Analytics Engineer
borghei/Claude-Skills
Analytics engineering across data modeling, dbt, transformation, and semantic layers.
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts.
$ npx skills add w95/awesome-claude-corporate-skills --skill data-context-extractor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install w95/awesome-claude-corporate-skills data-context-extractor --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/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/10-data-analytics/data-context-extractor .claude/skills/data-context-extractor && 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 "data-context-extractor" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractor into .claude/skills/data-context-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-context-extractor", 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/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractorType 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 w95/awesome-claude-corporate-skills --skill data-context-extractor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install w95/awesome-claude-corporate-skills data-context-extractor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/10-data-analytics/data-context-extractor .agents/skills/data-context-extractor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "data-context-extractor" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractor into .agents/skills/data-context-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-context-extractor", 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 w95/awesome-claude-corporate-skills --skill data-context-extractor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install w95/awesome-claude-corporate-skills data-context-extractor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/10-data-analytics/data-context-extractor .cursor/skills/data-context-extractor && 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 "data-context-extractor" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractor into .cursor/skills/data-context-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-context-extractor", 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/w95/awesome-claude-corporate-skills.git --path 10-data-analytics/data-context-extractor--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 w95/awesome-claude-corporate-skills --skill data-context-extractor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install w95/awesome-claude-corporate-skills data-context-extractor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/10-data-analytics/data-context-extractor .gemini/skills/data-context-extractor && 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 "data-context-extractor" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractor into .gemini/skills/data-context-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-context-extractor", 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 w95/awesome-claude-corporate-skills data-context-extractorInstalls 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 w95/awesome-claude-corporate-skills --skill data-context-extractor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/10-data-analytics/data-context-extractor .github/skills/data-context-extractor && 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 "data-context-extractor" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractor into .github/skills/data-context-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-context-extractor", 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 w95/awesome-claude-corporate-skills --skill data-context-extractor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install w95/awesome-claude-corporate-skills data-context-extractor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/10-data-analytics/data-context-extractor .opencode/skills/data-context-extractor && 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 "data-context-extractor" agent skill from https://github.com/w95/awesome-claude-corporate-skills/tree/main/10-data-analytics/data-context-extractor into .opencode/skills/data-context-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-context-extractor", 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.
data-context-extractorGenerate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts.
Data Context Extractor is an agent skill from w95/awesome-claude-corporate-skills. Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with…
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `references/domain-template.md`, `references/example-output.md` and `references/skill-template.md`).
It sits in Data & Analytics, covering Data analysis, Data warehousing and Skill authoring. The repository describes itself as: 166 production-ready Claude AI skills organized by corporate role — executive leadership, finance, HR, marketing, sales, legal, operations, engineering, product, data, customer…. The licence is MIT.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 78dbc7c. 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 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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.
Data Context Extractor loads about 1.8k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 205 tokens; SKILL.md has 763 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 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.
The full file from w95/awesome-claude-corporate-skills at commit 78dbc7c, republished under its MIT licence (© w95). 763 words, ~1,794 tokens.
.claude/skills/data-context-extractor/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.A meta-skill that extracts company-specific data knowledge from analysts and generates tailored data analysis skills.
This skill has two modes:
Use when: User wants to create a new data context skill for their warehouse.
Step 1: Identify the database type
Ask: "What data warehouse are you using?"
Common options:
Use ~~data warehouse tools (query and schema) to connect. If unclear, check available MCP tools in the current session.
Step 2: Explore the schema
Use ~~data warehouse schema tools to:
Sample exploration queries by dialect:
-- BigQuery: List datasets
SELECT schema_name FROM INFORMATION_SCHEMA.SCHEMATA
-- BigQuery: List tables in a dataset
SELECT table_name FROM `project.dataset.INFORMATION_SCHEMA.TABLES`
-- Snowflake: List schemas
SHOW SCHEMAS IN DATABASE my_database
-- Snowflake: List tables
SHOW TABLES IN SCHEMA my_schemaAfter schema discovery, ask these questions conversationally (not all at once):
Entity Disambiguation (Critical)
"When people here say 'user' or 'customer', what exactly do they mean? Are there different types?"
Listen for:
Primary Identifiers
"What's the main identifier for a [customer/user/account]? Are there multiple IDs for the same entity?"
Listen for:
Key Metrics
"What are the 2-3 metrics people ask about most? How is each one calculated?"
Listen for:
Data Hygiene
"What should ALWAYS be filtered out of queries? (test data, fraud, internal users, etc.)"
Listen for:
Common Gotchas
"What mistakes do new analysts typically make with this data?"
Listen for:
Create a skill with this structure:
[company]-data-analyst/
├── SKILL.md
└── references/
├── entities.md # Entity definitions and relationships
├── metrics.md # KPI calculations
├── tables/ # One file per domain
│ ├── [domain1].md
│ └── [domain2].md
└── dashboards.json # Optional: existing dashboards catalogSKILL.md Template: See references/skill-template.md
SQL Dialect Section: See references/sql-dialects.md and include the appropriate dialect notes.
