Attribution Model
indranilbanerjee/digital-marketing-pro
Design a multi-touch attribution strategy — recommends the best-fit model for the business's sales cycle and data maturity, defines credit-distribution rules and lookback windows, maps…
Build managed ingestion pipelines into Databricks using Lakeflow Connect.
Install Databricks Lakeflow Connect
$ npx skills add databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install databricks/databricks-agent-skills databricks-lakeflow-connect --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/databricks/databricks-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/databricks-lakeflow-connect .claude/skills/databricks-lakeflow-connect && 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 "databricks-lakeflow-connect" agent skill from https://github.com/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connect into .claude/skills/databricks-lakeflow-connect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databricks-lakeflow-connect", 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/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connectType 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 databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install databricks/databricks-agent-skills databricks-lakeflow-connect --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databricks/databricks-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/databricks-lakeflow-connect .agents/skills/databricks-lakeflow-connect && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "databricks-lakeflow-connect" agent skill from https://github.com/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connect into .agents/skills/databricks-lakeflow-connect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databricks-lakeflow-connect", 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 databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install databricks/databricks-agent-skills databricks-lakeflow-connect --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databricks/databricks-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/databricks-lakeflow-connect .cursor/skills/databricks-lakeflow-connect && 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 "databricks-lakeflow-connect" agent skill from https://github.com/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connect into .cursor/skills/databricks-lakeflow-connect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databricks-lakeflow-connect", 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/databricks/databricks-agent-skills.git --path skills/databricks-lakeflow-connect--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 databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install databricks/databricks-agent-skills databricks-lakeflow-connect --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databricks/databricks-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/databricks-lakeflow-connect .gemini/skills/databricks-lakeflow-connect && 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 "databricks-lakeflow-connect" agent skill from https://github.com/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connect into .gemini/skills/databricks-lakeflow-connect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databricks-lakeflow-connect", 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 databricks/databricks-agent-skills databricks-lakeflow-connectInstalls 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 databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/databricks/databricks-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/databricks-lakeflow-connect .github/skills/databricks-lakeflow-connect && 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 "databricks-lakeflow-connect" agent skill from https://github.com/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connect into .github/skills/databricks-lakeflow-connect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databricks-lakeflow-connect", 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 databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install databricks/databricks-agent-skills databricks-lakeflow-connect --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databricks/databricks-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/databricks-lakeflow-connect .opencode/skills/databricks-lakeflow-connect && 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 "databricks-lakeflow-connect" agent skill from https://github.com/databricks/databricks-agent-skills/tree/main/skills/databricks-lakeflow-connect into .opencode/skills/databricks-lakeflow-connect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databricks-lakeflow-connect", 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
databricks-lakeflow-connect- GitHub stars
- 345
- Token cost
- ~3.8k tokens
- SKILL.md length
- 1,487 words
- Files
- 8 (incl. references, assets)
- Skills in repo
- 32
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Build managed ingestion pipelines into Databricks using Lakeflow Connect.
- Works in 4 steps: SaaS pull — connector reads from an… → Database CDC via gateway — an ingestion… → Query-based — for sources without native… → …
- Ingesting from SaaS apps (Salesforce
- SKILL.md covers What Is Lakeflow Connect?, Is Lakeflow Connect the right…, Connector catalog and Required Tools, plus 11 more sections
- Calls databricks
What it does
Databricks Lakeflow Connect is an agent skill from databricks/databricks-agent-skills, published by the product's own GitHub organization. Build managed ingestion pipelines into Databricks using Lakeflow Connect. Use when ingesting from SaaS apps (Salesforce, Workday Reports, ServiceNow, Google Analytics 4, HubSpot, Confluence) or databases (SQL Server cloud and on-prem; PostgreSQL/MySQL CDC in PuPr) into Unity Catalog with serverless pipelines.
Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files and assets (for example `agents/openai.yaml`, `references/1-saas-connectors.md` and `references/2-database-connectors.md`). Compatibility notes: Requires databricks CLI (= v0.294.0)
It sits in Sales & Support, covering CRM management and Serverless. It works with Databricks, Salesforce, Microsoft SQL Server and MySQL. The repository describes itself as: Databricks AI Tools: skills and plugins for building on Databricks with Claude Code, Cursor, Codex, GitHub Copilot, and other AI coding agents.
When your agent uses it
- Ingesting from SaaS apps (Salesforce
- Workday Reports
- Google Analytics 4
- Databases (SQL Server cloud and on-prem
Example prompts
- “/databricks-lakeflow-connect”
Requirements
- Compatibility (from SKILL.md): Requires databricks CLI (>= v0.294.0)
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- SaaS pull — connector reads from an external SaaS via OAuth or API key, lands in a streaming Delta table.
- Database CDC via gateway — an ingestion gateway runs in the customer's network, stages change events to a UC Volume, a serverless…
- Query-based — for sources without native CDC (Oracle / Teradata / SQL Server / PG / MySQL query-based, Snowflake / Redshift / Synapse /…
- Community connectors — template-based, out of scope for this skill.
