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Rankly

Website intelligence for SEO agencies: a Windows desktop application for Managers, Team Leads and Agents to manage leads, run real technical SEO and passive security audits, deliver client reports, run audit-grounded email outreach and collaborate — backed by a secure API server.

Windows desktop (PySide6)  ──HTTP(S) / WS──▶  Flask API (one process)  ──▶  SQLite (this computer)
                                              │                              or PostgreSQL (team server)
                                              └─ audit engine, audit queue, reports, import + email workers

The desktop client never connects to the database and contains no server secrets. See docs/architecture.md.

For people using the app

Download Rankly-Portable-3.0.0.zip, unzip it, double-click Rankly.exe and choose On this computer: the app starts its own built-in server (the same exe with --serve), creates its database and keys in %LOCALAPPDATA%\Rankly\data, and asks for the first Manager account. Nothing else to install. Or choose Connect to a team server.

Manuals: User Manual · Technical Reference.

Quick start (local development)

:: 1. API server on the local SQLite database
set SEO_DB=sqlite
.venv\Scripts\python.exe scripts\dev_seed.py     :: once; demo accounts -> server_data\dev_credentials.txt
run.bat                                           :: http://127.0.0.1:5055

:: 2. Desktop client
run_desktop.bat

To try the packaged first-run flow from source, set a throwaway profile first: set SEO_AUDIT_PRO_PROFILE=dev-first-run (separate settings and data folder).

Build the Windows executable and the portable zip (and an installer, if Inno Setup 6 is installed):

build_exe.bat

Production deployment, environment variables and first-Manager setup: docs/deployment.md.

What it does

Area Highlights
Access Sign-in with lockout, forgot/reset password by emailed code, mandatory change of temporary passwords, refresh-token sessions stored in Windows Credential Manager, sign-out everywhere on password change
Roles Manager, Team Lead, Agent — enforced by the API (see docs/security.md)
Lead Bank Built for Google Maps scrapes (one niche + area per file, many files, millions of rows): multi-file CSV/XLSX import read on the person's own computer (only rows go to the server) with live progress; rows without a website and duplicates (by domain or phone, against the bank and within the file) removed and listed per file; niche → area navigator with counts; filters for unassigned / audited / contacted; select all matching across pages; assign to a person or team, or split evenly across a team; assignment history and conflict protection; CSV export; archive
Audits One click from a lead, or bulk: select leads (or all matching) and queue up to 100 per run (500 for Managers); a saved queue; each audit runs on the computer of the person who queued it, 2 at a time by default (Managers can change it), single audits first, survives restarts and closed apps; Queue view with progress, time left and cancel; one notification per finished batch. Real progress from the engine; scored results, issue explorer with resolved/unresolved tracking, passive security findings, recommendations, crawled pages
Reports Client and technical Word reports made on the auditing computer and stored for the whole team; PDF made on first open by the opener's computer (Word or LibreOffice) and stored for everyone; standalone HTML client report; JSON export. Results are stored compressed (~80 KB per audit)
Outreach Email drafts generated only from real audit findings and always editable; attachments; encrypted SMTP (Gmail or company domain); rate-limited queue; bulk outreach with preview and confirmation; delivery activity
Collaboration Direct messages and team channels with presence, typing, replies, edits, deletes, reactions and search; share a lead or an audit report in a message (no outside files in chat); notifications
Administration Teams, users, immutable audit log, audit defaults

The audit engine

Give it a website; it crawls the site and runs ~70 checks across ten weighted categories, plus PageSpeed Insights (lab + real-user CrUX data) and a passive security assessment.

Category Weight Examples
Technical SEO 16% robots.txt, sitemap, canonicals, indexability, redirects, broken links, structured data, hreflang
On-Page SEO 14% titles, meta descriptions, headings, thin content, image alt, internal links
Performance 14% PageSpeed mobile/desktop, Core Web Vitals, render-blocking, compression, caching
Content 10% readability, depth, E-E-A-T signals, NAP
Mobile 10% viewport, responsive signals, tap targets, mobile speed
Security 8% HTTPS/TLS, certificates, HSTS, security headers, cookies, information disclosure, sensitive file exposure, known JS library CVEs, SPF/DMARC/DKIM, authentication surface, WAF, technology fingerprint
Local SEO 8% local business signals
Off-Page / Authority 8% estimated authority model (labelled as an estimate)
Accessibility 8% language, labels, link text, landmarks, Lighthouse a11y
UX 4% layout stability, interactivity, font loading

Each check is pass (1.0) / warning (0.3) / fail (0.0); info and not-applicable checks are excluded, categories without data are dropped and weights renormalised, and honest penalties are applied. The security assessment is passive: exposed sensitive files are reported only as "Publicly accessible", never downloaded or quoted. Scoring and rules are documented in docs/AUDIT_SCORING.TXT and docs/SCORING_RULES.TXT.

Documentation

Document Contents
docs/architecture.md Components, request flow, structure
docs/desktop.md Startup, sign-in flows, navigation, local data, design system
docs/api.md REST and WebSocket reference
docs/database.md Schema, constraints, migrations
docs/security.md Authentication, RBAC matrix, data protection
docs/deployment.md Server and client deployment
docs/testing.md Automated and manual tests
docs/IMPLEMENTATION_RECORD.md What was found, changed, fixed, and what remains
docs/*.TXT Engine methodology notes (scoring, security headers, indexation, …)

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