Reference File Template: See references/domain-template.md
Use when: User has an existing skill but needs to add more context.
Ask user to upload their existing skill (zip or folder), or locate it if already in the session.
Read the current SKILL.md and reference files to understand what's already documented.
Ask: "What domain or topic needs more context? What queries are failing or producing wrong results?"
Common gaps:
For the identified domain:
Explore relevant tables: Use ~~data warehouse schema tools to find tables in that domain
Ask domain-specific questions:
Generate new reference file: Create references/[domain].md using the domain template
Each reference file should include:
Before delivering a generated skill, verify:
© w95, MIT. 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 5 other files (scripts, references) in 10-data-analytics/data-context-extractor of w95/awesome-claude-corporate-skills.
Open the folder on GitHubat commit 78dbc7c
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in w95/awesome-claude-corporate-skills, which our catalogue first saw on October 7, 2026.
Data Context Extractor 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 |
|---|---|---|---|---|---|---|
| Data Context Extractor this skillw95/awesome-claude-corporate-skills | 237 | 1 repos | ~1.8k | Automated safety check: Pass | MIT | |
| Analytics Engineerborghei/Claude-Skills | 881 | — | ~3.4k | Automated safety check: Pass | MIT | |
| Analyzing Dataastronomer/agents | 451 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Chdb Datastorevemetric/vemetric | 394 | 2 repos | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Yichen Wecom Local Vaultmcncarl/yichen-skills | 4.3k | — | ~1.3k | Automated safety check: Pass | Custom licence | |
| Erd Studio Setupliam-machine/erd-studio | 165 | — | ~8.5k | Automated safety check: Pass | Custom licence |
borghei/Claude-Skills
Analytics engineering across data modeling, dbt, transformation, and semantic layers.
astronomer/agents
Queries the data warehouse with SQL and answers business questions about data.
vemetric/vemetric
A skill your agent uses when the user has tabular data (pandas DataFrame, parquet, csv, Arrow, json) and wants to filter, group, aggregate, join, or speed up slow pandas.
mcncarl/yichen-skills
Read, decrypt, query, search, and export local WeCom/企业微信 5.x desktop databases on macOS into a private read-only vault.
liam-machine/erd-studio
Friendly, step-by-step setup for ERD Studio in an existing dbt project, for people who may be new to dbt or data modelling.
kappa90/dinobase
Sets up Dinobase, a local DuckDB database that syncs data from 100+ business sources, then answers questions across them with SQL joins and previewed write-backs.
w95/awesome-claude-corporate-skills
Framework for competitive landscape analysis across any industry.
w95/awesome-claude-corporate-skills
Research a company using Common Room data. An agent skill from w95/awesome-claude-corporate-skills.
w95/awesome-claude-corporate-skills
Prepare for a customer or prospect call using Common Room signals.
w95/awesome-claude-corporate-skills
Generate personalized outreach messages using Common Room signals.
w95/awesome-claude-corporate-skills
Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.).
w95/awesome-claude-corporate-skills
Research a specific person using Common Room data. An agent skill from w95/awesome-claude-corporate-skills.
Categories
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. Data Context Extractor is an agent skill from w95/awesome-claude-corporate-skills. Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts.
Data Context Extractor fits situations like: data analysts want Claude to understand their companys specific data warehouse; metrics definitions; common query patterns.
Run `npx skills add w95/awesome-claude-corporate-skills --skill data-context-extractor -a claude-code`. Or copy the skill folder (10-data-analytics/data-context-extractor in w95/awesome-claude-corporate-skills) into .claude/skills/data-context-extractor in your project. Claude Code loads it when a task matches its description.
Run `npx skills add w95/awesome-claude-corporate-skills --skill data-context-extractor -a codex`. Or copy the skill folder (10-data-analytics/data-context-extractor in w95/awesome-claude-corporate-skills) into .agents/skills/data-context-extractor 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 w95/awesome-claude-corporate-skills --skill data-context-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-context-extractor, .gemini/skills/data-context-extractor, .github/skills/data-context-extractor and .opencode/skills/data-context-extractor in your project.
Going by SKILL.md and its folder, Data Context Extractor needs Python for the scripts in its folder. Our summary lists: Python 3.
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.
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.
Data Context Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.8k tokens (SKILL.md is roughly 7.2k 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 4.5k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Data Context Extractor: Analytics Engineer (borghei/Claude-Skills, 881 stars), Analyzing Data (astronomer/agents, 451 stars), Chdb Datastore (vemetric/vemetric, 394 stars) and Yichen Wecom Local Vault (mcncarl/yichen-skills, 4.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
w95 (a GitHub user) maintains it in w95/awesome-claude-corporate-skills, which has 237 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on February 26, 2026.
Source: w95/awesome-claude-corporate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.