Tableau Workbook Auditor

Find what is wrong with any Tableau workbook (.twbx), and map every dependency inside it, entirely in your browser. Unused fields, duplicate calculations, performance problems, full calculated-field lineage, filters, dashboards and stored SQL. Nothing is uploaded, stored, or sent anywhere.

🔗 Live: https://tableau-lineage.com 📦 MCP server: tableau-lineage-mcp

Why

Inheriting someone else's Tableau workbook means reverse-engineering dozens of calculated fields by hand to answer one question: where does this number come from, and what breaks if I change it?

Two more questions come up just as often and have no free answer:

• What in here is dead? Tableau has no built-in way to list unused fields; the request has been open on the community forum since 2015.
• Why is it slow? Tableau's Workbook Optimizer needs a Creator licence, and Catalog needs Data Management on Server or Cloud.

This reads the workbook file itself and answers all three, free, with no licence and no account. Because workbooks often carry sensitive data, everything runs locally: the .twbx never leaves your machine, which is a property of the architecture rather than a promise (there is no server to send it to).

Features

Audit

• Dead weight: every field, parameter and calculation nothing uses, graded by confidence (unused, likely-unused, referenced-in-comment) with the reason spelled out. Reported as candidates rather than certainties, because a workbook file cannot prove a field is unreferenced everywhere.
• Duplicate calculations: identical formulas under different names, and the more dangerous case of the same name carrying different formulas.
• Performance lint: 15 static rules over what the file actually contains. Heavy and nested LODs, long calculations, string-heavy work, too many quick filters, missing context filters, live connections, non-fixed dashboard sizing, dense dashboards, orphan worksheets.

Lineage

• Interactive dependency graph (vis-network): calculated fields, raw fields, parameters and worksheets as nodes; edges show what feeds what. Cluster by data source, search, highlight chains, zoom and pan.
• Searchable data dictionary: every formula grouped by data source, plus a worksheets section.
• Seven clickable metrics: data sources, calculated fields, raw fields, parameters, LOD calcs, table calcs, filters.

Structure

• Filters, decoded: every filter deduplicated across worksheets, with its kind (categorical / quantitative / relative-date), context-filter status, stored member selections and ranges, and a per-worksheet breakdown. Data-source filters are called out separately.
• Dashboards: which worksheets each dashboard places, its fixed size and device layouts, plus sheets that sit on no dashboard and sheets that are hidden.
• Data provenance: extract or live, connection class / database / server, published (sqlproxy) sources, and refresh history where the workbook records it.
• Stored SQL: every Custom SQL query (full text), Initial SQL statement, stored-procedure reference with parameters, and RAWSQL_* calculation, each mapped to the connection it targets. Runtime-generated live-connection queries are not stored in workbook files, so they are explicitly out of scope.

Compare versions

Drop in up to five versions of the same dashboard and get a semantic diff: which calculations were added, removed, renamed or edited, and for every edit the downstream fields it can break, plus changed parameters, filters, worksheets, dashboards, data sources and SQL. Reformatting a calculation is not reported as a change, and a field that disappears while an identical formula appears under a new name is reported as a rename.

A git diff of two .twbx files cannot do this: the workbook is one large XML blob where layout coordinates and regenerated ids swamp the handful of real changes.

Exports

All generated in-browser, from the same parsed model:

• Interactive HTML report: self-contained and offline-ready (vis-network inlined), watermarked with the tool and the author.
• Markdown handover document: the workbook written up (metrics, audit, dashboards, data sources, parameters, filters, every formula, stored SQL) for a ticket, a wiki or a README. Also the format an LLM reads best when someone asks about the workbook later.
• CSV field inventory (including which worksheets use each field) and JSON of the complete model, audit included.

Everything else

• Private by architecture: .twbx parsing (unzip + XML) happens client-side. No backend, no upload, no cookies. Analytics is an anonymous, aggregate page-view count.
• Workbooks up to 500 MB: only the workbook XML is decompressed; the packaged data extract is never touched.
• Accessible: keyboard navigation, focus management, AA contrast, reduced-motion support, and a text dictionary as an equivalent to the canvas graph.
• Seven UI languages for the core interface strings (buttons, labels, status messages), with English fallback. Longer explanatory copy is English only.

