illo
>-
供给资产档案
编程与开发 Agent
代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。
场景
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
适配 Agent
Claude Code + OpenAI Agents + Cursor
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add tmchow/illo-skill --skill illo
维护状态
新鲜
今天有推送
风险
需审查
Dependency or permission surface needs review
GitHub 质量
340
72/100 质量 · 64/100 信任
覆盖标签
审查说明
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
强可靠的选择,值得加入生产工作流候选列表。
信任
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
340 个 GitHub Stars
仓库活跃度
340 个 Star,17 个 Fork
维护状态
今天有推送
许可证
MIT
安装
npx skills add tmchow/illo-skill --skill illo
安装安全性
标准软件包或运行时安装路径
权限范围
secrets or environment access, shell or command execution
Agent 结果
暂未有 Agent 结果数据
文档
Usable metadata, review docs
风险摘要
生产前审查
- The skill relies on external CLIs (Codex, Grok) and an OpenRouter API key, which may require additional setup and could introduce environment-specific failure modes.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 已声明许可证
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- Local desktop 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- Navigate local resources
适用 Agent
安装决策
- 命令
- npx skills add tmchow/illo-skill --skill illo
- 策略
- 阻止
- 人工审查
- 是
信任与风险
- 信任
- 56/100
- 审计
- 75/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- The skill relies on external CLIs (Codex, Grok) and an OpenRouter API key, which may require additional setup and could introduce environment-specific failure modes.
- 暂未有 OpenAgentSkill 使用反馈数据
- 高风险权限提示:Shell or command execution, Secrets or environment access
Agent 安全 v2
35/100 · 避免自动安装
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
高
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- 高风险权限提示:Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install tmchow-illoAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20illo%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20illo%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/tmchow-illo/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use illo in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20illo%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/tmchow-illo/install
Install command: npx skills add tmchow/illo-skill --skill illo
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/tmchow-illo/install
LLM 文本格式
/api/skills/tmchow-illo/install?format=text
寻找替代方案
/api/skills/search?q=illo&limit=3
Agent 提示词
Use illo for this task. Review https://www.openagentskill.com/api/skills/tmchow-illo/install, then install with: npx skills add tmchow/illo-skill --skill illoRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Manifest
/api/registry/manifest/tmchow-illo
LLM 文本
/api/registry/manifest/tmchow-illo?format=text
安装别名
/api/registry/install/tmchow-illo
推荐
/api/registry/recommend?task=Use%20illo%20in%20an%20agent%20workflow&limit=3
适配 Agent
Local desktop
平台
Claude Code, OpenAI Agents, Cursor
Agent 决策面板
Fallback candidate for Local desktop
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
Local desktop
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- Local desktop 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 72/100 质量档案
先审查
- The skill relies on external CLIs (Codex, Grok) and an OpenRouter API key, which may require additional setup and could introduce environment-specific failure modes.
- 暂未有 OpenAgentSkill 使用反馈数据
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次Local desktop任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub 采用度
信息340 个 GitHub Stars
Star/Fork 活跃度
检查340 个 Star,17 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过今天有推送
许可证清晰度
通过MIT
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- The skill relies on external CLIs (Codex, Grok) and an OpenRouter API key, which may require additional setup and could introduce environment-specific failure modes.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 340 stars, 17 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
Choose a stronger alternative or inspect the source manually before any install attempt.
质量档案
强 适用于 Agent 工作流的候选
可靠的选择,值得加入生产工作流候选列表。
工作流匹配
在这些场景使用此 Skill
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
工作流匹配
加入完整工作流
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
UI-TARS Desktop
Run multimodal agents that operate desktop interfaces
MoneyPrinterTurbo
利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
Cua
Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).
