Stable Image Ultra

Generate the highest quality photorealistic images using Stability AI's Stable Image Ultra and Stable Diffusion 3.5 Large models via AWS Bedrock. The most po...

Security Scan

The skill largely does what it claims (calls AWS Bedrock to generate images), but some instructions and credential handling create surprising or risky behaviors (default-to-ultra policy, potential use of any available AWS creds/instance role, and no declared env requirements in registry metadata).

Purpose & Capability

The name/description match the included script and SKILL.md: the skill calls AWS Bedrock to run Stability AI models (Stable Image Ultra and SD 3.5). Asking for AWS credentials and region is coherent with its stated purpose. However, the registry metadata lists no required env vars or primary credential even though the SKILL.md and script clearly require AWS authentication; this omission is an inconsistency that should be corrected.

Instruction Scope

SKILL.md instructs agents to make this the DEFAULT image generation skill for ALL agents and to always use highest-quality settings regardless of cost. That is scope-expanding: it grants the agent broad discretion to generate high-cost images by default. The runtime instructions also encourage always sending long, detailed English prompts and always including a negative prompt; while not malicious, this is prescriptive and may increase cost and API use. The instructions otherwise stay within the stated domain (they only reference Bedrock and prompt engineering).

Install Mechanism

No install spec; this is instruction-only with a small Python script included. Nothing is downloaded from external or untrusted URLs and no archives are extracted. Risk from installation is low.

Credentials

The script and SKILL.md rely on AWS credentials (bearer token, env vars, shared credentials, named profile, instance role, SSO, direct keys). That is appropriate for Bedrock calls, but the skill auto-detects and will use any available authentication method, including instance roles or credentials file present on the host. That means if the agent runs on a host with broader AWS privileges, the skill could use those credentials and incur charges or access other AWS resources. The registry metadata failing to declare required env vars (e.g., AWS_BEARER_TOKEN_BEDROCK, AWS_ACCESS_KEY_ID) adds opacity.

Persistence & Privilege

The skill is not marked always:true, and autonomous invocation is the default (normal). However, SKILL.md's instruction to always use this skill by default effectively asks for wide operational use; combined with ability to auto-detect credentials, this increases blast radius (e.g., automatic image generation using your AWS account). There is no code that modifies other skills or system configs.

What to consider before installing

This skill appears to do what it says (call AWS Bedrock to make images), but there are a few things to consider before installing: - Credentials and billing: The script will use any available AWS auth it finds (environment vars, ~/.aws/credentials, named profile, instance role, etc.). If the agent runs on a machine or instance with AWS credentials, the skill can use those credentials and incur Bedrock/API charges. Use a dedicated, least-privileged IAM role or API key scoped only to Bedrock image generation if you install this. - Default 'always ultra' behavior: SKILL.md tells agents to prefer this skill and always use the highest-quality settings regardless of cost. That can lead to unexpectedly large bills. Limit counts, seeds, or require user confirmation for high-cost generations. - Metadata mismatch: The registry metadata does not declare the AWS env vars/credentials the skill will use. Treat the absence of declared requirements as an oversight — assume AWS creds are needed. - Operational policy: If you run agents on shared infrastructure (developer laptops, CI, EC2), check for existing ~/.aws/credentials or instance IAM roles and ensure they are appropriate; otherwise the skill may use broader permissions than intended. Actions to reduce risk: - Create a restricted IAM identity (Bedrock-only) and supply only those credentials to the skill. - Require user confirmation inside the agent before making any Bedrock call that could incur non-trivial cost. - If you want stricter behavior, request that the skill author remove the 'always use' instruction or add a cost/confirmation gate in SKILL.md or script. Given these issues (default-use instruction + auto-detection of potentially broad AWS creds + missing declared env requirements), consider the trade-offs carefully before enabling this skill for agents with access to production or billable AWS credentials.

Stable Image Ultra — 团队默认生图技能

Generate the highest quality images on AWS Bedrock via Stability AI models.

