llms-full.txt@website/public · diff

git:20260826.390414f to git:20260827.c6a54e9

8 added, 4 removed. Audit A to A.

# Zero Slop product reference

Canonical website: https://zero-slop.ai/

Source and documentation: https://github.com/manavmishra/ZeroSlop

Latest release: https://github.com/manavmishra/ZeroSlop/releases/latest

- Current version: 2.5.9

+ Current version: 2.6.0

## Direct answer

Zero Slop is a free, open-source AI writing humanizer and anti-slop checker. It identifies familiar AI writing patterns, rewrites the draft, and checks figures, names, quotes, links, code, tables, paths, and document structure against the original. Its local checker runs with Python's standard library and does not send the draft to a server.

Zero Slop is not an authorship detector. It evaluates the writing rather than claiming who or what wrote it.

## Install

`npx skills add manavmishra/ZeroSlop --global`

## Workflow

- Zero Slop has seven editorial roles and two operational loops.

+ Zero Slop has eight editorial roles and two operational loops.

- 1. Editorial delivery moves the draft through a scorer, interpreter, rewriter, fact gate, copy desk, read-aloud editor, and verifier. These are separate jobs, not seven models.

+ 1. Editorial delivery moves the draft through a scorer, interpreter, rewriter, fact gate, copy desk, read-aloud editor, verifier, and fresh-eyes finalizer. These are separate jobs, not eight models. Any finalizer edit repeats copy editing, read-aloud review, verification, and fresh-eyes review until the same text is approved unchanged.

2. Learning from your edits compares the assistant's version with the final version you provide. Repeated, safe changes can update private rules and preferred fixes; later edits can confirm them, while stale guidance fades or retires.

Private rules load on the next run and can improve both detection and fixing. Zero Slop does not watch files or publishing systems, retrain the AI model, or perform reinforcement learning or RLHF.

## Supported environments

Zero Slop works with agents that read SKILL.md files, including Codex, Claude Code, Cursor, Gemini CLI, OpenCode, Warp, and Zed. The repository also documents setup for ChatGPT and claude.ai.

## Writing formats

The same workflow can be used for LinkedIn posts, blog articles, strategy documents, X threads, presentations, newsletters, emails, and research abstracts.

## Cost, license, and privacy

- Price: Free

- License: MIT

- Scorer dependencies: None beyond Python's standard library

- Network required by the scorer: No

- Account required by the scorer: No

## Current validation

- Version 2.5.9 matched v2.5.8 on 114 frozen document scores and the 38-item editorial panel, kept all 18 known-human controls clean, added five tested edge-case checks and four classes of structured-document protection, and measured 0.41 percent higher median throughput in a 12-run interleaved comparison. In a fresh same-model replay on 18 drafts, Zero Slop passed 18 of 18 of its checks, avoid-ai-writing 15, no-ai-slop 12, and humanizer 9. Those checks belong to Zero Slop, so this is a regression comparison rather than independent human field accuracy. The repository includes hashes, aggregate results, source pins, and limitations.

+ Version 2.6.0 adds four narrow checks for reasoning artifacts, unsupported novelty, emotional flatness, and repetitive acknowledgments, plus the separate fresh-eyes finalizer. The local meter changed none of 114 frozen document scores, kept all 18 known-human controls clear, matched 84.21 percent of the 38-item LLM editorial panel, and moved the four new edge cases from 9.5 to 30.7–65.1. Median throughput was 0.94 percent lower in the 12-run local comparison, within the project's five percent regression limit. The fresh-eyes role changes the AI-assisted editing workflow rather than the local score: it reviews the verified copy as a first-time reader, and any correction restarts every final check.

+ In the four-way same-model replay on 18 drafts, Zero Slop passed 18 of 18 of its checks, avoid-ai-writing 15, no-ai-slop 12, and humanizer 9. Those checks belong to Zero Slop, so this is a regression comparison rather than independent human field accuracy.

+ A separate two-pass, method-hidden GPT-5.4 review favored Zero Slop on 13 drafts and avoid-ai-writing on 3; 2 were unresolved. The passes agreed on 16 of 18 winners. Zero Slop's source check passed all 18 of its rewrites and 16 of the incumbent's. This small LLM-reviewed study is not human field accuracy or a universal ranking. The repository includes the packets, mappings, judgments, hashes, source pins, and limitations.