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技能库 智客分类:Agent 工作流 codex-pet

Codex Pet

代码 RunComfy上的宠物生成器. 构建一个与代码兼容的代码 宠物图案表. webp + pet.json 从单一的参考图像中将它降入"${CODEX_-HOME:-$HOME/.codex}/pets/<name>/",而Codex把它取出作为8内置相邻的自定义的Codex Pet. 这种技能产生了 Codex Pet 地图集 Codex 所期望的精确(1536x1872 PNG/WebP,8 cols x 9行,192x208单元格,9个动画状态——闲置,跑向右,跑向左,挥手,跳跃,失败,等待,跑向,审查). 呼叫 OpenAI GPT 图片2通过本地的RunComfy CLI编辑ONCE,作为"runcomfy run Openai/gpt-image-2/edit"来制作一款能动代码的Pet,然后用ImageMagick微变形——没有Codelex Pro,没有‘$imagegen',没有OPENAI_API_KEY需要,只有RUNCOMFY_TOKEN等编组所有9个动画行. 在"代码宠物","创建代码宠物","制作代码宠物","抓取代码宠物","/抓取图像","桌面宠物代码","代码宠物","spritesheet.webp"上触发,或明确要求为"OpenAI Codex"打造定制宠物.

380390 安装量

官方网址:作者主页

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

代码 RunComfy上的宠物生成器. 构建一个与代码兼容的代码 宠物图案表. webp + pet.json 从单一的参考图像中将它降入"${CODEX_-HOME:-$HOME/.codex}/pets/<name>/",而Codex把它取出作为8内置相邻的自定义的Codex Pet. 这种技能产生了 Codex Pet 地图集 Codex 所期望的精确(1536x1872 PNG/WebP,8 cols x 9行,192x208单元格,9个动画状态——闲置,跑向右,跑向左,挥手,跳跃,失败,等待,跑向,审查). 呼叫 OpenAI GPT 图片2通过本地的RunComfy CLI编辑ONCE,作为"runcomfy run Openai/gpt-image-2/edit"来制作一款能动代码的Pet,然后用ImageMagick微变形——没有Codelex Pro,没有‘$imagegen',没有OPENAI_API_KEY需要,只有RUNCOMFY_TOKEN等编组所有9个动画行. 在"代码宠物","创建代码宠物","制作代码宠物","抓取代码宠物","/抓取图像","桌面宠物代码","代码宠物","spritesheet.webp"上触发,或明确要求为"OpenAI Codex"打造定制宠物.

何时用

官方 description 未单独写出 Use when。按规范,代理会在用户任务与这段 description 的关键词匹配时激活本技能。

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Codex Pet — Pro Pack on RunComfy、What a Codex Pet is、Why this Codex Pet skill (vs OpenAI's official `hatch-pet`)、Codex Pet animation rows、Codex Pet style、Prerequisites。 其中含规范建议的小节:分步指令。

文件分析

文件分析:这是一份仅含 SKILL.md 的指令型技能,代理激活后整份正文进入上下文。

官方 description(原文)

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into `${CODEX_HOME:-$HOME/.codex}/pets/<name>/` and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as `runcomfy run openai/gpt-image-2/edit` to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no `$imagegen`, no OPENAI_API_KEY required, only RUNCOMFY_TOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

Codex Pet — Pro Pack on RunComfyWhat a Codex Pet isWhy this Codex Pet skill (vs OpenAI's official `hatch-pet`)Codex Pet animation rowsCodex Pet stylePrerequisitesCodex Pet pipeline (1 GPT Image 2 call, ~2 min)Step 1: Generate the canonical Codex Pet (1 call)Step 2: Normalize the canonical into a 192x208 Codex Pet cellStep 3: Build the 9 Codex Pet row strips programmaticallyHelpers9 Codex Pet rows with their per-frame micro-transforms

