Dr Dashboard

Executive KPI Dashboard

Generate executive KPI monitoring dashboards for the latest closed month.

Creates both Excel dashboards (for analysis) and PowerPoint one-pagers (for meetings).

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 __dr_agent means the add-in is loaded. Confirm with the agent.get_session probe, which you run by executing Office.js through the execute_office_js tool (see the Excel Context Contract in CLAUDE.md, §Transport) — it is not an MCP tool and has no MCP equivalent. A failed probe is a normal detection result, not an error: it means "no bridge here", which is the expected outcome in Claude Code. Do not surface it, do not retry it, and do not apply this skill's connection-error or Connectors-UI guidance to it — that guidance is about datarails-finance-os connector calls only. A successful probe means Excel context, on either transport. The bridge serves two add-in tracks and their session payloads differ: Flex (Office.js task pane) exposes isLoggedIn; the COM desktop add-in — the majority of live workbooks — exposes isConnected instead, and isConnected: false is not a login failure, an error, or a reason to stop or send the user anywhere. It merely means the workbook isn't connected to a Datarails file, which matters only to drilldown_* / create_dynamic_range (the bridge skill gates those itself). Only Flex's explicit isLoggedIn: false means sign-in is needed.

Route by the target of the request, not by whether a workbook is open.

• Org / server data — which tables, models and fields exist, aggregations, raw rows, distinct values, metrics, profiling — always the datarails-finance-os MCP connector, even in Excel. The bridge cannot answer these.
• Workbook actions — refresh, drill a cell, insert a DR function, read what a cell returns, publish, submit — always the add-in bridge. Never a native Excel recalc (calculate(), F9): it does not pull Datarails data and silently yields stale values.

In a live Excel context this skill cannot produce its file deliverable. Its generation steps depend on the Bash tool, which that surface does not provide. Say so plainly and offer the real alternatives — a scoped answer in chat, or re-running this skill from Claude Code where file output works. Never improvise another route to a file, never hand back a partial artifact, and never silently substitute a different deliverable: writing into someone's live workbook instead of giving them the file they asked for is a different and irreversible outcome, not a smaller version of the same one.

If you do write DR formulas into the workbook, writing and refreshing are one atomic step. Write to a new sheet, fire refresh_selected_cells_ribbon scoped to that range — a new-sheet block is one contiguous range, so one scoped call covers any cell count — then read the range back. refresh_ribbon is not the tool for this: it repulls every DR cell in the file and can silently move numbers elsewhere in the user's model. It is reserved for the one case the scoped command can't cover — scattered inserts across multiple sheets, per excel-context__internal's refresh-after-insert rule — and even then only with the user's explicit OK, after snapshotting the DR ranges you can bound, reporting each changed cell in them before → after with the compared ranges named, and saying plainly that cells beyond them may also have updated. If the user declines the whole-workbook refresh, fall back to scoped refresh_selected_cells_ribbon calls sheet-by-sheet — slower, but nothing outside the written cells moves. A freshly written DR formula reads Missing / Loading… / #BUSY! until an agent refresh lands, so never quote a value you have not read back after a successful refresh, and never present a figure fetched from the MCP connector as though it were the cell's value. /dr-get-formula is the full authority for DR.GET workbooks.

If the user asks you to elaborate on a DR-backed figure — "explain", "break down", "what's driving this", "why is X" — and the figures in scope are DR formula cells, offer the add-in's drill-down instead of silently re-deriving the number through the MCP connector. A drill resolves the exact filters behind that cell; a hand-rebuilt query only approximates them.

Arguments

Data Discovery

Before fetching any numbers, discover what the org actually has: list_data_models for the financials table, then get_fields_by_id / list_aliased_fields for its fields. Never assume field names, scenario values, or metric availability — they differ per org.

