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.
Document column-level mappings between source and target schemas.
Install Schema Mapper
$ npx skills add nimrodfisher/data-analytics-skills --skill schema-mapper -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nimrodfisher/data-analytics-skills schema-mapper --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/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/02-documentation-knowledge/schema-mapper .claude/skills/schema-mapper && 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 "schema-mapper" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapper into .claude/skills/schema-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-mapper", 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/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapperType 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 nimrodfisher/data-analytics-skills --skill schema-mapper -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nimrodfisher/data-analytics-skills schema-mapper --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/02-documentation-knowledge/schema-mapper .agents/skills/schema-mapper && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "schema-mapper" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapper into .agents/skills/schema-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-mapper", 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 nimrodfisher/data-analytics-skills --skill schema-mapper -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nimrodfisher/data-analytics-skills schema-mapper --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/02-documentation-knowledge/schema-mapper .cursor/skills/schema-mapper && 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 "schema-mapper" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapper into .cursor/skills/schema-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-mapper", 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/nimrodfisher/data-analytics-skills.git --path 02-documentation-knowledge/schema-mapper--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 nimrodfisher/data-analytics-skills --skill schema-mapper -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nimrodfisher/data-analytics-skills schema-mapper --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/02-documentation-knowledge/schema-mapper .gemini/skills/schema-mapper && 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 "schema-mapper" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapper into .gemini/skills/schema-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-mapper", 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 nimrodfisher/data-analytics-skills schema-mapperInstalls 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 nimrodfisher/data-analytics-skills --skill schema-mapper -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/02-documentation-knowledge/schema-mapper .github/skills/schema-mapper && 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 "schema-mapper" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapper into .github/skills/schema-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-mapper", 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 nimrodfisher/data-analytics-skills --skill schema-mapper -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install nimrodfisher/data-analytics-skills schema-mapper --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/02-documentation-knowledge/schema-mapper .opencode/skills/schema-mapper && 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 "schema-mapper" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/schema-mapper into .opencode/skills/schema-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-mapper", 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
schema-mapper- GitHub stars
- 465
- Token cost
- ~614 tokens
- SKILL.md length
- 306 words
- Files
- 4 (incl. scripts, references, assets)
- Skills in repo
- 31
- Repo updated
- First seen
- Licence
- MIT
At a glance
Document column-level mappings between source and target schemas.
- Works in 6 steps: Collect the source schema — list every… → Collect the target schema — same… → Map source columns to target columns —… → …
- Integrating data from multiple systems
- Runs Python scripts from its folder
- Designing ETL transformations
What it does
Schema Mapper is an agent skill from nimrodfisher/data-analytics-skills. Document column-level mappings between source and target schemas. Use when integrating data from multiple systems, designing ETL transformations, or documenting how raw fields become analytical assets.
Its SKILL.md is about 610 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts, reference files and assets (for example `assets/schema_mapping_template.md`, `references/schema_mapping_patterns.md` and `scripts/schema_compare.py`).
It sits in Data & Analytics, covering Data pipelines and ETL. The repository describes itself as: A comprehensive list of Claude & Codex skills for a wide range of data analytics tasks. The licence is MIT.
When your agent uses it
- Integrating data from multiple systems
- Designing ETL transformations
- Documenting how raw fields become analytical assets
Example prompts
- “/schema-mapper”
Requirements
- Python 3
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Collect the source schema — list every column name, data type, nullable flag, and a brief description. Pull from INFORMATION_SCHEMA, a…
- Collect the target schema — same structure for the destination table or model. If the target doesn't exist yet, draft it based on the…
- Map source columns to target columns — for each target column, identify the source column(s) that feed it. Record direct mappings (rename…
- Document transformation rules — for each derived mapping, write the exact transformation (e.g., CAST(amount_cents AS FLOAT) / 100.0…
- Flag gaps — identify target columns with no source (need to be created or defaulted) and source columns with no target (dropped or…
- Produce the mapping document — complete assets/schema_mapping_template.md with the full column inventory and share for review before…
What it can do on your machine
Read from SKILL.md and the folder at commit 9449d36. 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
Ships 1 file in scripts/ (Python), which the agent can run.
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
Schema Mapper loads about 614 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 306 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); the scripts in this folder are not scanned.
SKILL.md
The full file from nimrodfisher/data-analytics-skills at commit 9449d36, republished under its MIT licence (© nimrodfisher). 306 words, ~614 tokens.
Download SKILL.mdSave it as
.claude/skills/schema-mapper/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- schema-mapper
- description
- Document column-level mappings between source and target schemas. Use when integrating data from multiple systems, designing ETL transformations, or documenting how raw fields become analytical assets.
