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hatch-pet

根据文字或参考图制作适用于Codex的动态宠物,检查各动作的外观一致性与背景透明度,并输出动画精灵图及配置文件。

原文查看原文说明

Create, repair, validate, preview, and package Codex-compatible animated pet spritesheets from character art, screenshots, generated images, or visual references. Use when a user wants to hatch a Codex pet, create a custom animated pet, or build a built-in pet asset with an 8x9 atlas, transparent unused cells, row-by-row animation prompts, QA contact sheets, preview videos, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.

AI 评分90分/ 100查看安装方法

适用场景

  • 根据文字制作Codex宠物
  • 将角色图片制作成动态宠物
  • 修正动作之间的外观差异
  • 通过帧总览图或视频检查动作

中文介绍

功能

根据文字构想或参考图制作适用于Codex的动态宠物。先生成作为基准的外观,再制作待机、奔跑、挥手等动作。将多个动画帧排列成八列九行的精灵图,并打包pet.json和spritesheet.webp。支持查看帧总览图与预览视频,也能只修复存在问题的动作。

适用场景

适合将原创吉祥物制作成Codex宠物,或把已有角色图片改成小型数字宠物。检查全身轮廓、面部、花纹、颜色和道具在不同动作中是否保持一致,同时检查应当透明的单元格中是否仍有内容残留。

使用示例

“请制作一只亲切的像素画风柴犬宠物,拿着一颗小石榴。”

“请只修复这只宠物外观发生变化的动作。”

注意事项

常规图像生成使用已安装的$imagegen,拼装使用随附的Python脚本。动作图像生成原则上分配给子代理。备用生成脚本需要OPENAI_API_KEY。判断是否完成时,除自动验证外,还需要进行视觉检查。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

客观评估

AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。

指令清晰度能否看出何时使用、做什么
A良好明确说明根据文字或参考图创建、修复、验证并打包Codex宠物。
步骤具体性步骤、输入输出和示例是否具体
A良好指定八列九行布局、192×208单元格、输出文件名及参考图要求。
安全性发送数据、删除文件、执行命令等是否有说明
A良好备用生成需要确认时须询问用户,镜像处理也要求目视检查与明确批准。
安装难易度所需工具和 API 密钥是否少且有说明
B部分不足需要已安装的$imagegen和随附脚本,但运行环境的配置说明不完整。

总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月20日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

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包含的文件(23)

  • SKILL.md23.3 KB
  • agents/openai.yaml560 B
  • LICENSE.txt10.5 KB
  • README.md2.6 KB
  • references/animation-rows.md1.4 KB
  • references/codex-pet-contract.md788 B
  • references/qa-rubric.md3.2 KB
  • scripts/compose_atlas.py5.1 KB
  • scripts/derive_running_left_from_running_right.py4.8 KB
  • scripts/extract_strip_frames.py10.4 KB
  • scripts/finalize_pet_run.py13.7 KB
  • scripts/generate_pet_images.py10.2 KB
  • scripts/inspect_frames.py8.3 KB
  • scripts/make_contact_sheet.py2.9 KB
  • scripts/package_custom_pet.py3.4 KB
  • scripts/pet_job_status.py4.0 KB
  • scripts/prepare_pet_run.py26.8 KB
  • scripts/queue_pet_repairs.py6.6 KB
  • scripts/record_imagegen_result.py7.7 KB
  • scripts/render_animation_videos.py4.1 KB
  • scripts/render_animation_videos.sh152 B
  • scripts/test_generate_pet_images.py5.0 KB
  • scripts/validate_atlas.py4.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Hatch Pet

OpenDesign integration. This is the unmodified Codex hatch-pet skill, vendored under skills/hatch-pet/ so any OpenDesign agent can run it. After the skill finishes packaging, the resulting spritesheet.webp (under ${CODEX_HOME:-$HOME/.codex}/pets/<pet-name>/) can be imported into the floating pet companion via Settings → General → Pets → Import Codex sprite. The import flow auto-detects the 8×9 / 192×208 atlas and lets the user pick which animation row to play (idle, running-right, waving, …).

