photo-relic-editorial
A Codex skill for transforming real photos into Photo Relic artworks: truthful photographs paired with quiet paper-memory prints.
1How It Works & Mechanism
Zero-code dual-layer pure prompt implementation combining orchestration and knowledge base: SKILL.md serves as the workflow and aesthetic discipline layer (inspect photo → extract cues → select recipe → generate → run QA), while references/afterimage-editorial-prompt.md acts as a prompt compiler that SKILL.md mandates reading first (structural constraints, fidelity bans, subject treatments, signature system, and ready-to-use Prompt Templates).
Read `references/afterimage-editorial-prompt.md` before composing the final image prompt.
Pixel generation is fully delegated to the host's image tool, with the skill itself containing no scripts, API endpoints, or vendor lock-in: SKILL.md only mandates using the image generation/editing tool with the user's photo as the reference image, leaving vendor choice to the host (Codex's image tool).
This is a creative image-generation skill. When producing the final image, use the image generation/editing tool with the user's photo as the reference image.
The core creative constraint is the dichotomy between photo-area truth value and lower relic-area abstraction: any redrawing, beautifying, outpainting, or stylization is strictly forbidden on the real photograph area, confining abstraction to the lower relic area to ensure the final output is a true photo paired with a memory print rather than an all-over filter.
Use abstraction only in the relic region unless the user explicitly asks for an integrated edit.
Aesthetic decisions are parameterized into a 5-axis recipe system (layout rhythm / relic grammar / mark weight / title mode / motion seed) with discrete choices, requiring selection before prompt assembly to guarantee cross-photo series consistency while introducing controlled variations.
Pick one option from each axis before writing the image prompt. Vary the recipe when recent outputs look too similar, but keep the series identity stable.
A translation table mapping details into marks serves as the direct source of rendering quality: roofs → overlapping arcs, windows → sparse cuts/dots, people → short vertical incisions, water → one or two horizontal residue lines, preventing the panel from turning into an illustration or decoration.
Translate details into marks, not decorations: roof layers become stacked arcs; windows become sparse cuts or tiny dots; people become short vertical ticks; water becomes one or two horizontal residues; dusk becomes one small warm signal.
Dual Quality Gates (ten checks in SKILL.md + nine in references) perform checklist-based self-verification before generation; any primary failure permits only a single, shorter, and stricter regeneration, preventing mindless retries or lowering passing standards.
If one major item fails, regenerate once with a shorter, stricter prompt focused on that failure.
Codex ecosystem entry point: agents/openai.yaml provides display_name, short_description, and default_prompt; the README guides copying the entire directory into ~/.codex/skills and triggering it via $photo-relic-editorial, while the Chinese README demonstrates a serialized four-character Chinese title pattern.
default_prompt: "Use $photo-relic-editorial to turn this photo into a Photo Relic artwork with a truthful photo region and a recognizable abstract memory print."
2Core Capabilities
3External Dependencies
| Kind | Dependency / Endpoint |
|---|---|
| api | 宿主图像生成/编辑工具(参考图输入;SKILL.md 未点名厂商,供应商由 Codex 宿主决定) |
4Recommended Governance & Evidence
- SKILL.md: Pure prompt instructions and rule text, without script execution or external impacts
5Second-Pass Verification
- [ok] 外部依赖唯一条目:宿主 image tool + 无厂商端点 — SKILL.md 全文本扫描确认只有 'use the image generation/editing tool' 一类泛称,无 openai/gpt/anthropic/replicate 等点名;示例 PNG 的 C2PA 元数据(gpt-image 2.0)属产物证据而非指令,已在条目 note 中如实标注为『实际出图工具』推断。
- [ok] security.grade=green 的反例搜查(隐藏脚本/网络/凭证) — 隐藏文件仅 .gitignore/.DS_Store 类忽略项;文本文件 URL/token/exec 模式零命中;无 package.json/requirements/*.sh;唯一网络痕迹出现在 examples/*.png 的 C2PA 证书链(cv.iptc.org、ocsp-c2pa.ssl.com、trufo.ai),属图片内嵌内容凭证,非可执行代码。
- [ok] 『照片区不可篡改』声明 vs 实际能力 — 该声明是写给宿主图像模型的文本禁令(SKILL.md Creative Rules + references Photo Preservation 双重强调),skill 无代码可强制执行;第一遍已将其表述为『prompt 层约束 + Quality Gate 兜底』,未夸大为硬保证。
- [discrepancy] README 'Paper Beijing' 示例图身份 — 第一遍初读时按 README 语境默认示例是真实照片经 skill 处理的成图——成立;但第二遍在 PNG 内发现 C2PA 软件代理串 'nameigpt-imagegversionc2.0' 与 'c2pa.watermarked.unbound',确认示例成图由 OpenAI gpt-image 2.0 生成并含水印/内容凭证动作。此发现不推翻结论,但 internal_assets 与 verdict 对示例图的描述已按此修正(AI 生成示例,作为审美锚点)。
- [ok] references 文档『Prompt Compiler / Quality Gate』引用准确性 — 逐字重读 156 行全文,第一遍所用 quote(recipe 槽位模板、'If a major gate fails, regenerate once with a shorter corrective prompt…'、'Use abstraction only in the relic region…'、Signature System 色板/比例)均与原文一致。
- [ok] 元数据:commit/license/stars/last_push — GitHub API:spdx mit、stargazers_count 378、pushed_at 2026-08-05T02:37:31Z(= pin commit 时间,仓库 3 个 commit 无更新);本地镜像 HEAD == pin sha 2232da16afddc7940e2e2f280bfb85aa62da1bae。
6Verdict & Scenarios
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