Async fetch — aggregations and distinct values run as start → poll. start_aggregation_by_id/_by_alias and start_distinct_values_by_id/_by_alias take the same arguments as the retired blocking calls (dimensions/metrics/filters; table id + field id, or alias + field alias) and return immediately with {"status": "pending", "handle": {...}}. Echo that handle back verbatim to the matching get_aggregation_result_by_* / get_distinct_values_result_by_* tool: a {"status": "running", "retry_after_seconds": N} response means poll again with the same handle after ~N seconds (≈5s) — it is not an error, and large jobs may take several polls; when ready, the result arrives in the familiar shape (for distinct values, pass limit to the result tool). An expired/unknown-handle error means restart with the start_* tool. Transitional fallback: if the start_* tools aren't available on the connector (older server), the blocking twins get_aggregated_data_by_* / get_distinct_values_by_* still work with the same arguments.

Data-scope discovery — run before any aggregate (reuse anything already discovered this conversation).

1. Scenario domain. Pull distinct values of the scenario field (start_distinct_values_by_alias/_by_id → poll the matching result tool) — never assume a scenario name exists (Budget frequently doesn't; many orgs carry only {Actuals, Forecast}). For budget/plan questions, if no budget-like scenario exists, look for a planning-version-like field (alias/name matching /plan|version|cycle|budget/i) and use its versions as the plan side; if neither exists, say so and offer a comparison across the scenarios that do exist.
2. Account grain. Pull distinct values of each account-hierarchy level field (L0/L1/L2-like). Use the level whose values partition P&L flows into revenue/COGS/opex-like buckets — on many orgs the top level is the balance-sheet equation (ASSET/LIABILITY/EQUITY/INCOME) and P&L line items live one level deeper. For P&L work, scope to P&L flows and exclude balance-sheet buckets; never present asset/liability/equity totals as revenue or expenses.
3. Period scope. Discover the date field's range (distinct values of the reporting-month field, or MIN and MAX in two separate calls — one aggregation per field per call). Default every P&L question to the latest complete fiscal year (or trailing 12 closed months) — never an unscoped all-time total: financials tables are multi-year cumulative and mix balance-sheet stock with P&L flow. Label every output with the period + scenario it covers.
4. Reading GROUP BY responses. Each response returns exactly one row per requested group — no subtotal rows and no grand-total row mixed into the data list; grand totals arrive in a separate top-level totals field beside the rows ({"data": [...], "totals": {...}}), computed across all groups, not just the returned prefix. For a grand total, read totals — never sum the rows when the response carries truncated: true (summing the returned prefix silently under-counts; dev repro: 474 of 31,455 rows summed to 21% of the true total). totals combines the per-group results rather than re-scanning the rows, so it is exact exactly when the aggregation is decomposable: SUM (sum of the group sums), COUNT (sum of the group counts), MIN, and MAX. It is WRONG for AVG (unweighted mean of the group averages) and COUNT_UNIQUE (sum of the per-group distinct counts, so a value recurring across groups is counted once per group) — true average = SUM total ÷ COUNT total (two calls: a field may be aggregated at most once per request); true distinct count = the distinct-values tools. Treat every aggregation type not named exact above — UNIQUE_VALUES included, whose cross-group de-duplication is unverified (the COUNT_UNIQUE behaviour above is evidence the engine may not de-duplicate across groups at all) — as not decomposable: derive it from complete rows or the distinct-values tools, never from totals. totals is absent on dimension-less aggregations (the single returned row IS the total) and may be absent on responses cached before the rollout (cache TTL ≤ 7 days) — only in those two cases is a total obtained by summing complete (untruncated) rows. Null groups arrive explicitly labeled [null] and are real groups; read null counts from that bucket. Defensive filter: keep only rows in which every requested dimension key is present — a roll-up row omits one or more keys entirely, whereas a genuine null is present with the value [null]. On a correct response this is a no-op; it guards against a stale cached response still carrying legacy subtotal and grand-total rows, each of which equals the whole total and would inflate any sum. When COUNT-ing rows per group, aggregate a different field than the GROUP BY dimension itself — a same-field COUNT of the grouped dimension can 500.
5. Truncated results. Any data tool may return {"data": [...], "truncated": true, "total_rows": N, "returned_rows": M, "guidance": "..."} when the result exceeds the response size limit (~50 KB). The data prefix is incomplete — never compute totals, shares, or trends from it, and never present it as the full result. On aggregations the top-level totals field is unaffected by truncation (computed across all groups, not just the returned prefix) — read grand totals from it instead of re-fetching. Narrow the query (fewer dimensions, more filters, fewer selected columns — or a business metric for a named KPI) and re-fetch only when the rows themselves are needed beyond the cap; with totals present, a SUM/COUNT/MIN/MAX grand total never requires a re-fetch or chunking by dimension (AVG, COUNT_UNIQUE and UNIQUE_VALUES never read totals — true average = SUM total ÷ COUNT total from two calls; true distinct count = the distinct-values tools). A truncated response without totals (pre-rollout cache) cannot answer a grand-total question from its prefix. Re-run the aggregation once — a fresh run may miss the stale entry and return totals. If the re-run still carries no totals, stop re-running and fall back to narrowing or chunking by dimension until the responses are complete, then sum those rows. Never total the prefix.