Overview

Create a Codex-compatible animated pet from a concept, one or more reference images, or both. This skill owns pet-specific prompt planning, animation rows, frame extraction, atlas geometry, QA, previews, and packaging. It delegates visual generation to $imagegen.

User-facing inputs are optional. If the user omits a pet name, infer one from the concept or reference filenames; if that is not possible, choose a short appropriate name. If the user omits a description, infer one from the concept or references. If the user omits reference images, generate the base pet from text first, then use that base as the canonical reference for every animation row.

Generation Delegation

Use $imagegen for all normal visual generation.

Before generating base art, row strips, or repair rows, load and follow the installed image generation skill:

${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/SKILL.md

Do not call the Image API directly for the normal path. Let $imagegen choose its own built-in-first path and its own CLI fallback rules. If $imagegen says a fallback requires confirmation, ask the user before continuing.

When invoking $imagegen from this skill, pass the generated pet prompt as the authoritative visual spec. Do not wrap it in the generic $imagegen shared prompt schema and do not add extra polish, hero-art, photo, product, or illustration-style augmentation. Pet prompts should stay terse, sprite-specific, and digital-pet oriented; only add role labels for input images and any essential user constraint.

Use this skill's scripts for deterministic work only: preparing prompts and manifests, ingesting selected $imagegen outputs, extracting frames, validating rows, composing the final atlas, creating QA media, and packaging.

Hard boundary: do not create, draw, tile, warp, mirror, or synthesize pet visuals with local Python/Pillow scripts, SVG, canvas, HTML/CSS, or other code-native art as a substitute for $imagegen. For a normal pet run, expect up to 10 visual generation jobs: 1 base pet plus 9 row-strip jobs. The only exception is running-left, which may be derived by mirroring running-right only after running-right has been generated, visually inspected, and explicitly approved as safe to mirror. If mirroring is not appropriate, generate running-left as a normal grounded $imagegen row. If those calls are too expensive, blocked, or unavailable, stop and explain the blocker instead of fabricating row strips locally.

Do not mark visual jobs complete by editing imagegen-jobs.json, copying files into decoded/, or writing helper scripts that populate row outputs. Use record_imagegen_result.py for selected built-in $imagegen outputs, or generate_pet_images.py only for the documented secondary fallback. The deterministic scripts may only process already-generated visual outputs.

Only the base job may be prompt-only. Every row-strip job generated through $imagegen must use the input images listed in imagegen-jobs.json, including the canonical base reference created after the base job is recorded. Treat any row generation without attached grounding images as invalid.

Codex Digital Pet Style

Default pet art should match the Codex app's built-in digital pets: small pixel-art-adjacent mascots with compact chibi proportions, chunky readable silhouettes, thick dark 1-2 px outlines, visible stepped/pixel edges, limited palettes, flat cel shading, simple expressive faces, and tiny limbs. Even if the reference art is more detailed, complex or realistic, the generated pet should be simplified into this style.

Do NOT generate polished illustration, painterly rendering, anime key art, 3D rendering, glossy app-icon treatment, realistic fur or material texture, soft gradients, high-detail antialiasing, and complex tiny accessories. References that are more detailed than this should be simplified into the house style before row generation.

Transparency And Effects

Pet rows are processed into transparent 192x208 cells, so every generated pixel must either belong to the pet sprite or be cleanly removable chroma-key background. Prefer pose, expression, and silhouette changes over decorative effects.

Allowed effects must satisfy all of these conditions:

  • The effect is state-relevant and helps explain the animation.
  • The effect is physically attached to, touching, or overlapping the pet silhouette, not floating nearby.
  • The effect is inside the same frame slot as the pet and does not create a separate sprite component.
  • The effect is opaque, hard-edged, pixel-style, and uses non-chroma-key colors.
  • The effect is small enough to remain readable at 192x208 without clutter.

Examples of allowed effects: a tear touching the face, a small smoke puff touching the box or head, or tiny stars overlapping the pet during a failed/dizzy reaction.

