illo

审查 · 56
已收录

>-

Verified installs0
Stars340
版本0.34.4
质量72/100 ·
信任56/100 · Do not auto-install
审计75/100 · 需审查

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。

浏览赛道

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

编程GitHub automation自动化agent-skill

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

72

可靠的选择,值得加入生产工作流候选列表。

信任

Do not auto-install
56

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

审计

需审查
75

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.

CodexClaude CodeCursorOpenAgentSkill CLI

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。

打开 JSON

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

CodexClaude CodeCursorOpenAgentSkill CLIOpenAI AgentsCLI

安装决策

命令
npx skills add tmchow/illo-skill --skill illo
策略
阻止
人工审查

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

安装命令

npx skills add tmchow/illo-skill --skill illo

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

Blocked for auto-install阻止

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.

通过 API 解析

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。

网络访问

Skill 可能访问远程页面、API、仓库或外部服务。

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。

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。

skill install

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-illo

Agent 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。

打开文本计划

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。

打开安装 API

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 illo

Registry 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。

打开 Manifest

适配 Agent

71/100

Local desktop

平台

Claude Code, OpenAI Agents, Cursor

审计报告

需审查 · 75/100

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。

查看审计报告查看评估报告

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。

71
就绪度
原型验证
阶段

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. 1在沙盒 Agent 中安装它,并端到端完成一次Local desktop任务。
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 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.

56
OpenAgentSkill 信任评分

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

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。

72
GitHub Stars
340
新鲜度
今天
安装就绪
许可证
MIT
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.

工作流匹配

在这些场景使用此 Skill

工作流匹配

加入完整工作流

替代方案短名单

安装前对比

可能适合该任务的相近 Skill。

对比全部

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

71
就绪
原型验证
阶段

仓库近期活跃

审计

安装审查

安装与采用审查

75
需审查
安全性
70/100
维护状态
100/100
安装
92/100
打开完整审计查看评估报告

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。

0
已验证
Needs first agent run自动安装: 先审查最近: 未知
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。

安装

加入 Agent 工作流

免费且开源. 在生产 Agent 中安装前请先审查报告。

增长闭环

分享工具包

X

为 illo 准备的场景化草稿,可手动发布到 X。

策展说明
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
打开 X 草稿
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
打开回复草稿

收录来源

Registry 收录

可认领

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。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/tmchow-illo?metric=listed&label=Listed)](https://www.openagentskill.com/skills/tmchow-illo)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/tmchow-illo?metric=trust&label=Trust)](https://www.openagentskill.com/skills/tmchow-illo)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/tmchow-illo?metric=audit&label=Audit)](https://www.openagentskill.com/skills/tmchow-illo/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/tmchow-illo?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/tmchow-illo)

作者

T

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
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信任与安全

Do not auto-install

56
  • 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