Generated from Stella Chatbot's audit data
Stella Chatbot scores 45/100 across 6 category checks, which indicates listing-quality gaps across 3 of 6 audited categories. Strengths: title optimization (63/100) is the strongest category — installing for evaluation is fine, long-term confidence needs the gaps below addressed. Watch-items: languages (0/100) and description & content (40/100) drag the average down; lifting languages is the single largest available lever. Per-category breakdown below.
This is an independent listing audit for Stella Chatbot on WordPress. It scored 45/100 (grade D) on today's snapshot. Top strength: Categories & Discoverability at 63/100. Biggest gap: Languages at 0/100. We re-audit every 24 hours from the canonical WordPress listing.
Six weighted areas, pass / warning / fail per check, tiers at 85 / 65. Full methodology · Glossary
Last updated: August 31, 2026
Stella Chatbot's overall score of 45/100 is a result that signals significant listing weaknesses across multiple categories, computed as the weighted average of 6 category checks. The spread is highly polarized across categories — 3 categories score above the headline number and 3 score below. The strongest category is Title Optimization (63/100, +18 vs overall); the weakest is Languages (0/100), a 45-point gap below the headline score — the largest single lever. Top three by score: Title Optimization (63), Categories & Discoverability (63), Visual Assets (50).
Scoring criteria, category weightings, and the full rubric (identical across every WordPress Plugin Directory listing AppRanks audits) are documented on the methodology page and the audit-score glossary entry. Disputes or data corrections: [email protected].
Stella Chatbot scored 45/100 in the AppRanks listing audit — a result that signals significant listing weaknesses. The score is the weighted average of 6 category checks: Title Optimization 63/100, Description & Content 40/100, Visual Assets 50/100, Categories & Discoverability 63/100, Technical & Support 42/100, Languages 0/100. Each category is scored against a fixed rubric that is identical for every app on the platform, so scores are directly comparable across Wordpress listings.
Stella Chatbot's strongest audit area is Title Optimization, scored at 63/100. Of the 4 checks AppRanks runs in this category, 1 pass cleanly, with the remainder in warning rather than failing state. This is the dimension a competing listing would need to match before Stella Chatbot loses its current edge in this category.
The weakest area in Stella Chatbot's audit is Languages, scored at 0/100. The failing checks are language count, each with a concrete fix described below. Tightening this category is the highest-impact change available to the listing — its weight in the overall score makes it the lever most likely to move the headline number on the next refresh.