· 许可:MIT

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
codex-pet
description
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into `${CODEX_HOME:-$HOME/.codex}/pets/<name>/` and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as `runcomfy run openai/gpt-image-2/edit` to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no `$imagegen`, no OPENAI_API_KEY required, only RUNCOMFY_TOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
许可
MIT
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「codex-pet」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-8a4336aae974e1fb-Codex-Pet.html
请存为 .cursor/skills/codex-pet/SKILL.md 或 .claude/skills/codex-pet/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/prime-skills/runcomfy-agent-skills' --list

npx skills add 'https://github.com/prime-skills/runcomfy-agent-skills' --skill 'codex-pet'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版
--- name: codex-pet displayName: "Codex Pet — Pro Pack on RunComfy" description: > Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into `${CODEX_HOME:-$HOME/.codex}/pets//` and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as `runcomfy run openai/gpt-image-2/edit` to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no `$imagegen`, no OPENAI_API_KEY required, only RUNCOMFY_TOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex. homepage: https://www.runcomfy.com license: MIT --- # Codex Pet — Pro Pack on RunComfy [runcomfy.com](https://www.runcomfy.com/?utm_source=skills.sh&utm_medium=skill&utm_campaign=codex-pet) · [GPT Image 2 edit endpoint](https://www.runcomfy.com/models/openai/gpt-image-2/edit?utm_source=skills.sh&utm_medium=skill&utm_campaign=codex-pet) · [docs](https://docs.runcomfy.com/cli/introduction?utm_source=skills.sh&utm_medium=skill&utm_campaign=codex-pet) **Codex Pet generator on RunComfy.** Turn one source image into a Codex-compatible custom Codex Pet — `pet.json` + `spritesheet.webp` — drop it into `${CODEX_HOME:-$HOME/.codex}/pets//`, Codex picks it up next to the 8 built-in Codex Pets. ```bash npx skills add agentspace-so/runcomfy-agent-skills --skill codex-pet -g ``` ## What a Codex Pet is OpenAI Codex Pets (released May 2026) are pixel-art animated companions that float over your desktop while Codex codes — they react to mouse interaction and Codex status (scratching head when thinking, popping a speech bubble when a task completes). Codex ships with 8 built-in Codex Pets and supports custom Codex Pets installed locally as a folder under `${CODEX_HOME:-$HOME/.codex}/pets/`. Each custom Codex Pet folder contains exactly two files: - `pet.json` — manifest with `id`, `displayName`, `description`, `spritesheetPath`. - `spritesheet.webp` — Codex Pet sprite atlas, **1536x1872** PNG or WebP, 8 columns x 9 rows of 192x208 cells, transparent background. The 9 rows correspond to 9 animation states Codex plays. Each row uses a fixed number of leading frames; trailing cells stay fully transparent. ## Why this Codex Pet skill (vs OpenAI's official `hatch-pet`) OpenAI ships an official [`hatch-pet`](https://github.com/openai/skills/blob/main/skills/.curated/hatch-pet/SKILL.md) skill that produces the same Codex Pet artifact via the Codex-internal `$imagegen` system skill (requires Codex Pro + `$imagegen` configured). **This Codex Pet skill is a drop-in alternative that runs via the RunComfy CLI**: a single `RUNCOMFY_TOKEN` plus `runcomfy` and `magick` binaries — no Codex Pro, no `$imagegen`, no OPENAI_API_KEY. The output Codex Pet artifact is identical — same `pet.json` shape, same `spritesheet.webp` 1536x1872 atlas, same 9 animation rows — so Codex treats this Codex Pet exactly like one made by `hatch-pet`. This skill follows the same pattern Codex's built-in Codex Pets use: **one canonical pose, replicated across cells with ImageMagick micro-transforms** for subtle animation (1-2 px shifts, blink frames, tilt frames). That matches what the official `hatch-pet` output actually looks like cell-by-cell — the Codex Pet animation visible in the Codex desktop app is intentionally subtle. Pick this skill when: - You want a custom Codex Pet but don't have Codex Pro / `$imagegen`. - You want a custom Codex Pet built via the RunComfy Model API. - You want **batch Codex Pet generation** from a folder of source images (one canonical call per pet). - You're entering the OpenAI Codex Pet contest with a different model behind the visuals. - You said "codex pet", "/hatch", "make me a codex pet", "spritesheet.webp", "desktop pet for codex" explicitly. ## Codex Pet animation rows Codex reads one fixed atlas: 8 columns, 9 rows, 192x208 cells. Each Codex Pet row corresponds to one animation state with a specific number of leading frames. | Row | State | Used columns | Frames | Codex Pet behavior | |---|---|---|---|---| | 0 | idle | 0-5 | 6 | calm breathing/blinking; the reduced-motion first frame for the Codex Pet | | 1 | running-right | 0-7 | 8 | Codex Pet locomotion to the right | | 2 | running-left | 0-7 | 8 | mirrored locomotion to the left | | 3 | waving | 0-3 | 4 | greeting / attention gesture | | 4 | jumping | 0-4 | 5 | anticipation, lift, peak, descent, settle | | 5 | failed | 0-7 | 8 | error / sad / deflated reaction | | 6 | waiting | 0-5 | 6 | patient idle variant | | 7 | running | 0-5 | 6 | active working / in-progress loop (NOT foot-running) | | 8 | review | 0-5 | 6 | focused / inspecting / thinking | Trailing cells after each row's last used column must be fully transparent. ## Codex Pet style The Codex Pet visual house style: - **EXAGGERATED chibi proportions**: head occupies ~60 percent of total figure height; body and legs are tiny stubby and short. The whole figure should fit a near-square bounding box. - pixel-art-adjacent low-resolution mascot, chunky silhouette - thick dark 1-2 px outlines, visible stepped pixel edges - limited palette, flat cel shading, simple expressive face, tiny limbs - transparent background Avoid: motion lines, drop shadows, glows, sparkles, floating effects, text labels, scenery, white/black backgrounds. ## Prerequisites 1. **RunComfy CLI** — `npm i -g @runcomfy/cli` 2. **RunComfy account** — `runcomfy login`. CI alternative: `RUNCOMFY_TOKEN=`. 3. **ImageMagick** — `brew install imagemagick` (macOS) or `apt-get install imagemagick` (Linux). Provides the `magick` command for the deterministic atlas assembly. 4. **A source image URL** — publicly fetchable HTTPS, JPEG/PNG/WebP, the subject the Codex Pet will be modeled on. ## Codex Pet pipeline (1 GPT Image 2 call, ~2 min) 1. **Canonical Codex Pet** — single `runcomfy run openai/gpt-image-2/edit` call producing one 1024x1024 chibi pose on a magenta chroma-key background. 2. **Cell normalization** — chroma-key magenta → alpha 0, trim, aspect-fit into 192x208 with transparent padding. 3. **9 row strips, programmatic** — for each of 9 animation states, build the row's 8 cells via ImageMagick micro-transforms (translate / mask / mirror) of the canonical cell. Trailing cells filled with transparent 192x208. 4. **Atlas** — stack 9 row strips vertically into the 1536x1872 Codex Pet atlas. 