Avoid these by default because they usually break transparent-background cleanup or component extraction:

  • wave marks, motion arcs, speed lines, action streaks, afterimages, blur, or smears
  • detached stars, loose sparkles, floating punctuation, floating icons, falling tear drops, separated smoke clouds, or loose dust
  • cast shadows, contact shadows, drop shadows, oval floor shadows, floor patches, landing marks, impact bursts, glow, halo, aura, or soft transparent effects
  • text, labels, frame numbers, visible grids, guide marks, speech bubbles, thought bubbles, UI panels, code snippets, checkerboard transparency, white backgrounds, black backgrounds, or scenery
  • chroma-key-adjacent colors in the pet, prop, effects, highlights, or shadows
  • stray pixels, disconnected outline bits, speckle/noise, cropped body parts, overlapping poses, or any pose that crosses into a neighboring frame slot

State-specific guidance:

  • waving: show the wave through paw pose only. Do not draw wave marks, motion arcs, lines, sparkles, or symbols around the paw.
  • jumping: show vertical motion through body position only. Do not draw shadows, dust, landing marks, impact bursts, bounce pads, or floor cues.
  • failed: tears, attached smoke puffs, or attached stars are allowed if they obey the allowed-effects rules; do not use red X marks, floating symbols, detached smoke, detached stars, or separate tear droplets.
  • review: show focus through lean, blink, eyes, head tilt, or paw position. Do not add magnifying glasses, papers, code, UI, punctuation, or symbols unless that prop already exists in the base pet identity.
  • running-right, running-left, and running: show locomotion through body, limb, and prop movement only. Do not draw speed lines, dust clouds, floor shadows, or motion trails.

Pet Naming

Ask the user for a pet name when they have not provided one and only if the conversation naturally allows it. If asking would slow down a direct execution request, choose a short appropriate name from the pet concept, reference image, or personality, then use that name consistently as the display name and as the source for the package folder slug.

Good built-in style examples:

  • Codex - The original Codex companion.
  • Dewey - A tidy duck for calm workspace days.
  • Fireball - Hot path energy for fast iteration.
  • Rocky - A steady rock when the diff gets large.
  • Seedy - Small green shoots for new ideas.
  • Stacky - A balanced stack for deep work.
  • BSOD - A tiny blue-screen gremlin.
  • Null Signal - Quiet signal from the void.

Visible Progress Plan

For every pet run, keep a visible checklist so the user can see where the work is up to. Create the checklist before starting, keep one step active at a time, and update it as each step finishes.

Before creating the checklist, establish the pet name when possible. Use the user-provided name when available; otherwise infer a short appropriate name from the concept or references. If the name is too long, not settled, or not appropriate for a friendly checklist, use your pet instead.

Use this checklist for a normal pet run, replacing <Pet> with the pet's name or your pet:

  1. Getting <Pet> ready.
  2. Imagining <Pet>'s main look.
  3. Picturing <Pet>'s poses.
  4. Hatching <Pet>.

What each step means:

  • Getting <Pet> ready. Choose or confirm the pet name, description, source images, and working folder.
  • Imagining <Pet>'s main look. Generate the pet's main reference image. This is required for new pets, even when the user does not provide an image, because it becomes the visual source of truth.
  • Picturing <Pet>'s poses. Create the pose rows, starting with idle and running-right to confirm the pet still looks consistent. Only mirror running-left if running-right clearly works when flipped.
  • Hatching <Pet>. Turn the approved poses into the final pet files, review the contact sheet, previews, and validation results, fix any broken parts, save pet.json and spritesheet.webp into the pet folder, then tell the user where the pet and QA files were saved.

Only mark a step complete when the real file, image, or decision exists. If this is just a repair run, start from the first relevant step instead of restarting the whole checklist.

Default Workflow

  1. Prepare a pet run folder and imagegen job manifest:
SKILL_DIR="${CODEX_HOME:-$HOME/.codex}/skills/hatch-pet"
python "$SKILL_DIR/scripts/prepare_pet_run.py" \
  --pet-name "<Name>" \
  --description "<one sentence>" \
  --reference /absolute/path/to/reference.png \
  --output-dir /absolute/path/to/run \
  --pet-notes "<stable pet description>" \
  --style-notes "<style notes>" \
  --force

All arguments above are optional except any flags needed to express user constraints. For text-only requests, pass the concept through --pet-notes and omit --reference; prepare_pet_run.py will infer a name, description, chroma key, and output directory as needed.