概览
--- name: illo description: >- Creates original editorial illustrations where a recurring mascot character performs the idea — one caught scene by default, a hand-built explainer diagram (a flow, fan-out, timeline, loop, or stack) when the structure itself is the point, or a transparent character cutout (pose-only compositing asset, no scene or text) — in one of seventeen bundled looks (sixteen print, plus a photoreal toy-brick set). Also handles "surprise me" / "random" (optionally scoped to a focus or character): rolls provenance, builds three saying candidates, picks via interactive choice or auto-pick-best (`--autopick`), and renders one image. Triggers only when the skill is directly invoked or "illo" is requested; never on generic illustrate / draw / make-an-image requests. # x-release-please-start-version version: 0.34.4 # x-release-please-end argument-hint: "[idea or article URL] | build a character | install <character> | surprise me [focus] [--autopick] [using character]" author: Trevin Chow license: MIT metadata: hermes: tags: [illustration, riso, image-generation, editorial, mascot, codex, grok, openrouter] category: creative requires_toolsets: [terminal] openclaw: emoji: "🎨" homepage: https://illo-skill.com os: [macos, linux] requires: bins: [python3] ---
# Illo
Make original, distinctive editorial illustrations for written content. One image explains one idea: a key judgment, a flow, a before/after, a trap, a loop. A **recurring mascot** is the one performing the idea in every scene — the subject, never decoration. When one idea advances through stages, it can be a **mini-comic**: 2–4 panels inside a single image. And when the idea is itself a traceable structure — a pipeline, a fan-out, a timeline, a loop — it can be an **explainer**: the same mascot and look drawing the structure as a hand-built sketch-diagram with arrows and callouts (`references/composition.md`, "Two registers"; editorial scene is always the default). Or a **character cutout**: the mascot alone on a transparent PNG for downstream overlay — pose and contact continuity only, no idea, no text, no environment (`references/cutout.md`).
This is a configurable house style, not a generic image generator. The **methodology is the constant**; the **character pack and palette are the parameters** — and a character pack carries its **style** with it: one look per pack, chosen from the bundled look library (riso — grainy halftone, ink-layer offset, paper grain, one bold softly-rounded outline — plus blueprint, woodcut, pixel, clay, manila, chalk, phosphor, enamel, gouache, felt, diorama, sketchbook, bricks, fizz, bloom, and snes) or a custom style file. The default mascot is **Blot**, a deadpan ink-drop in riso. Palettes come from presets, the user's own palette file, or one derived color. Whatever the parameters, it is intentionally not a photo — with one deliberate exception, the `bricks` look, a toy-brick photography style — not a logo, not a corporate infographic, not a formal flowchart, not a UI mockup.
## Use cases — route the request
| The user wants | The path | |---|---| | **Illustrate an article / post / newsletter / URL** | Steps 0–7: route the source first (thesis → coverage: hero / hero+set / set / mini-comic — `references/composition.md`, "Source routing"), then shot list (hero row + anchors), one image per anchor, interleave by placement. | | **One image for a single concept** | Step 1 concept branch (up to ~3 quick questions if the idea is thin), then a single image. | | **Surprise / random** — "surprise me", "random", "surprise me with art quote using bray", "surprise me --autopick" | Read `references/surprise.md` in full: Step 0 first, then character + provenance (ignore `defaultCharacter`; `* quote` forces a cited quote; else ~1/3 roll), build **three** safe candidates, interactive picker or auto-pick-best (`--autopick` preferred for schedulers), then register from the locked saying, then Steps 3–7 as one image. Deliver saying + image. Poster titles default off; mini-comics still get per-panel labels. | | **A sequence — process, before→after, fail→fix** | One **mini-comic** when the progression sits in one place (shape routing in `references/composition.md` — the idea picks the shape, the destination never does). | | **A traceable structure** — "show the flow", "diagram the pipeline", "map the steps", "as an explainer" | The **explainer register** (`references/composition.md`, "The explainer register"): a hand-built flow / fan-out / timeline / loop / stack / system slice in the active look, the mascot a working part of it. Also reachable without the phrases when a unit's thesis IS the structure (the register gate). | | **Social-ready art for X posts / article body images** | 16:9 (or 1:1 when square is explicitly useful), bold `ink-punch`, watermark with the `x` handle if configured or asked. | | **X Article banner / hero image** | Use the unique banner format: **1536 × 640 px** when the user asks for an X Article hero/banner. Prompt and render through the normal `illo.py generate` image pipeline, with normal, undistorted character/object proportions and crop-safe breathing room. Do not satisfy this by manually compositing or rebuilding crops from another image unless the user explicitly asks for post-processing. | | **Blog / brand / site-matched art** | A named or custom palette, or derive the palette from one dominant color (`references/palettes.md`). | | **Their own mascot** — "make me a character", "use our mascot", "replace Blot" | The character builder: read `references/character-builder.md` in full and follow it end to end. | | **Community characters** — "what characters are available", "install blip", "install all characters", "update mole", "publish my character" | `references/pack-sharing.md` — engine `packs list/show/install/update`, including `packs install --all`; publish via a GitHub PR. | | **A different look** — "in blueprint", "woodcut style", "pixel version of blip" | Styles travel with character packs: build a **style variant pack** via `references/character-builder.md`, "Style variants". | | **Options to pick from, or "which model is best"** | Step 5b: `--count` variations or a model loop → `gallery` with a recommendation. | | **Fix an existing image** (stray title, recolor, mascot too decorative) | Edit prompts in `references/prompt-recipe.md`, passing the image back as `--ref`. | | **Character cutout / transparent PNG / overlay sticker** — "just the mascot", "no background", "paste on something else" | The **cutout register** (`references/cutout.md`): read in full, prompt from `references/prompt-recipe.md` "Cutout variant", generate with `--cutout` and `--aspect 1:1`. OpenRouter cutouts default to GPT Image 2 (not Grok). Not for explaining an idea — reroute to editorial if the ask needs a scene. | | **Animated idle / bot avatar / looping GIF of the mascot** | The **cutout register** plus `references/cutout.md`, "Idle loop / bot avatar": one transparent 1:1 cutout with `--cutout` and the character sheet as `--ref`, then programmatic motion on that PNG. |
## Prerequisites
The engine (`scripts/illo.py`, stdlib Python, no installs) renders through one of **three engine backends**; `python3` and network access are the only hard requirements. **Grok Bot** (Cursor's Grok Bot / the Grok desktop assistant) is a fourth, agent-side transport: use its built-in Grok image tool directly, not `illo.py generate`, when no user config explicitly selects an engine backend.
**Running the engine — set `$SKILL_DIR` inline in each block.** Every engine command below is `python3 "$SKILL_DIR/scripts/illo.py" …`. Set `SKILL_DIR` to the absolute path of the directory this `SKILL.md` was loaded from (it contains `scripts/illo.py` and `assets/`) **in the same command block that uses it** — shell state does not persist between separate command runs, so a value set in an earlier block is gone by the next. If the harness does not expose that path, find the installed `scripts/illo.py` and use its parent; if neither resolves, stop rather than guessing the working directory. The engine self-locates its own bundled assets, so `$SKILL_DIR` only has to be right enough to launch `illo.py` and to point `--ref` at the bundled character sheet.
Write the block **flatten-safe** — some hosts (Codex observed) collapse a fenced block to one line, turning a newline into a space. Terminate the assignment with `;` (`SKILL_DIR="…";` — without it, a flattened `SKILL_DIR="…" python3 "$SKILL_DIR/…"` becomes an env-prefix whose `$SKILL_DIR` expands to empty **before** the assignment applies, so the path collapses to `/scripts/illo.py`). Put **no comment on an assignment or command line** (a flattened `#` comments out the rest of the line and the command silently vanishes), and keep each invocation on **one line** (a flattened `\` continuation injects stray arguments). A wrong or unset value makes `doctor` (Workflow step 0) fail loudly (`can't open file …/scripts/illo.py`) — the signal to fix the path, not a skill fault.
