# Maks-s/sd-akashic

A compendium of informations regarding Stable Diffusion (SD)

Repository: https://github.com/Maks-s/sd-akashic
Canonical: https://ross.abutalabs.com/products/sd-akashic
License: Unlicense
License Family: permissive
Topics: diffusion, guide, stable-diffusion
Last push: 2023-03-08T10:18:52+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1485, "days_push": 1274, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1634, forks 78 (observed 2026-08-28T04:05:14.316963+00:00)

## What it is
A curated compendium of information about Stable Diffusion, including studies, art style and artist lists, keyword lists, and prompt resources. It serves as a reference guide for exploring AI image generation with Stable Diffusion.

## Use cases
- learn how to write better stable diffusion prompts
- find art styles and artist keywords for AI image generation
- understand how stable diffusion tokens and seeds work
- find guides and tutorials for stable diffusion beginners
- discover tools and resources for stable diffusion

## When to choose
- you want a curated reference of SD prompting knowledge, art styles, and keywords
- you are learning Stable Diffusion and want links to vetted guides and studies

## When to avoid
- you need runnable software or code for generating images
- you need up-to-date information on newer SD versions, as the repo was last updated in 2023

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, prompt-engineering, stable-diffusion
- domain: artificial-intelligence, image-processing, tutorials, awesome-lists
- platform: cross-platform
- tags: stable-diffusion, prompting, art-styles, compendium, ai-art, guide

## Member repositories
- Maks-s/sd-akashic (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:14.316963+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:47:02.943247+00:00, confidence not recorded.
  - readme: https://github.com/Maks-s/sd-akashic (fetched 2026-08-28T04:05:14.316963+00:00, sha 5104bbdb4726)
- Data as of 2026-08-30T08:39:29.467469+00:00.