Mz Dbt Release
MaterializeInc/materialize
Cut a dbt-materialize PyPI release: bump the version in version.py and setup.py, date the Unreleased CHANGELOG entry, and open the release PR with a Ship: <url body.
Builds Windmill data pipelines as independent, pipeline-annotated scripts forming a DAG over shared storage, defaulting to DuckDB nodes that materialize into DuckLake tables.
Install Windmill Data Pipeline Author
$ npx skills add windmill-labs/windmill --skill write-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install windmill-labs/windmill write-pipeline --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/windmill-labs/windmill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/system_prompts/auto-generated/skills/write-pipeline .claude/skills/write-pipeline && 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 "write-pipeline" agent skill from https://github.com/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipeline into .claude/skills/write-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-pipeline", 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/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipelineType 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 windmill-labs/windmill --skill write-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install windmill-labs/windmill write-pipeline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/windmill-labs/windmill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/system_prompts/auto-generated/skills/write-pipeline .agents/skills/write-pipeline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "write-pipeline" agent skill from https://github.com/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipeline into .agents/skills/write-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-pipeline", 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 windmill-labs/windmill --skill write-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install windmill-labs/windmill write-pipeline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/windmill-labs/windmill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/system_prompts/auto-generated/skills/write-pipeline .cursor/skills/write-pipeline && 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 "write-pipeline" agent skill from https://github.com/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipeline into .cursor/skills/write-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-pipeline", 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/windmill-labs/windmill.git --path system_prompts/auto-generated/skills/write-pipeline--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 windmill-labs/windmill --skill write-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install windmill-labs/windmill write-pipeline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/windmill-labs/windmill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/system_prompts/auto-generated/skills/write-pipeline .gemini/skills/write-pipeline && 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 "write-pipeline" agent skill from https://github.com/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipeline into .gemini/skills/write-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-pipeline", 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 windmill-labs/windmill write-pipelineInstalls 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 windmill-labs/windmill --skill write-pipeline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/windmill-labs/windmill.git skills-src && mkdir -p .github/skills && cp -r skills-src/system_prompts/auto-generated/skills/write-pipeline .github/skills/write-pipeline && 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 "write-pipeline" agent skill from https://github.com/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipeline into .github/skills/write-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-pipeline", 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 windmill-labs/windmill --skill write-pipeline -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install windmill-labs/windmill write-pipeline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/windmill-labs/windmill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/system_prompts/auto-generated/skills/write-pipeline .opencode/skills/write-pipeline && 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 "write-pipeline" agent skill from https://github.com/windmill-labs/windmill/tree/main/system_prompts/auto-generated/skills/write-pipeline into .opencode/skills/write-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "write-pipeline", 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.
Facts
- Skill name
write-pipeline- GitHub stars
- 18k
- Token cost
- ~4k tokens
- SKILL.md length
- 2,083 words
- Files
- 1
- Skills in repo
- 42
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Builds Windmill data pipelines as independent, pipeline-annotated scripts forming a DAG over shared storage, defaulting to DuckDB nodes that materialize into DuckLake tables.
- Works in 5 steps: Put every node in the same folder: f//.… → Write each node as its own script.… → Start each body with // pipeline, then… → …
- Building a multi-step data pipeline out of independent scripts
- SKILL.md covers Default to DuckDB + DuckLake, Ingesting from Python /…, Storage prerequisites and What makes a script a pipeline…, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
The skill draws a firm line between a flow, which is one runnable orchestrating its own steps, and a data pipeline, which is a set of separately deployed scripts wired together by on and materialize annotations and visualized at /pipeline/<folder>. When a request calls for ingesting, transforming or materializing data across steps, it builds pipeline-annotated scripts rather than a flow.
Its default is a duckdb node per table-producing step, writing a bare SELECT with a materialize-ducklake comment so the runtime handles the write into DuckLake, the lakehouse store the pipeline editor assumes. PostgreSQL is reserved for row-level, transactional mutations against an existing table, and bun or python3 nodes are reserved for non-tabular glue work such as calling an external API, landing any resulting tabular output back in DuckLake rather than a separate store. A DuckLake pipeline needs object storage and a configured DuckLake catalog before it can materialize or read anything, checked with a list command.
When your agent uses it
- Building a multi-step data pipeline out of independent scripts
- Deciding whether a step belongs in DuckDB, Postgres or a glue script
- Diagnosing a pipeline that fails because DuckLake storage is not configured
Example prompts
- “Build a pipeline that ingests the orders CSV and materializes it as a DuckLake table.”
- “Add a step to this pipeline that calls the weather API and lands the result in DuckLake.”
- “Check which DuckLake catalogs this workspace has before I build a new pipeline.”
Requirements
- A Windmill workspace with object storage and a DuckLake catalog configured
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Put every node in the same folder: f//. The folder is the pipeline.
