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x-post-classifier

aslamdoctor/x-post-classifier

Chrome extension classifying x.com posts via Jev Choice decisions.

Classification & Routing0.99Runner-up: Data Labeling & Curation
Automated README summary

Automatically summarized from the README on 26 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A Manifest V3 Chrome extension for x.com users that labels each post in the feed with a category badge and can dim selected categories, using TypeSafe's Jev model for classification.

How it uses Jev

When a post dwells in the viewport for at least 350ms, the extension sends a Jev Choice question to classify the post into one of six intents (Insight, News, Bait, Promo, Meme, Opinion). The returned category drives a header badge and optional dimming.

Primitives:choice

Technique worth stealing

Gate classification on viewport dwell time (350ms) plus two-tier caching to avoid redundant API calls during scrolling and DOM recycling.

Try it

Copy .env.example to .env with TYPESAFE_API_KEY, run bun install and bun run build, then load unpacked in chrome://extensions.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectFound in material0.95
  • Shows a System One patternnot found in the excerpt0.37
  • Describes handling uncertaintynot found in the excerpt0.04
  • Reports measured numbersnot found in the excerpt0.12
  • Is a runnable toolFound in material0.98
  • Top-10 learning shortlist signalnot found in the excerpt0.20
  • Is a replica of the modelnot found in the excerpt0.04
  • Solves a common problem (0–2)score on a 0–2 scale0.80 / 2
  • About JevFound in material0.97
Signals
Jev is core to the project0.95Shows a System One pattern0.37Describes handling uncertainty0.04Reports measured numbers0.12Is a runnable tool0.98Top-10 learning shortlist signal0.20Is a replica of the model0.0400.51Solves a common problem (0–2)0.80 / 2012

no-judgment band (0.40–0.60)

Design patterns
Funnel0.5800.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 26 Oct 2026.