  1. Inspect the next ready $imagegen jobs:
python "$SKILL_DIR/scripts/pet_job_status.py" --run-dir /absolute/path/to/run
  1. For each ready job, invoke $imagegen with:
  • the prompt file listed in imagegen-jobs.json
  • every input image listed for the job, with its role label
  • the default built-in image_gen path unless $imagegen itself routes otherwise

The base job must complete first. If user references exist, the base job uses them. If no references exist, the base job may be prompt-only. After recording the base, record_imagegen_result.py writes decoded/base.png and references/canonical-base.png; all row jobs use the original references if present plus those canonical base images.

prepare_pet_run.py also creates 9 row-specific layout guide images under references/layout-guides/, one per animation state. Row jobs attach the matching guide as a layout-only input so the model can follow the correct frame count, spacing, centering, and safe padding. Treat these guides as invisible construction references: the generated row strip must not include visible boxes, borders, center marks, labels, guide colors, or the guide background.

When generating row strips, keep the identity lock in the row prompt authoritative: do not redesign the pet, and preserve the same head shape, face, markings, palette, prop, outline weight, body proportions, and silhouette. A row that looks like a related but different pet is failed even if the deterministic geometry QA passes.

Generate and record running-right before deciding how to complete running-left. Inspect running-right against the base and references. If the pet is visually symmetric enough that a horizontal mirror preserves identity, prop placement, handedness, markings, lighting, text-free details, and direction semantics, derive running-left with:

python "$SKILL_DIR/scripts/derive_running_left_from_running_right.py" \
  --run-dir /absolute/path/to/run \
  --confirm-appropriate-mirror \
  --decision-note "<why mirroring preserves this pet's identity>"

If there is any asymmetric side-specific marking, readable text, non-mirrored logo, handed prop, one-sided accessory, lighting cue, or direction-specific pose that would become wrong when flipped, do not mirror. Generate running-left with $imagegen using its row prompt and all listed grounding images, including decoded/running-right.png as a gait reference.

For the built-in path, record the selected source image from $CODEX_HOME/generated_images/.../ig_*.png. Do not record files from the run directory, tmp/, hand-made fixtures, deterministic row folders, or post-processed copies as visual job sources.

  1. After selecting a generated output for a job, ingest it:
python "$SKILL_DIR/scripts/record_imagegen_result.py" \
  --run-dir /absolute/path/to/run \
  --job-id <job-id> \
  --source /absolute/path/to/generated-output.png

This copies the image to the exact decoded path expected by the deterministic pipeline and records source metadata in imagegen-jobs.json.

  1. When all jobs are complete, finalize:
python "$SKILL_DIR/scripts/finalize_pet_run.py" \
  --run-dir /absolute/path/to/run

Expected output:

run/
  pet_request.json
  imagegen-jobs.json
  prompts/
  decoded/
  frames/frames-manifest.json
  final/spritesheet.png
  final/spritesheet.webp
  final/validation.json
  qa/contact-sheet.png
  qa/review.json
  qa/run-summary.json
  qa/videos/*.mp4

Package output is written outside the run directory by default. If CODEX_HOME is set, use it; otherwise use $HOME/.codex.

${CODEX_HOME:-$HOME/.codex}/pets/<pet-name>/
  pet.json
  spritesheet.webp

Review qa/contact-sheet.png, qa/review.json, final/validation.json, and qa/videos/ before accepting the pet.

Deterministic validation is necessary but not sufficient. Before calling the pet done, visually inspect the contact sheet for identity consistency. Block acceptance if any row changes species/body type, face, markings, palette, prop design, prop side unexpectedly, or overall silhouette.