Schema Mapper
When to use
- Integrating a new data source and need to map its fields to the existing data model
- Designing an ETL or dbt transformation and need to document the logic
- Auditing what happened to a field during a migration
- Onboarding a new analyst who needs to understand where columns come from
- Preparing a data catalog entry that requires lineage at the column level
Process
- Collect the source schema — list every column name, data type, nullable flag, and a brief description. Pull from
INFORMATION_SCHEMA, a data dictionary, or the source API documentation. - Collect the target schema — same structure for the destination table or model. If the target doesn't exist yet, draft it based on the analytical requirements.
- Map source columns to target columns — for each target column, identify the source column(s) that feed it. Record direct mappings (rename only) and derived mappings (calculation, type cast, lookup join). Use
scripts/schema_compare.pyto automate direct-name matches. - Document transformation rules — for each derived mapping, write the exact transformation (e.g.,
CAST(amount_cents AS FLOAT) / 100.0,COALESCE(first_name, email)). - Flag gaps — identify target columns with no source (need to be created or defaulted) and source columns with no target (dropped or deferred). Record a decision for each.
- Produce the mapping document — complete
assets/schema_mapping_template.mdwith the full column inventory and share for review before implementation.
Inputs the skill needs
- Source schema: table name, column names, data types, and descriptions
- Target schema: same, or the analytical requirements that define it
- Any existing transformation logic (SQL, dbt models, Python code)
- Business rules that govern how values should be transformed or defaulted
- Stakeholder who can resolve ambiguous fields
Output
scripts/schema_compare.py— compares two schemas and finds direct-name matches and type mismatchesassets/schema_mapping_template.md— completed column-by-column mapping with transformation rules, gaps, and decisions- Optional: transformation SQL or dbt YAML generated from the mapping
© nimrodfisher, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts, references, assets) in 02-documentation-knowledge/schema-mapper of nimrodfisher/data-analytics-skills.
- SKILL.md
- assets/schema_mapping_template.md
- references/schema_mapping_patterns.md
- scripts/schema_compare.py
Open the folder on GitHubat commit 9449d36
Compare with similar skills
Schema Mapper 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 |
|---|---|---|---|---|---|---|
| Schema Mapper this skillnimrodfisher/data-analytics-skills | 465 | — | ~614 | Automated safety check: Pass | MIT | |
| Crawl4AI Web Scrapingsmallnest/goclaw | 598 | 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 | |
| Mz Dbt ReleaseMaterializeInc/materialize | 6.4k | — | ~1.2k | Automated safety check: Pass | Custom licence |
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Categories
Questions about Schema Mapper
What does Schema Mapper do?
Document column-level mappings between source and target schemas. Schema Mapper is an agent skill from nimrodfisher/data-analytics-skills. Document column-level mappings between source and target schemas.
When should I use Schema Mapper?
Schema Mapper fits situations like: integrating data from multiple systems; designing ETL transformations; documenting how raw fields become analytical assets.
How do I install Schema Mapper in Claude Code?
Run `npx skills add nimrodfisher/data-analytics-skills --skill schema-mapper -a claude-code`. Or copy the skill folder (02-documentation-knowledge/schema-mapper in nimrodfisher/data-analytics-skills) into .claude/skills/schema-mapper in your project. Claude Code loads it when a task matches its description.
How do I install Schema Mapper in Codex?
Run `npx skills add nimrodfisher/data-analytics-skills --skill schema-mapper -a codex`. Or copy the skill folder (02-documentation-knowledge/schema-mapper in nimrodfisher/data-analytics-skills) into .agents/skills/schema-mapper in your project. Codex loads it when a task matches its description.
Can I use Schema Mapper 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 nimrodfisher/data-analytics-skills --skill schema-mapper -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/schema-mapper, .gemini/skills/schema-mapper, .github/skills/schema-mapper and .opencode/skills/schema-mapper in your project.
What does Schema Mapper need to run?
Going by SKILL.md and its folder, Schema Mapper needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Schema Mapper 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 Schema Mapper 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Schema Mapper use?
Schema Mapper is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Schema Mapper use?
About 614 tokens (SKILL.md is roughly 2.5k 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 613 tokens, read only when the agent opens those files.
What are the alternatives to Schema Mapper?
Skills that share tags, products or a category with Schema Mapper: Crawl4AI Web Scraping (smallnest/goclaw, 598 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 Schema Mapper?
nimrodfisher (a GitHub user) maintains it in nimrodfisher/data-analytics-skills, which has 465 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on September 25, 2026.
Source: nimrodfisher/data-analytics-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.