How it works

.twbx (a ZIP)
  └─ fflate unzips ONLY the .twb entry  ──►  DOMParser reads the XML once
        ├─ extractor.ts        lineage model: calcs, dependencies, params, stats
        ├─ filterExtractor.ts  filters + per-worksheet usage
        ├─ sqlExtractor.ts     Custom SQL, Initial SQL, stored procs, RAWSQL
        ├─ dashboardExtractor  dashboards, hidden/orphan sheets, provenance
        ├─ audit.ts            dead weight, duplicates, performance lint
        └─ diff.ts             semantic diff between two parsed workbooks
              ├─ in-app: a sandboxed <iframe srcdoc> report
              └─ exports: HTML / Markdown / CSV / JSON, all from the same model

The packaged data extract inside a .twbx is never decompressed, which is why a 500 MB workbook is fine and why the tool cannot see your rows even in principle.

Correctness notes

The analytical core is a TypeScript port of the original Python service, with fixes that each exist because the naive version was wrong on a real workbook:

1. Parameter references by caption. Formulas reference parameters by caption ([Parameters].[Survival Target (Months)]) while the internal name differs ([Survival Benchmark]). The original leaked a phantom Parameters dependency.
2. Table-calc detection by token, not substring. TOTAL inside [total_views] was flagging ordinary fields as table calcs. Now matched as whole function calls; LOD detection is brace-anchored.
3. Comments and string literals are stripped before dependency scanning. A field name mentioned in a // comment is not a dependency, and treating it as one made unused fields look used.
4. Nodes are keyed by data source, not name alone. Two data sources can both define [Sales]; merging them fused unrelated lineage into one node.
5. Captions resolve document-wide. Workbooks built on published data sources keep captions only in the worksheet dependency stubs, so filters and worksheet fields surfaced raw keys like Calculation_5431234567890123.
6. A <datasources> block is only real at the workbook root. Every worksheet carries a reference list of the same shape, which counted one data source thirteen times on a twelve-sheet workbook.

All are covered by tests (npm test, npm run test:core).

Tech stack

Vite · React 19 · TypeScript · Tailwind CSS · fflate (unzip) · native DOMParser (XML) · vis-network (graph). No backend.

MCP server (for AI assistants)

The same engine ships as an MCP server, so Claude, Cursor and other MCP clients can read and audit workbooks straight from your disk. Still 100% local, nothing uploaded.

Claude Desktop: download the extension and double-click it. One click, no terminal and no Node setup.

Claude Code (installs the MCP plus a skill that knows when to use it):

/plugin marketplace add andey0Saikiran/tableau-lineage
/plugin install tableau-lineage@tableau-lineage

Cursor and other MCP clients:

claude mcp add tableau-lineage -- npx -y tableau-lineage-mcp

Eleven tools: analyze_workbook, audit_workbook, diff_workbooks, list_calculated_fields, get_field, trace_dependencies, list_parameters, get_lineage_graph, list_sql_queries, list_filters, list_worksheets. Full docs in mcp/.

Things worth asking it:

• "Audit this workbook and tell me what is safe to delete."
• "What changed between these two versions, and what does it break?"
• "Which sheets filter on Region, and what values are selected?"
• "Write a data dictionary for this workbook."

Run locally

npm install
npm run dev          # http://localhost:5173

Other scripts:

npm run build        # typecheck + production build + pre-render to dist/
npm run preview      # serve the production build
npm run typecheck    # tsc --noEmit
npm test             # Vitest: extractors, audit, diff, exports
npm run test:core    # extractor parity + regression tests (Node)
npm run prerender    # re-run the static pre-render over an existing dist/

The build pre-renders the landing page with react-dom/server and injects the markup into dist/index.html, so crawlers get real content instead of an empty <div id="root">. It stays a fully static site: there is no server at build time or run time.

Deploy (Cloudflare Workers static assets)