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 full-aigc-skills/jimeng-skills --skill jimeng-cli-text2imagegit clone --depth 1 https://github.com/full-aigc-skills/jimeng-skillsWrote 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/full-aigc-skills/jimeng-skills/jimeng-cli-text2image)<a href="https://agentmods.dev/skills/full-aigc-skills/jimeng-skills/jimeng-cli-text2image"><img src="https://agentmods.dev/badge/skills/full-aigc-skills/jimeng-skills/jimeng-cli-text2image/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/full-aigc-skills/jimeng-skills/jimeng-cli-text2image"><img src="https://agentmods.dev/badge/skills/full-aigc-skills/jimeng-skills/jimeng-cli-text2image.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 | $0.00067 | $0.00941 |
| Opus 5 | $0.00034 | $0.00470 |
| Sonnet 5 | $0.00013 | $0.00188 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
jimeng-cli-text2image 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.
What it actually says
即梦 CLI 文生图
执行前先运行 dreamina text2image -h。本技能记录 v1.4.14 稳定工作流;实际 help 始终是参数事实源。
When to use and boundary
用于已经进入 CLI 执行、轮询或故障诊断阶段的文生图任务。不该用于图生图、视频生成或单纯的提示词创作;这些场景分别加载对应的 jimeng-cli-* 或 jimeng-prompt-* 技能。
必须遵守
- 每次提交显式传
--resolution_type=1k|2k|4k。 --width与--height必须成对出现、为正整数,并与--ratio互斥。- 模型 token 使用
5.0Pro,不要写成人类可读名称5.0 Pro。 generate_num范围为 1–10。- 提交前说明会消耗积分;优先
--poll=0获取submit_id。
模型与分辨率矩阵、宽高像素限制见
dreamina-cli skill 的 references/dreamina-cli-v1.4.14-contract.md。
如未安装,请先 npx skills add full-aigc-skills/jimeng-skills --skill dreamina-cli。
标准执行
dreamina user_credit
dreamina text2image \
--prompt="一只橘猫坐在窗边,柔和晨光,浅景深" \
--ratio=1:1 \
--model_version=5.0 \
--resolution_type=2k \
--poll=0
自定义尺寸时省略 ratio:
dreamina text2image \
--prompt="竖版产品海报,留出标题区域" \
--model_version=5.0 \
--resolution_type=2k \
--width=1536 \
--height=2048 \
--poll=0
异步闭环
Step 1:验证
运行 dreamina text2image -h,校验模型、分辨率、ratio 或自定义尺寸组合。
Step 2:提交
检查积分、说明消费影响、提交并保存 submit_id。
Step 3:终态闭环
querying 仅表示已受理;继续 query_result,直到 success 或 fail。失败时报告
fail_reason;需要文件时增加 --download_dir=<absolute-path>。
Gotchas
- 分辨率遗漏:v1.4.14 会拒绝未传
resolution_type的请求。 - 宽高冲突:自定义 width/height 不能与 ratio 同时出现。
- 展示名误作 token:
5.0 Pro必须转换为5.0Pro。 - 受理误作成功:
querying不是成功终态。 - 积分消耗:真实提交前必须让用户知道会消费积分。
References
dreamina-cliskill 的 v1.4.14 参数契约(如未安装:npx skills add full-aigc-skills/jimeng-skills --skill dreamina-cli)- 参数参考
- 模型选择
- 工作流模式
- 示例
What ships with it
8 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.
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 · 81 lines · 67 tokens per session scan A 28077ed4f787
jimeng-cli-text2image is a skill published in the GitHub repository full-aigc-skills/jimeng-skills (3 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 67 tokens to every session and 941 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
general-video
Author or edit a custom HyperFrames composition when no specialized workflow fits, or when BRIEF.md sets flow: companion. Use for longer or multi-scene pieces, brand and sizzle reels, montages, static loops, static title cards, footage remixes, and freeform builds. Use motion-graphics instead for a short unnarrated…
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
chengfeng-check-updates
An environment manager for a video-editing system. It checks whether its skills and runtime—the software needed to run them—are installed and compatible.
diagnostic-stem-delivery
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.