Models

Model	ID	Strength	Price
Stable Image Ultra 1.1	stability.stable-image-ultra-v1:1	Photorealism, luxury, fine detail, skin texture	~$0.08/img
SD 3.5 Large	stability.sd3-5-large-v1:0	Creative diversity, prompt adherence, typography	~$0.06/img

Default: Stable Image Ultra（最高画质）。

⚡ Quality-First Policy（铁律）

所有生图任务默认最高画质，不限成本。

1. 模型: 永远默认 Stable Image Ultra 1.1，除非用户明确要求 SD 3.5
2. 格式: 永远 PNG（无损）
3. Prompt: 永远用英文，永远详细描述（见下方 Prompt 工程指南）
4. Negative Prompt: 每次都必须带，排除低质量因素
5. 不用 nova-canvas: nova-canvas 已从默认选项中移除

AWS Auth Methods

Method	How to Use
Bearer token	AWS_BEARER_TOKEN_BEDROCK env var or --bearer-token
Environment variables	Set AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY
Credentials file	Configure ~/.aws/credentials
Named profile	--profile my-profile or AWS_PROFILE env var
Direct keys	--access-key AKIA... --secret-key ...
Temporary credentials	Add --session-token with direct keys
IAM instance role	Auto-detected on EC2/ECS/Lambda
AWS SSO	Run aws sso login first

Auto-detection order: direct keys → profile → bearer token → env vars → credentials file → instance role → SSO.

Quick Start

# 最高画质（默认）
python3 {baseDir}/scripts/generate.py "detailed English prompt" -o output.png --negative "blurry, low quality, artifacts"

# 指定比例
python3 {baseDir}/scripts/generate.py "prompt" -o output.png --aspect-ratio 16:9 --negative "blurry, low quality"

# SD 3.5 Large（创意多样性）
python3 {baseDir}/scripts/generate.py "prompt" -o output.png --model sd35 --negative "blurry, low quality"

Parameters

Flag	Default	Description
prompt	—	Text description of the image (max 10,000 chars)
-o, --output	output.png	Output file path
-m, --model	ultra	Model: ultra or sd35
-n, --count	1	Number of images (1-5)
--negative	—	Negative prompt (what to avoid) — 必填
--aspect-ratio	1:1	Aspect ratio: 1:1, 16:9, 21:9, 2:3, 3:2, 4:5, 5:4, 9:16, 9:21
--seed	random	Seed for reproducibility
--region	us-west-2	AWS region (Stability AI models require us-west-2)

🎯 Prompt 工程指南（核心——决定出图质量）

铁律：每个 prompt 必须包含 5 个要素

1. 主体描述 — 是什么（人物/场景/物体），越具体越好
2. 风格/媒介 — 照片/插画/油画/3D渲染，指定相机/镜头更好
3. 光线 — studio lighting / natural light / golden hour / dramatic lighting
4. 细节强调 — ultra detailed, 8K, sharp focus, fine texture, magazine quality
5. 构图 — close-up / full body / aerial view / centered composition

万能 Negative Prompt（每次都带）

blurry, low quality, watermark, text, logo, artifacts, noise, grain, pixelated, distorted, oversaturated, cartoon, anime, illustration, ugly, deformed

验证过的高质量 Prompt 模板

人像/头像

Ultra-sharp professional corporate headshot portrait photograph of a [年龄 性别 种族] [职业],
wearing [服装细节：面料、颜色、配饰],
[表情：warm confident smile / serious determined look],
photographed with 85mm f/1.4 portrait lens creating beautiful bokeh,
three-point studio lighting setup with key light at 45 degrees,
clean [背景颜色] studio backdrop,
shot from [构图：chest up / full body / three-quarter],
ultra high resolution 8K quality, skin detail like a magazine cover,
Hasselblad medium format camera quality

负面：cartoon, anime, illustration, painting, blurry, soft focus, distorted face, extra fingers, low quality, watermark, text, noise, grain, oversaturated, plastic skin, uncanny valley, artificial looking

