile, copy the binary into the Docker context as ./greptime, and build the supplied Dockerfile, which uses Ubuntu 24.04 only as the runtime base and exposes the binary as its entrypoint. It is explicitly not a release workflow and must not be used to publish production or release artifacts.
Before building, the agent gathers inputs in a single batch configuration: the source repository, the edition and binary name (open-source or Enterprise), the Cargo profile, a target platform preselected as linux/amd64 unless Docker runs on arm64, the build mode (a loadable debug image or a registry push), and the registry, repository and tag read from the workspace's .env, with the tag incremented if it already exists. Non-secret image settings are kept in .env for the next build.
Python and shell scripts handle platform detection, binary builds, context preparation, tag selection and image builds, and tests cover platform and config handling. Docker with Buildx is required for cross-platform builds, while Podman works only for native-platform builds.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit a8e293f. 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 8 files in scripts/ (Python and Shell), which the agent can run.
Shell commands in SKILL.md call:
dockerpython3podmancargoFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use docker, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires Docker with Buildx for cross-platform builds; Podman is supported for native-platform builds.
From compatibility in the SKILL.md frontmatter.
GreptimeDB Dev Docker Image loads about 4k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 1,867 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 noted patterns worth knowing about, such as sudo or a known installer.
retain the non-secret image settings in `.env` forORY` only from the selected workspace's `.env` and prefill them in the batch configuration. Example: `registry.example.cTAG` only from the selected workspace's `.env` and prefill it in the batch configuration. When the tag exists in the selreference, build mode, and non-secret `.env` values.| Registry/repository | Use `.env` defaults, enter new values |st changed non-secret image settings to `.env`;selected workspace's `.env`;confirm it before `.env` is updated or an image is built. Never use automaticlives only in the selected workspace's `.env`. Thekeys and never reads or displays other `.env`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 GreptimeTeam/greptimedb at commit a8e293f, republished under its Apache-2.0 licence (© GreptimeTeam). 1,867 words, ~4,001 tokens.
.claude/skills/greptimedb-development-docker-image/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.Package a locally built GreptimeDB binary into a development-only Docker
image for debugging and local-cluster testing, optionally push it to a
development registry, and retain the non-secret image settings in .env for
the next build. It is not a release-image workflow and must not be used to
publish a production or release artifact.
This skill follows the documented development-image build procedure:
greptime with Cargo's nightly profile../greptime.Dockerfile, which uses Ubuntu 24.04 only as the runtime
base image and exposes the greptime binary as its entrypoint.Collect or discover the following before any build or push:
| Input | Discovery and rule |
|---|---|
| Source repository | Treat the directory in which this skill is invoked as the default workspace. Include it as an editable field in the batch configuration; do not ask a separate confirmation. Do not assume open-source versus Enterprise. |
| Edition and binary | Default to greptime; use the binary name the user requests for Enterprise builds. The copied Docker-context filename must always be greptime. |
| Cargo profile and binary source | Include this in the batch configuration. Default to rebuilding nightly; reuse an existing binary only after the user explicitly accepts that its freshness is unverified. |
| Target platform | Preselect linux/amd64 unless Docker's server is linux/arm64, then preselect linux/arm64. Let the user override it in the batch configuration. Ubuntu 24.04 is the runtime base image, not a target-platform choice. Each image has exactly one target platform, but it may differ from the host platform. |
| Build mode | Ask whether the user wants a locally loadable debug image or a registry push. |
| Registry/repository | Read IMAGE_REGISTRY and IMAGE_REPOSITORY only from the selected workspace's .env and prefill them in the batch configuration. Example: registry.example.com/team + greptimedb-dev. |
| Tag | Read IMAGE_TAG only from the selected workspace's .env and prefill it in the batch configuration. When the tag exists in the selected registry, preselect an incremented version. |
Use the image reference ${IMAGE_REGISTRY}/${IMAGE_REPOSITORY}:${IMAGE_TAG}.
If the registry is intentionally empty, omit its slash rather than producing a
leading slash.
Use the platform's interactive prompt component for every question, selection, and confirmation. Do not ask an open-ended text question when a single-choice, multi-select, or confirmation component can represent the decision. If the platform does not provide an interactive component, use the equivalent numbered or lettered prompt below and wait for input before continuing.
