dr-extract
Extract validated financial data from Datarails Finance OS to Excel — a RAW FULL-YEAR export — a 4-sheet workbook (P&L, Balance Sheet, KPIs including SaaS metrics where sourceable from the org's data, and validation checks); no analysis or narrative. For an analyzed workbook use intelligence; for an executive deck use insights. Self-contained — discovers the client's tables and fields on its own, no profile or setup step required.
Install
With your agent
Install OMGSkills skill "datarails/dr-claude-code-plugins-re:skills/extract" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/Datarails/dr-claude-code-plugins-re /tmp/dr-claude-code-plugins-re && ln -s /tmp/dr-claude-code-plugins-re/skills/extract ~/.claude/skills/dr-extractFrom README
Datarails Financial Data Extraction Extract validated financial data from Finance OS to Excel workbooks. Data is pulled via MCP tools and the workbook is built locally with openpyxl. No server-side rendering. The workbook contains: P&L Data: Revenue, COGS, Operating Expenses by month KPI Data: quarterly KPIs the org's data can actually source — revenue by quarter always; SaaS metrics (ARR, Net New ARR, Churn, LTV) only when a KPI source exists (see the KPI-honesty rule under Sheets to Generate) Validation: Cross-checks between P&L and KPI tables Excel Context — Routing Preamble Before any data pull, establish whether this skill is running in a live Excel context (Claude for Excel with the Datarails Add-In loaded) and route accordingly. Detect — never infer from the user's wording. A sheet list containing dragent means the add-in is loaded.
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