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art-director艺术总监

Agent Skill

art-director 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:art-director(艺术总监)
来源仓库:https://github.com/machinesofdesire/art-director
安装命令:
openclaw skills install art-director
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install art-director

简介

为品牌故事生成符合美学标准的视觉图像提案。art-director 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 融合持久品牌风格与每帧编辑逻辑产出连贯视觉效果。
  • 适用于营销素材、广告创意等研究检索类需求。
  • 输出为提示词而非直接图片,依赖外部文生图引擎。
  • 版权归属需明确约定,商用前应核实授权范围。

SKILL.md

name
art-director
description
Generate on-aesthetic images for any brand telling stories with images. Combines a persistent brand aesthetic with per-image editorial thinking to produce visuals that do work — parallel arguments, not decoration. Wraps nano-banana-pro (Gemini) for the underlying image generation.
version
1.0.3
emoji
🎨
homepage
https://github.com/MachinesOfDesire/art-director
metadata
openclaw
requires
bins
env
primaryEnv
GEMINI_API_KEY

Art Director Skill

Generate on-aesthetic images for any brand telling stories with images — publications, newsletters, essays, reports, brand blogs, longform product marketing, anything where the image has to feel like it belongs to you and has to do work.

The difference between this skill and a text-to-image tool: A text-to-image tool takes a description and renders it. This skill takes (a) your brand's persistent aesthetic and (b) the specific brief for this image, and generates something that argues. The image is a parallel statement to the writing, not a summary of it.


What this looks like

One brief, nine shipped aesthetics. Same image brief run through each preset — nine different arguments from the same subject.

DocumentaryProduct-photoConceptual-illustration
DocumentaryProduct photoConceptual
Observed, photographicStudio photography, seamlessPainterly, metaphor-forward
SchematicOrbitalEditorial-collage
SchematicOrbitalEditorial collage
Ink linework, paper, exploded-viewFlat vector, mid-century posterTorn paper, halftone, analog
Product-renderSynthwavePhosphor
Product renderSynthwavePhosphor
3D render, architecturalChrome, neon, after-midnightGreen CRT, scan lines, low-bit

A detailed worked example (same brief across three of these aesthetics, with the thinking that produced the brief) lives further down in this file.


The two layers

Every generation is brand aesthetic + per-image brief → final prompt. Two files, two roles:

aesthetic.md — your brand's visual identity. Written once, edited as you learn. Defines palette, composition, rendering, tone, constraints, and reference anchors that stay consistent across every image you generate. Think of this as your publication's or brand's visual voice. Calling agents never touch this file; operators do.

The brief — what this specific image needs to do. Written fresh each call by the agent or human requesting the image. Subject, argument, emotional register for this piece. Never contradicts the aesthetic; sharpens it for this particular story.

The skill merges them. Operators control the aesthetic. Agents control the brief. Nobody has to know the other layer to do their job.


Setup

Install nano-banana-pro first — this skill calls it for image generation:

openclaw skill install nano-banana-pro

Pick a starting aesthetic preset and copy it into your workspace:

python3 art_director.py install --preset documentary
# or one of: conceptual-illustration, product-render, product-photo,
#            schematic, editorial-collage, synthwave, phosphor, orbital
# or: --preset blank  to start from an empty template

This writes aesthetic.md into the current directory. Edit it freely — the preset is a template, not a runtime value.

Optional environment variables:

  • OUTPUT_DIR — where generated images land (default: current directory)
  • AESTHETIC_PATH — path to aesthetic.md (default: ./aesthetic.md)
  • GEMINI_API_KEY — required for image generation (inherited by nano-banana-pro)

How to use this skill

When asked to create an image for a piece of content, follow this process.

Step 1 — Understand the brief

You need at minimum:

  • What the piece is about — not just the topic, the argument
  • Tone — urgent, contemplative, melancholy, sardonic, precise, angry, hopeful
  • What to avoid — topic-specific clichés to rule out

Ask for any missing elements before proceeding. A vague brief produces a vague image.

Step 2 — Apply art direction thinking

Before writing a single prompt, work through these questions:

What must this image DO? Not what should it look like — what should it accomplish emotionally and intellectually? Define the function before defining the form. A piece about labor displacement should make the reader feel the weight before they read a word. A piece about financial abstraction should feel cold and constructed.

What is the visual metaphor? Every image worth making has one. Not a literal illustration of the topic — a metaphor that the reader carries into the text. A piece about regulatory capture is not a photograph of a door with a lock. It might be a hand adjusting a scale that was never level to begin with. The literal image is the first idea. It is almost never the right one.

What clichés must be avoided? Every topic has visual clichés that signal lazy thinking:

  • AI: robot hands, Matrix green text, glowing brains, humanoid robots, circuit board patterns
  • Finance: stock tickers, dollar signs, Wall Street facades, upward-pointing arrows
  • Politics: Capitol buildings, handshakes, flags
  • Climate: melting ice, smokestacks, polar bears
  • Technology: devices, keyboards, code on screens
  • Product / SaaS: dashboards floating in space, gradient backgrounds, abstract geometry

Name the clichés specific to this brief. Actively move away from them.