Key Metrics Included

Render only KPIs you can source. A KPI may come from (a) the org's metric catalog — list_business_metrics (ungated) for discovery; the get_business_metric_* data tools are feature-gated and may be absent, and USER-kind metrics often return empty — or (b) aggregation over the discovered P&L grain (revenue, expense buckets, gross/operating margin when COGS/OpEx-like buckets exist). SaaS/unit-economics metrics (ARR, MRR, churn, LTV, CAC, burn, runway, NRR) are not derivable from a P&L table — include them only if discovered as populated metrics; otherwise omit the card/slide entirely. Never render a placeholder, estimate, or fabricated value for a KPI you could not source.

The lists below are candidates, not guarantees — each card renders only when sourceable per the rule above:

Growth & Revenue:

• ARR (Annual Recurring Revenue)
• Revenue
• MoM/QoQ growth rates

Health & Efficiency:

• Churn rate (%)
• LTV (Lifetime Value)
• CAC (Customer Acquisition Cost)

Operational:

• Burn rate (monthly)
• Runway (months of cash)
• Burn multiple

Custom Metrics: Any KPI in your data (adapts to profile)

Datarails Brand Styling

When generating Excel or PowerPoint files, apply Datarails brand styling:

Font: Poppins (fall back to Calibri if unavailable). Weights: 400 regular, 600 semibold, 700 bold.

Colors:

Excel layout:

• Content starts at column B (column A is a narrow gutter)
• Rows 1-6: header banner with navy background, white title text, white subtitle
• Gridlines OFF. Freeze panes at B7.
• Footer as last row with generation date
• Every cell must have font, fill, alignment, and number format set

Number formats: _(* #,##0_);_(* (#,##0);_(* "-"_);_(@_) (default), $#,##0 (dollars), $#,##0.0,,"M" (millions), 0.0% (percent)

Variance coloring: Any cell showing a delta/change: green (2ECC71) if favorable, red (E74C3C) if unfavorable. Apply automatically based on value sign and metric context.

PowerPoint: Navy (0C142B) background, 16:9 widescreen, Poppins font, white text, amber (FFA30F) accent lines, card backgrounds 001F37.

DR.GET Formulas — Authoring Contract

If asked to add live / refreshable Datarails formulas (DR.GET) to a generated workbook, the only valid form is:

=DR.GET(Value, "[DimensionName]", CellRef, "[DimensionName]", CellRef, ...)

