DESIGNOSFORGE is an open-source Codex agent/skill system for turning AI design from prompt guessing into a governed design workflow.
It focuses on the problems that make AI visuals feel unusable: fragmented compositions, dirty textures, weak prompts, garbled text, broken layout order, and unreviewable delivery.
At its core are PromptPacket v1.6, aesthetic quality gates, training-aware case memory, project-context routing, corpus audit tools, anti-fragmentation controls, text/encoding health checks, layout-order rules, and GitHub-ready release workflows.
DESIGNOSFORGE is released under the MIT License as an open-source Codex agent/skill system.
Use it to study, adapt, and extend:
- Codex skill packaging
- design-agent orchestration
- visual prompt governance
- aesthetic quality gates
- LoRA aesthetic corpus planning
- training-aware aesthetic memory indexing
- project-context routing for commercial, academic competition, and public cultural work
- GitHub-ready release workflows
See docs/CODEX_INSTALL.md for local Codex skill installation.
Most AI design workflows fail after generation starts. DESIGNOSFORGE moves quality control before generation:
- one dominant focal anchor instead of scattered fragments
- grid, density, and negative-space rules instead of visual noise
- exact visible text instead of pseudo-text and mojibake
- structured PromptPacket output instead of loose prompt paragraphs
- project-context locks instead of mixing commercial and academic competition logic
- memory-case recommendations instead of relying on vague style recall
- reviewable GitHub workflows instead of one-off local experiments
For launch copy, social posts, and community announcements, see docs/PROMOTION_COPY.md.
PYTHONPATH=. python -m app.cli capabilities
PYTHONPATH=. python -m app.cli run "做一个品牌 VI 方案" --prompt-packet
PYTHONPATH=. python -m app.cli gitops sync-registry
PYTHONPATH=. python -m app.cli github status
PYTHONPATH=. python -m app.cli github release-plan --version v1.6.0
PYTHONPATH=. python -m app.cli quality audit "高级 大气 细碎 脏乱 生成一张海报"
PYTHONPATH=. python -m app.cli lora init-aesthetic-space
PYTHONPATH=. python -m app.cli lora audit-corpus
PYTHONPATH=. python -m app.cli lora build-memory-index
PYTHONPATH=. python -m app.cli lora recommend --domain exhibition-board --context academic-discipline-competition
PYTHONPATH=. pytest -qThis source package includes a GitHub Actions workflow, PR body, release notes, and a source skill validator.
After binding a target remote, push release/1.6.0 and tag v1.6.0, then open a draft PR using docs/PR_BODY_v1.6.0.md.
Use codex_skill/designos-forge/SKILL.md as the Codex skill entry. The included Codex entry has been upgraded to designos-forge v1.6.0 with aesthetic quality gates, training-aware case memory, project-context routing, prompt precision, text/encoding health, environment-aware routing, and Git/GitHub release planning.