Crawl4AI Web Scraping
smallnest/goclaw
Scrapes sites, handles JavaScript-heavy pages and extracts structured data with Crawl4AI, through its crwl CLI or Python SDK, including schema-based extraction without an LLM.
Follow the bundled weighted data-processing pipeline. An agent skill from Jinze-Lee/codex-skills-workbench.
Install Weighted Data Pipeline
$ npx skills add Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Jinze-Lee/codex-skills-workbench weighted-data-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/Jinze-Lee/codex-skills-workbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/weighted-data-pipeline .claude/skills/weighted-data-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 "weighted-data-pipeline" agent skill from https://github.com/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-pipeline into .claude/skills/weighted-data-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weighted-data-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/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-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 Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Jinze-Lee/codex-skills-workbench weighted-data-pipeline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jinze-Lee/codex-skills-workbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/weighted-data-pipeline .agents/skills/weighted-data-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 "weighted-data-pipeline" agent skill from https://github.com/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-pipeline into .agents/skills/weighted-data-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weighted-data-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 Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Jinze-Lee/codex-skills-workbench weighted-data-pipeline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jinze-Lee/codex-skills-workbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/weighted-data-pipeline .cursor/skills/weighted-data-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 "weighted-data-pipeline" agent skill from https://github.com/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-pipeline into .cursor/skills/weighted-data-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weighted-data-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/Jinze-Lee/codex-skills-workbench.git --path skills/weighted-data-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 Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Jinze-Lee/codex-skills-workbench weighted-data-pipeline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jinze-Lee/codex-skills-workbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/weighted-data-pipeline .gemini/skills/weighted-data-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 "weighted-data-pipeline" agent skill from https://github.com/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-pipeline into .gemini/skills/weighted-data-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weighted-data-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 Jinze-Lee/codex-skills-workbench weighted-data-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 Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Jinze-Lee/codex-skills-workbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/weighted-data-pipeline .github/skills/weighted-data-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 "weighted-data-pipeline" agent skill from https://github.com/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-pipeline into .github/skills/weighted-data-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weighted-data-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 Jinze-Lee/codex-skills-workbench --skill weighted-data-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 Jinze-Lee/codex-skills-workbench weighted-data-pipeline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jinze-Lee/codex-skills-workbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/weighted-data-pipeline .opencode/skills/weighted-data-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 "weighted-data-pipeline" agent skill from https://github.com/Jinze-Lee/codex-skills-workbench/tree/main/skills/weighted-data-pipeline into .opencode/skills/weighted-data-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weighted-data-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
weighted-data-pipeline- GitHub stars
- 109
- Token cost
- ~290 tokens
- SKILL.md length
- 109 words
- Files
- 3 (incl. references)
- Skills in repo
- 17
- Repo updated
- First seen
- Licence
- None found
At a glance
Follow the bundled weighted data-processing pipeline. An agent skill from Jinze-Lee/codex-skills-workbench.
- Works in 5 steps: Read references/source-note.md first. → Follow the note's pipeline order, data… → Replace stale file paths, script names,… → …
- Explicitly invokes $weighted-data-pipeline
- SKILL.md covers Overview, Workflow and Source
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Weighted Data Pipeline is an agent skill from Jinze-Lee/codex-skills-workbench. Follow the bundled weighted data-processing pipeline. Use this skill only when the user explicitly invokes $weighted-data-pipeline. Do not auto-select this skill for general data-processing or weighted-analysis tasks.
Its SKILL.md is about 290 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/source-note.md`).
It sits in Data & Analytics, covering Data pipelines and ETL.
When your agent uses it
- Explicitly invokes $weighted-data-pipeline
- Tasks that involve Data pipelines and ETL
Example prompts
- “/weighted-data-pipeline”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Read references/source-note.md first.
- Follow the note's pipeline order, data handoff points, and file-role distinctions closely.
- Replace stale file paths, script names, and intermediate outputs with current project equivalents instead of copying blindly.
- Preserve the original pipeline logic while adapting to the present workspace.
- If the note conflicts with the current user request, follow the current request and explain the adjustment.