• Never transliterate an MCP/API call into a formula. DR.GET takes no table, field, or aggregation arguments — =DR.GET(Value,"financials","Amount","SUM",...) is invented syntax that the Datarails Add-in cannot parse or refresh.
• Dimension names go in square brackets inside quotes ("[Scenario]"). Dimension values are always cell references, never hardcoded strings.
• Date cells referenced by formulas hold end-of-month date serials computed from the calendar — never raw epoch timestamps from API responses (epochs land a day early with a time component and never match).
• Before writing any formula, create the workbook-scoped defined name Value referring to the string constant "Value" (wb.defined_names.add(DefinedName("Value", attr_text='"Value"'))) — otherwise Excel autocorrects the bare token to its built-in VALUE() and the formula breaks.
• Bare =DR.GET(...) only — never wrapped in IFERROR/IF/ROUND.
• Every rule here applies to the retrieval/period family — DR.GET, DR.QTD, DR.YTD, DR.MTD share one form (=DR.QTD(Value, "[Dim]", CellRef, ...)), one cell-reference discipline, one Value defined-name requirement, one no-wrapping rule. "DR.GET" in this contract means that family. Helper functions with their own documented signatures (e.g. DR.INCLUDE, DR.RANGE) are not covered here — author those only from their own documentation, never by analogy with this form.
• In a live Excel context, writing DR formulas and refreshing them is one atomic step — a freshly written DR cell reads Missing until an agent refresh lands, and only read-back values may be quoted. The Excel-context routing preamble (or the skill's own Step 0 workflow) owns that procedure; this contract owns the formula text.

The get-formula skill (/dr-get-formula) is the full reference — parameter cells, validated dimension values, report layouts. Prefer it for whole formula workbooks; apply this contract when adding any retrieval/period DR formula (DR.GET/DR.QTD/DR.YTD/DR.MTD) to a workbook here.

Output

Excel Dashboard

• Summary sheet with top KPIs
• All Metrics sheet with complete list
• Current values
• Status indicators (✅ or ⚠️)
• Period + scenario label on every sheet and figure

PowerPoint One-Pager

• Single professional slide
• Top metrics in boxes
• Color-coded for quick scanning
• Period + scenario stated on the slide
• Generated timestamp
• Perfect for executive team syncs

Examples

Generate dashboard for the latest closed month

/dr-dashboard

Output (illustrative — your org's period, metric count, and values will differ):

📊 Generating dashboard for 2026-02...
  📈 Fetching KPI metrics...
  📊 Calculating trends...
  📋 Generating Excel dashboard...
  🎯 Generating PowerPoint one-pager...

✅ Dashboard generated successfully

==================================================
EXECUTIVE DASHBOARD
==================================================
Period: 2026-02
Metrics: 7

Outputs:
  Excel: tmp/Executive_Dashboard_2026-02-03_143022.xlsx
  PowerPoint: tmp/Dashboard_OnePager_2026-02-03_143022.pptx
==================================================

Specific month

/dr-dashboard --period 2025-12

With custom locations

/dr-dashboard \
  --output-xlsx reports/dashboard.xlsx \
  --output-pptx reports/dashboard.pptx

Use Cases

Daily Executive Sync

/dr-dashboard  # Use PowerPoint for standup

Weekly Team Update

# Share Excel for details, PowerPoint for overview
/dr-dashboard

Monthly Board Package

# Generate for month-end
/dr-dashboard --period 2026-01

Investor Demo

# Professional one-pager
/dr-dashboard --output-pptx investors_dashboard.pptx

Performance

• Generation: <2 minutes
• Real-time KPI data
• Scales to 100+ metrics
• Efficient aggregation

Color Coding

• ✅ Green - Positive metrics (high revenue, low churn)
• ⚠️ Yellow - Needs attention (rising burn, declining growth)
• 🔴 Red - Critical (low runway, high churn)

Features

Excel Dashboard:

• Sortable data
• Easy drill-down
• Print-friendly
• Shareable format

PowerPoint One-Pager:

• Executive-ready
• Meeting-ready (1 slide)
• Branded template
• Easy to share

Automated Updates

Schedule weekly updates:

# Every Monday at 8 AM
0 8 * * 1 /dr-dashboard \
  --output-pptx reports/weekly_dashboard.pptx

Integration

Works with:

• /dr-insights - Understand why metrics changed
• /dr-reconcile - Validate KPI accuracy
• /dr-anomalies-report - Check data quality
• /dr-extract - Get latest data

Related Skills

• /dr-insights - Detailed trend analysis
• /dr-reconcile - Validate KPI accuracy
• /dr-anomalies-report - Check data quality
• /dr-forecast-variance - Forecast vs actual