dr-reconcile
Reconcile P&L vs KPI data sources. Validates consistency and identifies discrepancies with variance analysis.
npx skills add majiayu000/claude-skill-registry --skill reconciliation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# P&L vs KPI Reconciliation Validate consistency between P&L and KPI data sources. Identifies discrepancies and explains variances. Essential for month-end close and financial validation. ## Arguments | Argument | Description | Default | |----------|-------------|---------| | `--year <YYYY>` | **REQUIRED** Calendar year to reconcile | — | | `--scenario <name>` | Scenario to reconcile | `Actuals` | | `--tolerance-pct <#>` | Acceptable variance threshold | `5.0` | | `--output <file>` | Output file path | `tmp/Reconciliation_YYYY_TIMESTAMP.xlsx` | ## What It Validates ### Revenue Consistency - P&L Revenue vs KPI Revenue - Within tolerance threshold - Identifies timing differences ### Expense Completeness - COGS + Operating Expense coverage - Validation of expense structure - Missing expense categories ### Data Completeness - All expected accounts present - All expected KPI metrics available - Data quality validation ### Variance Analysis - Absolute variance amounts - Percentage variance - Tolerance compliance - Root cause identification ## Datarails Brand Styling When generating Excel or PowerPoint files, apply Datarails brand styling: **Font:** Poppins (fall back to Calibri if unavai
- Arguments
- What It Validates
- Revenue Consistency
- Expense Completeness
- Data Completeness
- Variance Analysis
- Datarails Brand Styling
- Output
- Examples
- Reconcile current year (default 5% tolerance)
- Strict reconciliation (1% tolerance)
- Reconcile specific scenario
- Custom output location
- Use Cases
What does the dr-reconcile skill do?
Reconcile P&L vs KPI data sources. Validates consistency and identifies discrepancies with variance analysis.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill reconciliation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.