Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AgenticAIPlan/AgenticAISkills --skill ernie-image-gengit clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agenticaiplan/agenticaiskills/ernie-image-gen)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/ernie-image-gen"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/ernie-image-gen/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/ernie-image-gen"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/ernie-image-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.01943 |
| Opus 5 | $0.00038 | $0.00971 |
| Sonnet 5 | $0.00015 | $0.00389 |
| Haiku 4.5 | $0.00008 | $0.00194 |
Grade A, and why
ernie-image-gen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ERNIE Image Gen
使用 ERNIE Image 做文生图,默认走服务调用模式,并支持切换到兼容原生 /generate 接口的模式。这个 skill 适合:
- 需要通过配置切换不同 ERNIE Image 服务地址
- 需要保留
model_dir/weight_tar_path等部署上下文,但不希望写死本机路径 - 需要中文优先、多语言混合、长文本、多区域文本渲染
- 需要把生成图片和元数据稳定落盘到当前项目或当前任务目录
默认逻辑:云端优先,本地显式触发
这个 skill 的默认行为是:
- 优先采用云端模型服务
- 默认优先找云端配置
- 默认优先使用
assets/cloud-config.portable.cn.yaml - 默认优先走
openai_compatible
- 如果云端配置还没完成
- 不要直接假设本地模型
- 先引导使用者补齐最少配置:
base_url、auth_token_env、mode - 配完后先做
health_check.py,再生成
- 只有在用户明确说明要用本地模型时
- 才切到本地配置路径
- 才使用本地权重 / 本地部署上下文
- 才优先参考
assets/local-config.portable.cn.yaml
使用者先配置这几项
无论是在另一台电脑、另一个项目,还是分享给别人用,优先检查这 5 项:
base_url- 改成你自己的 ERNIE Image 服务地址
auth_token_env- 填“环境变量名”,不是 API Key 本身
- 例如:
ERNIE_IMAGE_API_KEY
mode- OpenAI 兼容接口用
openai_compatible - 原生接口用
native_generate
- OpenAI 兼容接口用
output.artifact_dir- 推荐保留
${ERNIE_IMAGE_ARTIFACT_DIR:-./achievement} - 不写死本机绝对路径
- 推荐保留
weight_tar_path- 如果只是调远程服务,可以留空
- 只有在你要保留本地部署上下文时才需要填
推荐直接从这两个模板开始:
- 通用英文模板:
assets/cloud-config.portable.yaml - 通用中文模板:
assets/cloud-config.portable.cn.yaml - 本地模型中文模板:
assets/local-config.portable.cn.yaml
如果你只是普通云端调用,最常用的动作其实只有两步:
export ERNIE_IMAGE_API_KEY='你的key'
python3 scripts/generate_image.py --config assets/cloud-config.portable.cn.yaml --prompt '一只可爱的橘猫表情包'
Quick Start
A. 默认:云端服务调用
- 优先复制可移植云端模板,而不是项目私有模板:
assets/cloud-config.portable.cn.yaml- 或
assets/cloud-config.portable.yaml
- 按需修改:
mode:openai_compatible或native_generatebase_urlauth_token_envmodel_dir(通常不用改)weight_tar_path(可留空,或用环境变量占位)- 输出目录
output.artifact_dir(推荐相对路径或环境变量)
- 先做健康检查:
python3 scripts/health_check.py \
--config assets/cloud-config.portable.cn.yaml
- 生成图片:
python3 scripts/generate_image.py \
--config assets/cloud-config.portable.cn.yaml \
--prompt "一只戴宇航员头盔的橘猫,电影感打光,超高细节"
B. 仅当用户明确要求:本地模型调用
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 411 B
- assets/cloud-config.portable.cn.yaml 3.0 KB
- assets/cloud-config.portable.yaml 843 B
- assets/ernie-image-gen.example.yaml 532 B
- assets/local-config.portable.cn.yaml 1.7 KB
- references/local-deploy.md 2.3 KB
- references/portable-usage.md 3.2 KB
- references/prompting.md 2.7 KB
- references/service-config-and-api.md 3.2 KB
- scripts/__init__.py 40 B runs code
- scripts/common.py 17 KB runs code
- scripts/generate_image.py 1.7 KB runs code
- scripts/health_check.py 534 B runs code
- scripts/validate_config.py 483 B runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 238 lines · 76 tokens per session scan A fada7194d3ad
ernie-image-gen is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 76 tokens to every session and 1,943 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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