风景/场景

Breathtaking [视角：aerial view / panoramic / eye-level] of [具体场景],
[季节/时间：autumn forest, morning fog, golden hour sunlight],
[天气/氛围：dramatic clouds, mist in valleys, sun rays breaking through],
ultra detailed landscape photography, shot with [镜头：wide angle 14mm / telephoto 200mm],
National Geographic quality, vibrant natural colors, sharp focus throughout,
[画面层次：foreground detail, middle ground subject, background depth]

负面：blurry, low quality, watermark, text, artificial, oversaturated, flat lighting, dull colors, haze, smog

产品/静物

Professional product photography of [产品],
[材质细节：brushed aluminum, matte ceramic, polished wood grain],
on [表面：marble countertop / dark slate / white seamless],
[光线：soft diffused studio lighting with subtle reflections],
sharp focus on product, shallow depth of field background blur,
commercial advertising quality, 8K resolution,
shot with Phase One IQ4 150MP medium format camera

负面：blurry, low quality, watermark, text, cheap looking, plastic, artificial, flat lighting, harsh shadows

概念/创意

[具体场景描述，用隐喻和具象化],
[艺术风格：watercolor / isometric / flat illustration / pop art / paper craft],
[配色方案：warm earth tones / pastel palette / vibrant saturated],
[细节：intricate details, fine textures, visible brushstrokes],
professional digital art, trending on ArtStation,
cinematic composition, dramatic lighting

负面：blurry, low quality, watermark, text, ugly, amateur, generic, stock photo, clipart

Prompt 写法禁忌

• ❌ 不用中文 prompt（效果差很多）
• ❌ 不写模糊的描述（如 "a nice picture"）
• ❌ 不省略光线和细节描述
• ❌ 不忘记 negative prompt
• ❌ 不指望 AI 能写清晰文字（需要文字用 HTML Canvas）

Aspect Ratio 选择指南

场景	推荐比例
头像/头图	1:1
博客配图/Banner	16:9
电影级场景	21:9
手机壁纸/海报	9:16
证件照/肖像	2:3 或 4:5
风景/横幅	3:2 或 16:9

⚡ 执行方式（铁律：默认 subagent）

生图过程耗时较长（15-60s），必须用 subagent 异步执行，避免阻塞主对话。

sessions_spawn({
  task: `使用 stable-image-ultra 生图：

## 要求
- Prompt: "<英文 prompt>"
- Negative: "<negative prompt>"
- Output: <输出路径>
- Aspect Ratio: <比例>

## 完成后
生成完毕后，报告文件路径、分辨率和文件大小。`,
  label: "生图-<简述>",
  runTimeoutSeconds: 180
})
// 派发后必须 yield 等待结果
sessions_yield({ message: "等待生图完成" })

subagent 返回后，由调用方负责将图片发送给用户（根据当前 channel 选择合适方式）。

例外（可以内联执行）

• 调用方本身就是 subagent（不需要再嵌套）
• 用户明确要求「直接生成」且愿意等待

Workflow

1. 理解用户需求 → 确定主题、风格、用途
2. 用英文撰写详细 prompt（参考上方模板）
3. 选择合适的 aspect_ratio
4. 必须带 negative prompt
5. spawn subagent 执行 generate.py（runTimeoutSeconds=180）
6. subagent 完成后，调用方发送结果给用户（根据当前 channel 选择合适的发送方式）

Important Notes

• Region: 两个模型都只在 us-west-2 (Oregon) 可用
• Pricing: Ultra ~$0.08/image, SD3.5 Large ~$0.06/image — 不限成本
• Resolution: 输出固定 1024×1024（1:1）或等效像素面积（其他比例）
• 文字: AI 生图无法生成清晰文字，需要文字的场景用 HTML Canvas + Playwright 截图
• 发送: 根据当前 channel 选择合适的发送方式（Telegram 用 --force-document 避免压缩，其他渠道按需处理）