What it can do on your machine
Read from SKILL.md and the folder at commit 7aa34a5. 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
Weighted Data Pipeline loads about 290 tokens when it runs, and up to ~649 if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 109 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
Without a licence we can't republish the file, so here is its outline and opening line. It has 109 words (~290 tokens).
“Use references/source-note.md as the source of truth for this skill.”
- name
- weighted-data-pipeline
Files
SKILL.md and 2 other files (references) in skills/weighted-data-pipeline of Jinze-Lee/codex-skills-workbench.
- SKILL.md
- agents/openai.yaml
- references/source-note.md
Open the folder on GitHubat commit 7aa34a5
Compare with similar skills
Weighted Data Pipeline 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 |
|---|---|---|---|---|---|---|
| Weighted Data Pipeline this skillJinze-Lee/codex-skills-workbench | 109 | — | ~290 | Automated safety check: Pass | None | |
| Crawl4AI Web Scrapingsmallnest/goclaw | 599 | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Glue 09 10 Migrationaws-samples/aws-glue-samples | 1.5k | — | ~2.4k | Automated safety check: Pass | MIT-0 | |
| Migrate Glue Devendpoint To Interactive Sessionsaws-samples/aws-glue-samples | 1.5k | — | ~3.6k | Automated safety check: Pass | MIT-0 | |
| Dbt Databricks PR Readydatabricks/dbt-databricks | 380 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Apache Spark EngineerJeffallan/claude-skills | 12k | 1 repos | ~1.7k | Automated safety check: Pass | MIT |
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Categories
Questions about Weighted Data Pipeline
What does Weighted Data Pipeline do?
Follow the bundled weighted data-processing pipeline. An agent skill from Jinze-Lee/codex-skills-workbench. Weighted Data Pipeline is an agent skill from Jinze-Lee/codex-skills-workbench. Follow the bundled weighted data-processing pipeline.
When should I use Weighted Data Pipeline?
Weighted Data Pipeline fits situations like: explicitly invokes $weighted-data-pipeline; tasks that involve Data pipelines and ETL.
How do I install Weighted Data Pipeline in Claude Code?
Run `npx skills add Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a claude-code`. Or copy the skill folder (skills/weighted-data-pipeline in Jinze-Lee/codex-skills-workbench) into .claude/skills/weighted-data-pipeline in your project. Claude Code loads it when a task matches its description.
How do I install Weighted Data Pipeline in Codex?
Run `npx skills add Jinze-Lee/codex-skills-workbench --skill weighted-data-pipeline -a codex`. Or copy the skill folder (skills/weighted-data-pipeline in Jinze-Lee/codex-skills-workbench) into .agents/skills/weighted-data-pipeline in your project. Codex loads it when a task matches its description.
Can I use Weighted Data Pipeline 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 Jinze-Lee/codex-skills-workbench --skill weighted-data-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/weighted-data-pipeline, .gemini/skills/weighted-data-pipeline, .github/skills/weighted-data-pipeline and .opencode/skills/weighted-data-pipeline in your project.
What does Weighted Data Pipeline need to run?
SKILL.md names no scripts, command-line tools or credentials: Weighted Data Pipeline is instructions for the agent only.
Does Weighted Data Pipeline 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 Weighted Data Pipeline 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 Weighted Data Pipeline use?
No licence was found for Weighted Data Pipeline or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Weighted Data Pipeline use?
About 290 tokens (SKILL.md is roughly 1.2k 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 359 tokens, read only when the agent opens those files.
What are the alternatives to Weighted Data Pipeline?
Skills that share tags, products or a category with Weighted Data Pipeline: Crawl4AI Web Scraping (smallnest/goclaw, 599 stars), Glue 09 10 Migration (aws-samples/aws-glue-samples, 1.5k stars), Migrate Glue Devendpoint To Interactive Sessions (aws-samples/aws-glue-samples, 1.5k stars) and Dbt Databricks PR Ready (databricks/dbt-databricks, 380 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Weighted Data Pipeline?
Jinze-Lee (a GitHub user) maintains it in Jinze-Lee/codex-skills-workbench, which has 109 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on May 2, 2026.
Source: Jinze-Lee/codex-skills-workbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.