5. **WebP** — convert atlas PNG to WebP. 6. **Manifest + install** — write `pet.json`, copy both files into `${CODEX_HOME:-$HOME/.codex}/pets//`. The micro-transform approach matches what Codex's built-in Codex Pets actually do — the Codex Pet animation is intentionally subtle, so 1-2 px shifts and blink masks per cell give the right visual feel without burning 72 GPT Image 2 calls. ### Step 1: Generate the canonical Codex Pet (1 call) ```bash PET_NAME="my-pet" PET_DESC="A friendly companion for late-night refactors." SOURCE_URL="https://.../source.png" RUN_DIR="./codex-pet-run/${PET_NAME}" CHROMA="#FF00FF" # magenta chroma-key mkdir -p "${RUN_DIR}" runcomfy run openai/gpt-image-2/edit \ --input "{ \"prompt\": \"Generate one canonical Codex digital pet sprite based on the input image. EXAGGERATED chibi proportions: the head occupies about 60 percent of the total figure height; body and legs are tiny stubby and short. The whole pet figure must fit within a near-square bounding box (overall aspect close to 1:1). Pixel-art-adjacent low-resolution mascot, chunky whole-body silhouette, thick dark 1-2 px outline, visible stepped pixel edges, limited palette, flat cel shading, simple expressive face, tiny limbs. Centered in the image. No polished illustration, no painterly render, no anime key art, no 3D render, no glossy app-icon polish, no realistic detail. Background: solid flat magenta ${CHROMA} chroma-key fill outside the pet silhouette. The pet itself must not use the chroma-key color or any close-to-magenta highlights. No gradients, no shadows, no halos, no scenery, no text. Identity preserved from the input image.\", \"images\": [\"${SOURCE_URL}\"], \"size\": \"1024*1024\" }" \ --output-dir "${RUN_DIR}/decoded/" BASE=$(ls "${RUN_DIR}/decoded/"*.png | head -1) echo "canonical Codex Pet: ${BASE}" ``` ### Step 2: Normalize the canonical into a 192x208 Codex Pet cell Chroma-key magenta to alpha, trim to the pet sprite bounding box, aspect-fit into 192x208 with transparent padding. ```bash magick "${BASE}" \ -fuzz 18% -transparent "${CHROMA}" \ -alpha set \ -trim +repage \ -resize 192x208 \ -gravity center \ -background none \ -extent 192x208 \ "${RUN_DIR}/cell.png" ``` The 18% fuzz is tuned for GPT Image 2's anti-aliased magenta edges. Adjust to 25% if the Codex Pet has wider magenta halos, or to 8-10% if the pet has near-magenta highlights getting clipped. ### Step 3: Build the 9 Codex Pet row strips programmatically For each row, build 8 cells from the canonical via ImageMagick micro-transforms, fill unused trailing cells with transparent, then concatenate into a 1536x208 row strip. ```bash SRC="${RUN_DIR}/cell.png" mkdir -p "${RUN_DIR}/cells" # Helpers shift_cell() { magick "$SRC" -background none -roll "+${1}+${2}" -alpha set "$3"; } rotate_cell() { magick "$SRC" -background none -distort SRT "$1" -alpha set "$2"; } make_blink() { # Eyes are roughly at y=80-100 in a 208-tall cell. # Soften with a skin-tone overlay across that horizontal band. magick "$SRC" \ -region 80x6+56+82 -fill "#f4e6d8" -colorize 70% -blur 0x0.5 +region "$1" } blank_cell() { magick -size 192x208 xc:none -alpha set "PNG32:$1"; } build_row() { local row=$1; shift local i=0 for spec in "$@"; do local out="${RUN_DIR}/cells/row${row}-frame${i}.png" case "$spec" in base) cp "$SRC" "$out" ;; blink) make_blink "$out" ;; shift:*) IFS=':' read -r _ x y <<< "$spec"; shift_cell "$x" "$y" "$out" ;; rotate:*) IFS=':' read -r _ ang <<< "$spec"; rotate_cell "$ang" "$out" ;; esac i=$((i+1)) done while [ "$i" -lt 8 ]; do blank_cell "${RUN_DIR}/cells/row${row}-frame${i}.png" i=$((i+1)) done magick "${RUN_DIR}/cells/row${row}-frame"*.png +append -alpha set \ "${RUN_DIR}/cells/row${row}-strip.png" } # 9 Codex Pet rows with their per-frame micro-transforms build_row 0 base base blink base base blink # idle (6) build_row 1 base shift:1:0 shift:2:-1 shift:1:0 base shift:-1:0 shift:-2:-1 shift:-1:0 # running-right (8) # row 