XrmToolSuite.TechnicalDebtAnalyzer 1.2026.7.12

🧹 Technical Debt Analyzer

An XrmToolBox plugin that scans a connected Dataverse environment with eight UI-free analyzers, scores the accumulated technical debt on a 0–100 scale with a Low/Medium/High band, and lists prioritized cleanup findings in a severity-coloured grid. Read-only — it queries metadata, plugin registration, web resources, processes and roles, and never modifies anything.

Features

The eight analyzers cover the main debt sources; each degrades a failed query or permission gap to an informational finding rather than aborting the scan.

• Debt score: severities are weighted (Critical=25 / High=12 / Medium=5 / Low=2 / Info=0), summed and capped at 100, and banded at 15 (Medium) / 40 (High). Debt accumulates — a single Critical does not force the High band.
• Dashboard: a score + band header, a headline metric strip (total findings plus a per-category breakdown), and a detail pane per finding (component, description, recommendation, docs link).
• Trends tab: charts the debt score run-over-run per environment from local per-machine JSON snapshots (a dependency-free GDI line chart, a "since last run" delta banner, and a confirmation-gated Clear history action). Trend history is local only — the tool never writes to the org.

Exports

• Excel workbook
• PDF report (native, MigraDoc/PdfSharp-GDI)
• HTML dashboard
• JSON
• Markdown cleanup checklist
• An executive summary — offline-templated by default, with an auditable, opt-in AI path
• The Trends tab additionally exports the snapshot series to CSV/JSON

Help & Support

A right-aligned Help button on the toolbar opens a Help & Support dialog (Documentation, Report an issue, and a support link, each opened in the browser). The tool implements IHelpPlugin and IGitHubPlugin pointing at repository kkora/XrmToolSuite, so XrmToolBox's own tool-menu links resolve to the same project.

Build & install

This tool is not single-DLL — it ships the Excel/PDF export dependency chain (ClosedXML + PdfSharp/MigraDoc-GDI) into the Plugins root next to the tool DLL. The one-step build copies the whole chain automatically:

dotnet build src\Tools\XrmToolSuite.TechnicalDebtAnalyzer\XrmToolSuite.TechnicalDebtAnalyzer.csproj -c Release -p:DeployToXTB=true

Restart XrmToolBox and open Technical Debt Analyzer. For a manual copy to another machine, copy every DLL from the tool's bin\Release\net48\ folder — flat in the Plugins root, never a subfolder, or XrmToolBox silently drops the tool. See ./DEPLOYMENT.md and the suite guide Deployment_Guide_XrmToolBox.md.

Usage

1. Connect to your Dataverse environment.
2. Open Technical Debt Analyzer; tick which analyzers to run (the unchecked set persists).
3. Run the scan — analysis runs on a background worker with progress and cancellation.
4. Review the severity-coloured findings grid and the dashboard; click a finding for its detail pane.
5. Export to Excel / PDF / HTML / JSON / Markdown, and open the Trends tab to see the score over time.

Notes & limitations

• Read-only — never modifies the environment. Trend history is stored as local per-machine JSON under the XrmToolBox Settings folder (capped to the most recent 100 runs per environment); Clear history is confirmation-gated.
• Per-entity row probing is capped (400 by default); the cap is reported as an Info finding when hit.
• The optional AI executive summary is opt-in behind a session-only API key that is never persisted, and a payload-preview consent dialog shows the anonymized JSON before anything is sent. Component names in the payload are toggleable.
• Local models (Ollama): run the summary against a local model — no API key, nothing leaves the machine.
  1. Install: winget install Ollama.Ollama (or ollama.com/download). Ollama serves http://localhost:11434 automatically; start it manually with ollama serve if needed.
  2. Pull a model: ollama pull qwen2.5:7b (also gemma3:4b, llama3.2:3b, qwen2.5-coder:7b). ollama list shows installed models, ollama ps shows loaded ones, ollama run <model> "hi" warms one up.
  3. AI settings ▸ Provider = Ollama (local), Model = qwen2.5:7b, leave API key blank. The first request loads the model (waits up to 5 min); if Ollama isn't running it falls back to the offline summary. nomic-embed-text is an embedding model — use a chat model (qwen2.5/gemma3/llama3.2).
• System Customizer or higher is recommended for full results.