Minimize user round trips: run the collector first against the invocation directory, then use one interactive form or batched prompt to collect workspace, edition/binary, profile/reuse-or-rebuild choice, target platform, build mode, registry/repository, tag, and whether to inspect the configured registry tag. Use the invocation directory as the editable workspace default. Prefill collector values and mark recommended defaults. If the user changes workspace, rerun the collector for that workspace without asking another configuration question. Only ask a follow-up if information is missing or invalid, or a safety gate is required. Treat unchanged prefilled values as accepted.
Keep separate confirmation components only for elevated privileges: sudo,
package installation, and privileged QEMU setup. Use one final confirmation for
all non-privileged selected work.
Always offer Cancel for an action that can write state, build, push, or
require elevated privileges. Display the relevant preview before the user
confirms it: source/binary path, file architecture result, platform(s), image
reference, build mode, and non-secret .env values.
Use single-choice controls inside the one batch form for mutually exclusive choices:
| Decision | Required choices |
|---|---|
| Cargo output | Rebuild nightly (recommended), reuse an existing binary only with a freshness-unverified acknowledgement, choose a profile/binary |
| Target platform | linux/amd64 (default unless Docker server is arm64), linux/arm64 (default when Docker server is arm64). The selected image may be cross-built with Buildx. |
| Build mode | Load locally (recommended), push to development registry |
| Registry/repository | Use .env defaults, enter new values |
| Tag | Use proposed increment when the configured tag exists, enter a version |
When push is selected and the image configuration is complete, automatically
run the read-only registry-tag check. It may return unknown; do not treat that
as a missing tag.
Use one final confirmation for all selected non-privileged operations:
.env;The final confirmation must clearly state: “This creates a development and local-cluster test image, not a release or production artifact.”
For a real multi-select only, use lettered choices ([A], [B]) and accept
all, none, or cancel; otherwise use single-choice components.
Before asking the profile, registry, or tag questions, run the bundled,
read-only collector. It works on macOS and Linux, does not invoke cargo build,
and emits JSON that can be shown or summarized to the user:
python3 <skill-dir>/scripts/collect_context.py \
--source <source-checkout> \
--bin greptime \
--profile nightly \
[--target <rust-target>]Use its report to identify:
IMAGE_REGISTRY, IMAGE_REPOSITORY, or IMAGE_TAG values in the
selected workspace's .env;--bin exists;When push is selected and image configuration is complete, rerun the collector
with --check-registry-tag and all selected image values. It uses the selected
engine's read-only manifest inspection and returns exists or unknown;
unknown includes an unavailable registry, an absent tag, or missing
authentication and must not be treated as an absent tag.
python3 <skill-dir>/scripts/collect_context.py \
--source <source-checkout> \
--bin <binary> \
--profile <profile> \
--engine <docker|podman> \
--registry <registry> \
--repository <repository> \
--tag <tag> \
--check-registry-tagWhen the status is exists and the tag ends in a number, preselect the
collector's candidate_tag as the next development tag. The user must still
confirm it before .env is updated or an image is built. Never use automatic
incrementing as permission to overwrite or push an existing image.
If Cargo metadata or the requested binary target is unavailable, stop before building and ask the user to correct the source path or binary target.
The profile/binary choice is a field in the batch configuration, not a separate
question. Its default is the existing nightly output when present:
Question: Which Cargo build output should package this image?
Options:
- Rebuild nightly (Recommended): run Cargo with `--profile nightly`, then use its output.
- Reuse nightly output: use the existing output only after showing its path, modification time, size, and matching platform; freshness is unverified.
- Choose profile or binary: provide a different Cargo profile or an explicit binary path.Do not infer that a binary under target/debug, target/release, or another
profile is suitable. For an existing binary, show its resolved path and run
file before asking for final build confirmation.