Does the brief require departing from the brand aesthetic? Most of the time, no — the aesthetic holds. Occasionally a piece demands departure (a tonal shift, a special issue, an unusual subject). Departure requires editorial justification, not aesthetic preference. If you're departing, say so and say why in your delivery notes.

Step 3 — Construct the image prompt

The prompt is a creative brief to a generative system. Apply these rules:

Use art and photography language, not tech language:

  • "chiaroscuro lighting" not "dramatic shadows"
  • "Kodachrome warmth" not "warm colors"
  • "grain and imperfection" not "realistic texture"
  • "negative space as structure" not "minimalist"
  • "desaturated with single color accent" not "muted colors"

Be specific about what matters:

  • Mood and emotional register
  • Compositional approach (rule of thirds, centered, asymmetric, etc.)
  • Color temperature and saturation
  • Light source and quality
  • Texture and finish

Be silent about what doesn't: Let the system find its own solutions for secondary elements. Over-specification produces over-engineered images.

Always include these technical specifications (the skill will append them if you forget):

  • 16:9 aspect ratio — required for standard publication header format
  • no embedded text or typography — typography is set separately by the CMS
  • Fight the generic AI aesthetic: grain, imperfection, photographic texture — not hyper-rendered smoothness

Structure your prompt as: [Visual metaphor / scene], [compositional approach], [light quality], [color palette and temperature], [texture and finish], [reference anchor if relevant], 16:9, no embedded text, [any per-piece direction]

The skill will automatically prepend your brand's aesthetic.md as the opening context. Your brief should sharpen and specify within that frame, not restate it.

Step 4 — Generate

python3 art_director.py generate \
  --brief "your full art-directed prompt" \
  --output "YYYY-MM-DD-slug.png" \
  [--resolution 2K]

Resolutions:

  • 1K — draft / review pass
  • 2K — standard publication (default)
  • 4K — high-resolution final

Step 5 — Review

After generation, review against the brief:

  • Does it do the work defined in Step 2?
  • Does it avoid the named clichés?
  • Does the tone match?
  • Does it feel on-brand (aesthetic held) while still specific to this piece?
  • If the piece has a CMS that overlays text on the image, is there space for that?

If the image feels decorative rather than editorial, identify which element turned it generic. Adjust the prompt toward the metaphor, away from the literal. Regenerate.

One refinement pass is expected and normal. More than two passes usually means the metaphor needs rethinking, not the prompt.

Step 6 — Deliver

Report:

  • The saved image path
  • The final prompt used (for the prompt archive)
  • A one-sentence rationale: what does this image argue, and how does it connect to the piece?

The iteration loop

Aesthetic configs only get good through iteration. After install, generate a batch of 10–20 images against your current aesthetic with varied briefs. Review them side by side. Tune the aesthetic. Regenerate.

python3 art_director.py batch --briefs briefs.txt --outdir ./iteration-01/

briefs.txt is one brief per line (blank lines ignored). The skill generates one image per brief against the current aesthetic.md. This is how you learn what your brand actually wants by seeing what it doesn't want.


Editorial standards

No people without abstraction. Do not generate identifiable individuals, real or synthetic. If human presence is needed, use silhouette, abstraction, hands, shadow, partial framings. The ethics of synthetic portraiture are unresolved. Don't go there.

No text in the image. Ever. Text rendering in generative models is unreliable and typography is a typographer's job. Images with text embedded will look wrong even when they work.

Credit the image. If your brand has a convention for labeling AI-generated images, use it. Transparency is non-negotiable.

Bias awareness. Generative models default toward Western, lighter-skinned, conventionally attractive subjects. Direct against the default when the image calls for diversity the model would otherwise erase.


Worked example

A real brief run through three of the nine shipped presets, so you can see the two-layer model working: same image brief, different aesthetics, three different arguments. (The full nine-aesthetic grid lives in README.md.)

Piece: An essay about silent obsolescence — things that still run but no longer serve their purpose. The piece never names projection; the image carries the metaphor.

Tone: Quiet, slightly haunted, observational.

Avoid: Dramatic beams of light, empty theaters, film reels mid-flight, anything that romanticizes the projector as a Cinema Paradiso icon.

*Thinking:* The image must carry the stopped-but-still-running feeling. The literal read — a projector in a booth — would miss it. The move is to make the machine feel *on* while giving it nothing to do: no reel threaded, no window to a theater, no beam — just the lamp contained inside its own housing, glowing for no one.

*Brief:*

Extreme close-up of a projection booth interior — projector housing, lamp,
film gate, two closed canisters on the shelf. Nothing loaded. Booth sealed;
no window to a theater. The lamp amber is a small contained glow at the
housing aperture, not a beam, not a room wash. The machine is on. There is
nothing to play. Accent: archival-tape amber (#C4873A).

The same brief across three of the nine presets

Documentary — observed, photographic, magazine-feature register:

Documentary preset output

Conceptual-illustration — painterly, metaphor-forward, essay register:

Conceptual-illustration preset output

Product-render — 3D render, architectural, product-marketing register:

Product-render preset output

The brief never changed. The aesthetic did. That's the skill.


What this skill is not

This is not a tool for decorative images. It is not a tool for literal illustration. It is not a faster way to get stock photography.

If the brief is "generate an image of an AI robot for our AI article," push back. That's the wrong brief. The right brief is: what should a reader *feel* before they start reading? Start there.

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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