2 = running-left = horizontal flip of row 1, built below build_row 3 base shift:0:-1 base shift:0:-1 # waving (4) build_row 4 shift:0:2 base shift:0:-8 shift:0:-2 base # jumping (5) — vertical arc build_row 5 base shift:0:1 rotate:1 shift:0:1 shift:0:2 shift:0:1 rotate:-1 base # failed (8) build_row 6 base base shift:0:-1 base base shift:0:1 # waiting (6) build_row 7 base shift:0:-1 base shift:0:-1 base shift:0:-1 # running (6) build_row 8 base rotate:-2 base rotate:2 base base # review (6) # Row 2: running-left = mirror of running-right magick "${RUN_DIR}/cells/row1-strip.png" -flop -alpha set "${RUN_DIR}/cells/row2-strip.png" ``` The micro-transform table is what gives the Codex Pet its readable-but-subtle motion in Codex. Tweak the numbers per row to taste; the deltas are intentionally small (1-2 px) so the Codex Pet feels alive without becoming distracting. ### Step 4: Compose the Codex Pet atlas Stack the 9 row strips vertically into the 1536x1872 Codex Pet atlas, then convert to WebP. ```bash magick \ "${RUN_DIR}/cells/row0-strip.png" \ "${RUN_DIR}/cells/row1-strip.png" \ "${RUN_DIR}/cells/row2-strip.png" \ "${RUN_DIR}/cells/row3-strip.png" \ "${RUN_DIR}/cells/row4-strip.png" \ "${RUN_DIR}/cells/row5-strip.png" \ "${RUN_DIR}/cells/row6-strip.png" \ "${RUN_DIR}/cells/row7-strip.png" \ "${RUN_DIR}/cells/row8-strip.png" \ -append -alpha set "${RUN_DIR}/spritesheet.png" magick "${RUN_DIR}/spritesheet.png" "${RUN_DIR}/spritesheet.webp" ``` ### Step 5: Write the Codex Pet manifest ```bash cat > "${RUN_DIR}/pet.json" </`. **Why use this Codex Pet skill instead of `hatch-pet`?** Official `hatch-pet` requires the Codex-internal `$imagegen` system skill (Codex Pro). This skill needs only `RUNCOMFY_TOKEN` and runs the same animation-row spec via the RunComfy CLI, with one GPT Image 2 call total. **How long does a Codex Pet generation take?** ~2 minutes — 1 GPT Image 2 edit call (~90s) plus a few seconds of ImageMagick atlas assembly. **Why only one API call?** The Codex Pet animation in the Codex desktop app is intentionally subtle (you can confirm by inspecting any built-in Codex Pet's atlas — 72 cells of nearly-identical poses with tiny variations). One canonical pose plus deterministic ImageMagick micro-transforms produces the same animation feel without burning 72 separate generation calls. **Can the Codex Pet skill take a non-human subject?** Yes — pets, mascots, objects, foods all work. The base prompt simplifies the source into the Codex Pet house style automatically. **How do I install my Codex Pet?** Copy `pet.json` and `spritesheet.webp` into `${CODEX_HOME:-$HOME/.codex}/pets//` and reload Codex. **What if the canonical Codex Pet drifts off identity?** Re-run step 1 with a tighter identity-preservation prompt (e.g. name specific features: hair color, glasses, accessory). Steps 2-6 are deterministic and don't need to change. **What size is each Codex Pet frame?** 192x208 px. Each row strip is 1536x208 (8 frames). Final Codex Pet atlas is 1536x1872 (9 stacked rows). **Can I add custom poses or replace rows?** Yes — modify the `build_row` calls in step 3. The atlas slot count per row must match the Codex contract (idle=6, running-right/left=8, waving=4, jumping=5, failed=8, waiting/running/review=6) for Codex to play them correctly. ## Limitations - **One canonical pose per Codex Pet** — animation is via ImageMagick transforms, not multi-frame model generation. This matches the built-in Codex Pets' subtle animation but won't produce dramatic motion (e.g. distinct frame-by-frame running cycle). - **GPT Image 2 doesn't output alpha** — the magenta chroma-key + post-process is a workaround. If the Codex Pet has near-magenta