- **Codex backend (free for Codex subscribers).** When the host has a usable **Codex CLI** — installed, `codex login`-ed, with the `image_generation` feature — illo can generate through the user's Codex subscription at no per-image charge (it draws on their Codex quota). No API key, no token: illo only shells out to the user's own CLI. Detected, not assumed; gpt-image-2 is automatic; unsupported on Windows/WSL. - **Grok CLI backend (free for Grok/xAI subscribers).** When the host has a usable **Grok CLI** — installed and `grok login`-ed — illo can generate through the user's Grok subscription via `grok -p` (headless), drawing on their Grok quota. Same env-free, token-free subprocess design as Codex. **Grok returns JPEG with no alpha, so it cannot make transparent cutouts** — those auto-fall back to a cutout-capable backend. The image tool exposes no model selector. - **Grok Bot native transport (agent-side, free for Grok Bot users).** When **you are Grok Bot** — specifically Cursor's Grok Bot / the Grok desktop assistant with the built-in Grok image tool — build the illo prompt and call that tool with the active character's model sheet as a reference image. Do not require the Grok CLI, Codex CLI, or an OpenRouter key; do not treat a missing engine backend as a reason to run `init`. This is not a generic "host image API" rule and not an `illo.py --backend` value. - **OpenRouter backend (paid, direct or explicit fallback).** Needs an **OpenRouter API key** in the user's config file — the **single credential channel** — written once by the user-run `init` (mode 600). The engine never reads secrets from the environment and never accepts them as command-line arguments. A host without a subscription CLI can select this engine path directly. A failed Codex/Grok CLI render does **not** spend money automatically: paid fallback requires `--allow-paid-fallback`. It is **model-selectable** (`--model`).
Capsule of the backend/transport model (resolution and precedence, the CLI requirements, the Grok Bot native path, the built-in image tool being automatic, quota vs. charge, cutout limits, Windows/WSL, fallback): **read `references/backends.md` in full before choosing or explaining a backend** — the mechanics live there, once.
### Setup is the user's job (never enter the key yourself)
Entering an API key is something the **user** does. Do not type, paste, print, or store the user's key — direct them to bootstrap it:
- **Bootstrap (user runs it):** `python3 "$SKILL_DIR/scripts/illo.py" init` — prompts for the key at a hidden prompt (never echoed) and writes the YAML config `${XDG_CONFIG_HOME:-~/.config}/illo/config.yaml` (mode 600). It can also store non-secret defaults: `--model`, `--palette`, `--aspect`, `--character`, `--watermark`. Use `--no-key` to update preferences without to
技术详情
- 版本
- 0.34.4
- 许可证
- MIT
- 最近更新
- 2026年8月22日
- 发布时间
- 2026年8月22日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 illo 准备的场景化草稿,可手动发布到 X。
For a repeatable workflow, this is a skill worth shortlisting before another blank prompt. illo: >- 340 stars https://www.openagentskill.com/skills/tmchow-illo?ref=x
可选:带安装命令的回复
Listing + install path for illo: https://www.openagentskill.com/skills/tmchow-illo?ref=x Install: npx skills add tmchow/illo-skill --skill illo
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- Trevin Chow
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 Trevin Chow,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/tmchow-illo)
[](https://www.openagentskill.com/skills/tmchow-illo)
[](https://www.openagentskill.com/skills/tmchow-illo/audit)
[](https://www.openagentskill.com/skills/tmchow-illo)作者
Trevin Chow
@trevin-chow
健康信号
- GitHub Stars
- 340
- 质量评分
- 41/100
- 最近 GitHub 推送
- 2026年8月22日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 0
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
Do not auto-install
- GitHub 采用度340 个 GitHub Stars信息
- Star/Fork 活跃度340 个 Star,17 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护今天有推送通过
- 许可证清晰度MIT通过
- README/SKILL.md 完整度公开元数据需要更完整的 README/SKILL.md 上下文信息
- 依赖与运行时风险command execution surface, credential or environment access检查
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