What it can do on your machine
Read from SKILL.md and the folder at commit f4fcec5. 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
Shell commands in SKILL.md call:
databricks
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
docs.databricks.comdatabricks.com
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.
Compatibility
Requires databricks CLI (>= v0.294.0)
From compatibility in the SKILL.md frontmatter.
Context cost
Databricks Lakeflow Connect loads about 3.8k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 1,487 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 1,487 words (~3,796 tokens).
“Build managed ingestion pipelines that pull from SaaS apps and databases into Unity Catalog Delta tables, governed end-to-end and powered by serverless Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables / DLT).”
- name
- databricks-lakeflow-connect
- compatibility
- Requires databricks CLI (>= v0.294.0)
- metadata.version
- 0.1.0
- parent
- databricks-core
Files
SKILL.md and 7 other files (references, assets) in skills/databricks-lakeflow-connect of databricks/databricks-agent-skills.
- SKILL.md
- agents/openai.yaml
- assets/databricks.png
- assets/databricks.svg
- references/1-saas-connectors.md
- references/2-database-connectors.md
- references/4-ingestion-decision-tree.md
- references/5-troubleshooting-and-monitoring.md
Open the folder on GitHubat commit f4fcec5
Compare with similar skills
Databricks Lakeflow Connect 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 |
|---|---|---|---|---|---|---|
| Databricks Lakeflow Connect this skilldatabricks/databricks-agent-skills | 345 | — | ~3.8k | Automated safety check: Pass | Custom licence | |
| Attribution Modelindranilbanerjee/digital-marketing-pro | 854 | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Airbyte AgentKilo-Org/kilo-marketplace | 189 | — | ~2.2k | Automated safety check: Pass | Custom licence | |
| Churn Riskindranilbanerjee/digital-marketing-pro | 854 | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Lead Importindranilbanerjee/digital-marketing-pro | 854 | 1 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Pipeline Updateindranilbanerjee/digital-marketing-pro | 854 | 1 repos | ~3.3k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Databricks Lakeflow Connect
What does Databricks Lakeflow Connect do?
Build managed ingestion pipelines into Databricks using Lakeflow Connect. Databricks Lakeflow Connect is an agent skill from databricks/databricks-agent-skills, published by the product's own GitHub organization. Build managed ingestion pipelines into Databricks using Lakeflow Connect.
When should I use Databricks Lakeflow Connect?
Databricks Lakeflow Connect fits situations like: ingesting from SaaS apps (Salesforce; workday Reports; google Analytics 4; databases (SQL Server cloud and on-prem.
How do I install Databricks Lakeflow Connect in Claude Code?
Run `npx skills add databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a claude-code`. Or copy the skill folder (skills/databricks-lakeflow-connect in databricks/databricks-agent-skills) into .claude/skills/databricks-lakeflow-connect in your project. Claude Code loads it when a task matches its description.
How do I install Databricks Lakeflow Connect in Codex?
Run `npx skills add databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a codex`. Or copy the skill folder (skills/databricks-lakeflow-connect in databricks/databricks-agent-skills) into .agents/skills/databricks-lakeflow-connect in your project. Codex loads it when a task matches its description.
Can I use Databricks Lakeflow Connect 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 databricks/databricks-agent-skills --skill databricks-lakeflow-connect -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/databricks-lakeflow-connect, .gemini/skills/databricks-lakeflow-connect, .github/skills/databricks-lakeflow-connect and .opencode/skills/databricks-lakeflow-connect in your project.
What does Databricks Lakeflow Connect need to run?
Going by SKILL.md and its folder, Databricks Lakeflow Connect needs the command-line tools its instructions call (databricks). Compatibility (from SKILL.md): Requires databricks CLI (>= v0.294.0).
Does Databricks Lakeflow Connect access the network?
SKILL.md names 2 domains. As links in the text: docs.databricks.com and databricks.com. This is read from the text; nothing was executed.
Is Databricks Lakeflow Connect 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 Databricks Lakeflow Connect use?
Databricks Lakeflow Connect 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 Databricks Lakeflow Connect use?
About 3.8k tokens (SKILL.md is roughly 15k 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 6.9k tokens, read only when the agent opens those files.
What are the alternatives to Databricks Lakeflow Connect?
Skills that share tags, products or a category with Databricks Lakeflow Connect: Attribution Model (indranilbanerjee/digital-marketing-pro, 854 stars), Airbyte Agent (Kilo-Org/kilo-marketplace, 189 stars), Churn Risk (indranilbanerjee/digital-marketing-pro, 854 stars) and Lead Import (indranilbanerjee/digital-marketing-pro, 854 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Databricks Lakeflow Connect?
databricks (a GitHub organization, an official publisher) maintains it in databricks/databricks-agent-skills, which has 345 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on October 6, 2026.
Source: databricks/databricks-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.