Publisher QC Scorecard
Audit publishers before you buy a backlink
What it does
Evaluate publishers before buying guest posts or link insertions. Run 5 hard risk gates, score 7 quality dimensions, verify live placements, and export the complete audit trail to CSV — free, private, and processed in your browser.
Audit backlink publishers with 5 hard gates, 7 weighted quality dimensions and 7 post-publication checks. Export the evidence to CSV—free, no signup, processed in your browser.
Review guest-post and link-insertion opportunities with hard risk gates, weighted quality scoring and post-publication acceptance checks—not DR or DA alone. Built for SEO teams, consultants and agencies that need an inspectable decision—not a black-box quality claim. Reject obvious risks before a headline metric or low price can distort the decision. Compare qualified candidates across seven evidence-based quality dimensions. Check the live URL, context, anchor, attributes and technical status after publication. Fill in the review details, evaluate all five hard gates, then score the seven quality dimensions. There is no submit button: the score and decision update instantly as you make…from wailianjianshe.com
Does the same job
all alternatives →More growth this month
the category →
AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com