Subagent Row Generation

After the base job has been recorded and references/canonical-base.png exists, row-strip visual generation must use subagents unless the user explicitly says not to use subagents for this session. Before row generation, state that subagents are being used and which row jobs are being delegated. If subagents cannot be spawned because the current environment or tool policy blocks them, stop before row-strip generation, explain the blocker, and ask for explicit user direction before continuing sequentially.

The parent agent must own the manifest and package writes.

Default flow:

  1. Parent runs prepare_pet_run.py.
  2. Parent generates and records base.
  3. Parent runs pet_job_status.py.
  4. Parent spawns subagents for idle and running-right first as identity and gait checks.
  5. Parent records the selected idle and running-right results returned by subagents.
  6. Parent decides whether running-left is safe to derive by mirror; if not, parent treats it as a normal grounded row job delegated to a subagent.
  7. Parent spawns subagents for every remaining non-derived row image-generation job.
  8. Each subagent receives the row prompt and every listed input image path, invokes $imagegen, and returns only the selected $CODEX_HOME/generated_images/.../ig_*.png source path.
  9. Parent alone runs record_imagegen_result.py, derive_running_left_from_running_right.py, repair queueing, finalization, QA, and packaging.

Subagent write boundary: do not let subagents edit imagegen-jobs.json, copy files into decoded/, run record_imagegen_result.py, run derive_running_left_from_running_right.py, run finalize_pet_run.py, or package the pet. This avoids manifest races and keeps provenance checks centralized.

Subagent handoff contract:

  • Give each subagent exactly one row job unless you are intentionally batching adjacent simple rows.
  • Include the row id, the absolute prompt file path, the full prompt text or an instruction to read that exact prompt file, and every input image path with its role label from imagegen-jobs.json.
  • Explicitly remind the subagent that the prompt's transparency and effects rules are mandatory: no detached effects, no wave marks for waving, no speed lines or dust for running rows, and only attached opaque sprite-like tears/smoke/stars when allowed by the state prompt.
  • Tell the subagent to inspect the generated candidate for frame count, identity consistency, clean flat chroma-key background, safe spacing, and forbidden detached effects before returning it.
  • Tell the subagent to return only the selected original $CODEX_HOME/generated_images/.../ig_*.png source path plus a one-sentence QA note. The parent decides whether to record or repair it.

Use this template for each subagent:

Generate the `<row-id>` row for this hatch-pet run.

Run dir: <absolute run dir>
Prompt file: <absolute prompt file>
Input images:
- <absolute path> — <role>
- <absolute path> — <role>

Read and follow the row prompt exactly, including the Transparency and artifact rules. Use `$imagegen` only; do not use local scripts to draw, tile, edit, or synthesize sprites.

Before returning, visually check:
- exact requested frame count
- same pet identity as the canonical base
- clean flat chroma-key background
- complete, separated, unclipped poses
- no forbidden detached effects or slot-crossing artifacts

Do not edit manifests, copy into decoded, record results, mirror rows, finalize, repair, or package. Return only:
selected_source=/absolute/path/to/$CODEX_HOME/generated_images/.../ig_*.png
qa_note=<one sentence>

No silent sequential fallback: if subagents cannot be used for row-strip visual generation, stop and ask for explicit user direction before continuing without them. Only an explicit user instruction such as "do not use subagents" or "run this sequentially" authorizes a normal sequential row-generation path. The final answer must report which row jobs were delegated to subagents and which, if any, were mirrored or repaired by the parent.

Repair Workflow

If finalization stops because row QA failed, queue targeted repair jobs:

python "$SKILL_DIR/scripts/queue_pet_repairs.py" \
  --run-dir /absolute/path/to/run

Then repeat the $imagegen generation and record_imagegen_result.py ingest loop for each reopened row job. Regenerate the smallest failing scope: the failed row, not the whole sheet.

For identity repairs, use the canonical base image, original references, contact sheet, and exact row failure note as grounding context. Repair only the failed row while preserving the canonical pet identity.

Secondary Image Generation Fallback

scripts/generate_pet_images.py is a secondary fallback for this skill.