- Write each node as its own script. Default to duckdb materializing into DuckLake (see "Default to DuckDB + DuckLake" above); pick…
- Start each body with // pipeline, then the // on input declarations, then the transform that writes the output.
- Chain nodes by asset URI: read an upstream node's output asset, then // on in the downstream node so the edge forms. Reuse exact asset…
- Don't deploy nodes unless the user asks to. A pipeline only "runs" once its scripts are deployed and their triggers exist.
What it can do on your machine
Read from SKILL.md and the folder at commit fb22e5c. 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 (its code samples are sql, python and typescript).
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
Windmill Data Pipeline Author loads about 4k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 2,083 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.
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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 2,083 words (~3,996 tokens).
“A data pipeline is NOT a flow. A flow is one runnable that orchestrates steps internally. A data pipeline is a set of independent scripts, each deployed on its own, that form a DAG by reading and writing shared storage…”
- name
- write-pipeline
Files
Just SKILL.md in system_prompts/auto-generated/skills/write-pipeline of windmill-labs/windmill.
Open the folder on GitHubat commit fb22e5c
Compare with similar skills
Windmill Data Pipeline Author 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 |
|---|---|---|---|---|---|---|
| Windmill Data Pipeline Author this skillwindmill-labs/windmill | 18k | — | ~4k | Automated safety check: Pass | Custom licence | |
| Mz Dbt ReleaseMaterializeInc/materialize | 6.4k | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| Dinobase Business Data Querieskappa90/dinobase | 263 | — | ~1.5k | Automated safety check: Pass | Custom licence | |
| Create Examplegodatadriven/whirl | 205 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Rocky Pocrocky-data/rocky | 304 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Altimate Data Warehouse DelegateAltimateAI/data-engineering-skills | 128 | — | ~1.4k | Automated safety check: Pass | MIT |
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Authoring a new POC under examples/playground/pocs/. An agent skill from rocky-data/rocky.
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Related
Works with
Categories
Questions about Windmill Data Pipeline Author
What does Windmill Data Pipeline Author do?
Builds Windmill data pipelines as independent, pipeline-annotated scripts forming a DAG over shared storage, defaulting to DuckDB nodes that materialize into DuckLake tables. The skill draws a firm line between a flow, which is one runnable orchestrating its own steps, and a data pipeline, which is a set of separately deployed scripts wired together by on and materialize annotations and visualized at /pipeline/<folder>. When a request calls for ingesting, transforming or materializing data across steps, it builds pipeline-annotated scripts rather than a flow.
When should I use Windmill Data Pipeline Author?
Windmill Data Pipeline Author fits situations like: building a multi-step data pipeline out of independent scripts; deciding whether a step belongs in DuckDB, Postgres or a glue script; diagnosing a pipeline that fails because DuckLake storage is not configured.
How do I install Windmill Data Pipeline Author in Claude Code?
Run `npx skills add windmill-labs/windmill --skill write-pipeline -a claude-code`. Or copy the skill folder (system_prompts/auto-generated/skills/write-pipeline in windmill-labs/windmill) into .claude/skills/write-pipeline in your project. Claude Code loads it when a task matches its description.
How do I install Windmill Data Pipeline Author in Codex?
Run `npx skills add windmill-labs/windmill --skill write-pipeline -a codex`. Or copy the skill folder (system_prompts/auto-generated/skills/write-pipeline in windmill-labs/windmill) into .agents/skills/write-pipeline in your project. Codex loads it when a task matches its description.
Can I use Windmill Data Pipeline Author 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 windmill-labs/windmill --skill write-pipeline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/write-pipeline, .gemini/skills/write-pipeline, .github/skills/write-pipeline and .opencode/skills/write-pipeline in your project.
What does Windmill Data Pipeline Author need to run?
SKILL.md names no scripts, command-line tools or credentials: Windmill Data Pipeline Author is instructions for the agent only. Our summary lists: A Windmill workspace with object storage and a DuckLake catalog configured.
Does Windmill Data Pipeline Author 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 Windmill Data Pipeline Author 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 Windmill Data Pipeline Author use?
Windmill Data Pipeline Author has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Windmill Data Pipeline Author use?
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.
What are the alternatives to Windmill Data Pipeline Author?
Skills that share tags, products or a category with Windmill Data Pipeline Author: Mz Dbt Release (MaterializeInc/materialize, 6.4k stars), Dinobase Business Data Queries (kappa90/dinobase, 263 stars), Create Example (godatadriven/whirl, 205 stars) and Rocky Poc (rocky-data/rocky, 304 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Windmill Data Pipeline Author?
windmill-labs (a GitHub organization) maintains it in windmill-labs/windmill, which has 18,146 GitHub stars. The repository holds 42 skills in this directory. The repository was last updated on October 9, 2026.
Source: windmill-labs/windmill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.