The image configuration lives only in the selected workspace's .env. The
collector reads only the following keys and never reads or displays other .env
values:
IMAGE_REGISTRY=registry.example.com/team
IMAGE_REPOSITORY=greptimedb-dev
IMAGE_TAG=dev-001.env if it exists. Ignore blank lines and # comments..env confirmation and do not update the file. Otherwise,
preview only the changed IMAGE_* values, request confirmation, and update
the file while preserving unrelated entries and comments.docker login
output in .env, build commands, logs, or responses. Ask the user to log in
themselves if a push needs authentication.For a repeated build, offer an incremented tag before asking. Use
scripts/next_image_tag.py --tag <existing-tag> to calculate it. It increments
the final numeric component while preserving zero padding:
weny-2025-0715-01 -> weny-2025-0715-02
v0.1.4 -> v0.1.5
debug-009 -> debug-010If the saved tag has no trailing number, ask the user for the next tag rather than inventing a versioning convention. Do not overwrite an existing image tag without explicit user confirmation.
Only if a managed value is missing or differs, persist the values with the bundled helper after confirmation instead of hand-editing the file:
python3 <skill-dir>/scripts/update_image_env.py \
--env <source-checkout>/.env \
--registry <registry> \
--repository <repository> \
--tag <tag>Run these checks and report the selected path:
uname -s
uname -m
docker version --format '{{.Server.Os}}/{{.Server.Arch}}'
docker buildx version
docker buildx inspect --bootstrapFor a native-platform build, Podman can be used if Docker is unavailable. For any non-native request, require Docker Buildx. Do not silently fall back to a native build when the requested image platform differs.
If the requested target is unavailable, stop and ask the user to configure a Buildx builder and cross-compilation toolchain externally. Do not automate privileged QEMU or binfmt setup, and never run an unpinned privileged image.
From the source checkout, build the requested binary. For open-source amd64:
<skill-dir>/scripts/build_binary.sh \
--source <source-checkout> --package cmd --bin greptime --profile nightlyFor open-source arm64:
<skill-dir>/scripts/build_binary.sh \
--source <source-checkout> \
--package cmd \
--bin greptime \
--profile nightly \
--target aarch64-unknown-linux-gnuFor Enterprise, use the user-provided executable target, for example:
<skill-dir>/scripts/build_binary.sh \
--source <source-checkout> --bin greptime-ent-cloud --profile nightlyFor a user-selected profile, replace nightly in the helper call and resolve
the binary under target/<profile>/<binary> (or
target/<rust-target>/<profile>/<binary> for cross-compilation). Reuse the
existing target file only when the interactive profile question selected reuse;
otherwise invoke the helper to rebuild it.
Do not use a binary compiled for the host architecture in an image intended for
another architecture. Determine the binary path from the Cargo target and
profile, then copy it into the Docker context as greptime:
cp <source-target-binary> <build-context>/greptimeVerify it before building the image with file <build-context>/greptime; its
reported architecture must match the requested target platform.
Create a fresh isolated build context (never use the repository root) and use the bundled preparation script. The helper rejects an existing Dockerfile or binary output to prevent accidental context reuse:
<skill-dir>/scripts/prepare_context.sh \
--context "$(mktemp -d)" \
--binary <source-target-binary> \
--dockerfile <skill-dir>/assets/Dockerfile \
--platform <platform>Run the command only after the user confirms the final image reference and whether it should be pushed.
Use the bundled build helper rather than spelling out individual Docker or Podman commands. It follows the existing scripts' Docker-first/Podman-fallback behavior, uses Buildx for a non-native Docker request, and accepts exactly one target platform per image:
<skill-dir>/scripts/build_image.sh \
--context <build-context> \
--image <image-reference> \
--platform <platform> \
--mode local|push--mode local builds a native image locally or uses docker buildx --load for
a non-native image. --mode push pushes the selected single-platform image.
The helper never pushes in local mode.
This is intentionally a runtime image built from a precompiled binary, not a
multi-stage Dockerfile. Ubuntu 24.04 is the runtime base image only; select one
target platform separately as linux/amd64 or linux/arm64. Only introduce a
multi-stage Dockerfile if the user asks to compile within Docker or the local
Rust toolchain cannot build the required target. Keep the final Ubuntu 24.04
runtime stage and existing entrypoint unless the user asks to change runtime
behavior.
At the final confirmation, repeat that the selected reference is a development/local-cluster test image, not a release artifact. If the user requests a release or production image, stop and direct them to the release process instead.
For a local image, use the selected engine to inspect its architecture and
start it with --help:
docker image inspect <image-reference> --format '{{.Os}}/{{.Architecture}}'
docker run --rm <image-reference> --helpFor Podman, use podman image inspect <image-reference> and
podman run --rm <image-reference> --help. For a pushed Podman image, use
podman manifest inspect <image-reference>.