Use it only when the installed $imagegen system skill is unavailable or cannot be invoked in the current environment. Normal pet creation should delegate visual generation to $imagegen, because $imagegen owns the built-in-first image generation policy and its own CLI fallback behavior.

Run the secondary fallback only after explaining why $imagegen cannot be used:

python "$SKILL_DIR/scripts/generate_pet_images.py" \
  --run-dir /absolute/path/to/run \
  --model gpt-image-2 \
  --states all

The secondary fallback requires OPENAI_API_KEY.

Rules

  • Keep $imagegen as the primary generation layer.
  • Keep reference images attached/visible for $imagegen whenever the chosen path supports references.
  • Attach the row's references/layout-guides/<state>.png image to every row-strip job as a layout-only guide, and do not accept outputs that copy guide pixels.
  • Use subagents for row-strip visual generation after the parent records the base image. The parent may generate the base, but row-strip jobs belong to subagents unless the user explicitly says not to use subagents for this session.
  • Generate every normal visual job with $imagegen: base plus all row strips that are not explicitly approved running-left mirror derivations.
  • Treat only the base job as eligible for prompt-only generation; every row job must attach its listed grounding images.
  • Delegate running-right first, then mirror running-left only when visual inspection confirms a mirror preserves identity and semantics; otherwise delegate running-left as a normal grounded $imagegen row.
  • Never substitute locally drawn, tiled, transformed, or code-generated row strips for missing $imagegen outputs.
  • Never manually mutate imagegen-jobs.json to claim a visual job completed.
  • Do not rely on generated images for exact atlas geometry; use this skill's deterministic scripts.
  • Use the chroma key stored in pet_request.json; do not force a fixed green screen.
  • Keep the pet's silhouette, face, materials, palette, and props consistent across all rows.
  • Enforce the transparency and effects rules above in every base, row, and repair prompt.
  • Treat visual identity drift as a blocker even when qa/review.json and final/validation.json have no errors.
  • Treat a contact sheet that shows cropped references, repeated tiles, white cell backgrounds, or non-sprite fragments as failed.
  • Treat forbidden detached effects, chroma-key-adjacent artifacts, shadows, glows, smears, dust, landing marks, wave marks, speed lines, or motion trails as failed rows.
  • Treat qa/review.json errors as blockers. Warnings require visual review.

Acceptance Criteria

  • Final atlas is PNG or WebP, 1536x1872, transparent-capable, and based on 192x208 cells.
  • Used cells are non-empty and unused cells are fully transparent.
  • Atlas follows the row/frame counts in references/animation-rows.md.
  • Contact sheet and preview videos have been produced unless explicitly skipped.
  • qa/review.json has no errors.
  • Row-by-row review confirms the animation cycles are complete enough for the Codex app.
  • ${CODEX_HOME:-$HOME/.codex}/pets/<pet-name>/pet.json and ${CODEX_HOME:-$HOME/.codex}/pets/<pet-name>/spritesheet.webp are staged together for custom pets.

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通过浏览器查看页面,执行点击、输入、截图和信息提取。主要用于检查OpenDesign的本地预览,以及核查网页应用的运行情况与质量。

  • 检查OpenDesign本地预览
  • 测试网页应用的点击和输入
  • 截取页面或元素图像
nexu-io/open-design10.3万2026年10月20日 更新

ai-music-album

免费有简介AI 评分 80分

用于AI音乐专辑制作,涵盖概念构思、歌词初稿、曲目排序和导出,适合独立专辑实验或品牌音乐企划;完整制作流程需另行安装上游资源包。

  • 策划独立制作的专辑
  • 围绕专辑主题起草歌词
  • 安排专辑曲目顺序
nexu-io/open-design10.3万2026年10月20日 更新

algorithmic-art

免费有简介AI 评分 80分

使用p5.js,根据计算规则与随机数创作生成艺术。固定随机种子即可重现相同画面,适合制作海报、表现动感的静态图像和艺术构图草案。

  • 根据规则制作海报
  • 创作具有动感的静态图像
  • 试验艺术作品的构图
nexu-io/open-design10.3万2026年10月20日 更新

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