colors (rare for chibi palettes), switch the chroma-key to a different solid (`#00FFFF` cyan or `#00FF00` green) in both the prompt and the post-process. - **Identity drift** — GPT Image 2 may simplify the source image identity into Codex Pet style; specific small features (e.g. earrings, prop colors) may shift. - **No audio / voice on Codex Pet** — Codex Pets are visual-only. ## Exit codes The `runcomfy` CLI uses sysexits-style codes: | code | meaning | |---|---| | 0 | Codex Pet canonical generated successfully | | 64 | bad CLI args | | 65 | bad input JSON for the Codex Pet call / schema mismatch (e.g. `size: "1024_1024"` instead of `"1024*1024"`) | | 69 | upstream 5xx | | 75 | retryable: timeout / 429 | | 77 | not signed in or token rejected | `magick` (ImageMagick) returns 0 on a clean Codex Pet atlas; non-zero indicates a missing input frame or output-path permission issue. Full reference: [docs.runcomfy.com/cli/troubleshooting](https://docs.runcomfy.com/cli/troubleshooting?utm_source=skills.sh&utm_medium=skill&utm_campaign=codex-pet). ## How it works 1. The skill calls `runcomfy run openai/gpt-image-2/edit` once with the user's source image and a tight chibi-proportion prompt, producing a 1024x1024 canonical Codex Pet on magenta. 2. ImageMagick chroma-keys the magenta to alpha 0, trims the sprite bbox, aspect-fits into a 192x208 cell. 3. ImageMagick programmatically builds 9 row strips by applying micro-transforms (1-2 px translate, blink mask, rotate, mirror) to the canonical cell. 4. The 9 row strips stack into the 1536x1872 Codex Pet atlas; the atlas converts to WebP. 5. A `pet.json` manifest is written; both files are copied into `${CODEX_HOME:-$HOME/.codex}/pets//` where Codex picks up the custom Codex Pet automatically. ## Credits The 9-row Codex Pet atlas spec — column counts, frame counts, cell dimensions — comes from OpenAI's official [`hatch-pet`](https://github.com/openai/skills/tree/main/skills/.curated/hatch-pet) skill (MIT licensed). The animation-row contract and the chroma-key strategy are documented there. This skill reuses the spec but swaps the visual generator (`$imagegen` → RunComfy GPT Image 2) and the atlas assembly (Python → ImageMagick) so it runs without Codex Pro. ## What this skill is not Not a Codex client. Not a `hatch-pet` replacement when `$imagegen` is available — official `hatch-pet` is preferable when Codex Pro is in play. Not a self-hosted GPT Image 2 — depends on a working RunComfy account. ## Security & Privacy - **Token storage**: `runcomfy login` writes the API token to `~/.config/runcomfy/token.json` with mode 0600. Set `RUNCOMFY_TOKEN` env var to bypass the file in CI. - **Input boundary**: Codex Pet prompts are passed as JSON via `--input`. The CLI does NOT shell-expand. No shell-injection surface. - **Third-party content**: source image URL is fetched by the RunComfy server. Treat external URLs as untrusted — image-based prompt injection is a known risk for any image-edit model. - **Outbound endpoints**: only `model-api.runcomfy.net` and `*.runcomfy.net` / `*.runcomfy.com`. - **Generated-file size cap**: the CLI aborts any single Codex Pet canonical download > 2 GiB. - **Local install path**: the final Codex Pet writes to `${CODEX_HOME:-$HOME/.codex}/pets//`. No remote upload.

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Agent 工作流

Agent Team Orchestration

管弦乐团多代理团队,任务设定周期,交接协议,审查工作流程. 使用时间: (1)建立2+特派员队伍,具有不同专业,(2)确定任务路线和生命周期(收录框_ spec_建设_审查_完成),(3)在特派员之间制定交接协议,(4)建立审查和质量关口,(5)管理特派员之间的交流和文物共享.

Agent 工作流

Superpowers

Spec-first,TDD,子代理驱动的软件开发工作流程. 当:(1)构建任何新功能或应用——触发脑暴_计划_子代理执行回路,(2)调试出一个bug或测试失败——触发系统性的根起过程,(3)用户说"让我们构建","帮助我计划","我想添加X",或"这个被打破",(4)完成一个功…