For a pushed image, inspect its remote manifest:
docker buildx imagetools inspect <image-reference>Report the final image reference, target platform, source binary path, and whether the image was loaded locally or pushed.
docker login, privileged QEMU setup, package installation, or
overwrite a tag without confirmation..env entries as part
of this workflow.© GreptimeTeam, 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 11 other files (scripts, assets) in .agents/skills/greptimedb-development-docker-image of GreptimeTeam/greptimedb.
Open the folder on GitHubat commit a8e293f
GreptimeDB Dev Docker Image 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 |
|---|---|---|---|---|---|---|
| GreptimeDB Dev Docker Image this skillGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Fly Io DeployerLeoYeAI/openclaw-master-skills | 2.2k | — | ~6.3k | Automated safety check: Notes | MIT | |
| Deploy To Tempsgotempsh/temps | 831 | — | ~1.3k | Automated safety check: Notes | Apache-2.0 | |
| Rust Deployable Servicehashgraph-online/awesome-codex-plugins | 1.3k | — | ~796 | Automated safety check: Pass | MIT | |
| Monstermq Broker Configvogler75/monster-mq | 143 | — | ~2.2k | Automated safety check: Pass | GPL-3.0 | |
| Funnelcake Deployment Workflowdivinevideo/divine-mobile | 266 | — | ~3.6k | Automated safety check: Pass | MPL-2.0 |
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GreptimeTeam/greptimedb
Diagnoses a failed GreptimeDB fuzz CI job by pulling its GitHub Actions logs and fuzz artifacts, then matching the evidence to the local source code.
GreptimeTeam/greptimedb
Runbook for publishing a GreptimeDB version: pick the release branch, verify the Cargo version, then tag, create the GitHub release and open the docs note PR.
GreptimeTeam/greptimedb
Generates a GreptimeDB release changelog with git cliff, subtracts patch PRs already shipped, rebuilds contributors and prepares the docs-repo blog PR.
Categories
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry. 04 only as the runtime base and exposes the binary as its entrypoint. It is explicitly not a release workflow and must not be used to publish production or release artifacts.
GreptimeDB Dev Docker Image fits situations like: packaging a locally built GreptimeDB binary for local-cluster debugging; cross-building a development image for another platform; pushing a non-release GreptimeDB or Enterprise image to a development registry.
Run `npx skills add GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a claude-code`. Or copy the skill folder (.agents/skills/greptimedb-development-docker-image in GreptimeTeam/greptimedb) into .claude/skills/greptimedb-development-docker-image in your project. Claude Code loads it when a task matches its description.
Run `npx skills add GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a codex`. Or copy the skill folder (.agents/skills/greptimedb-development-docker-image in GreptimeTeam/greptimedb) into .agents/skills/greptimedb-development-docker-image 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 GreptimeTeam/greptimedb --skill greptimedb-development-docker-image -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/greptimedb-development-docker-image, .gemini/skills/greptimedb-development-docker-image, .github/skills/greptimedb-development-docker-image and .opencode/skills/greptimedb-development-docker-image in your project.
Going by SKILL.md and its folder, GreptimeDB Dev Docker Image needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (docker, python3, podman and cargo). Our summary lists: Docker with Buildx for cross-platform builds, or Podman for native builds; Cargo and a GreptimeDB source checkout; Python, for the helper scripts. Compatibility (from SKILL.md): Requires Docker with Buildx for cross-platform builds; Podman is supported for native-platform builds..
SKILL.md contains no URLs. Its commands use docker, 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 notes only (mentions a .env file), nothing it rates as a warning. 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.
GreptimeDB Dev Docker Image 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 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with GreptimeDB Dev Docker Image: Fly Io Deployer (LeoYeAI/openclaw-master-skills, 2.2k stars), Deploy To Temps (gotempsh/temps, 831 stars), Rust Deployable Service (hashgraph-online/awesome-codex-plugins, 1.3k stars) and Monstermq Broker Config (vogler75/monster-mq, 143 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
GreptimeTeam (a GitHub organization) maintains it in GreptimeTeam/greptimedb, which has 6,727 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 10, 2026.
Source: GreptimeTeam/greptimedb on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.