dreamina-cli

Dreamina CLI

⚠️ 停维护公告：旧版 Dreamina CLI（dreamina，v1.4.18）将于 2026 年 11 月 起停止维护。新任务请改用 Canvas 替代技能 dreamina-canvas-cli（安装：npx skills add full-aigc-skills/dreamina-skills --skill dreamina-canvas-cli）。本技能内容保留作历史契约参考。

Use this skill when you need Dreamina（即梦） image or video generation, login, session management, or task history work through dreamina.

即梦 is the Chinese product name of Dreamina. For a generic 即梦 request, select dreamina-canvas-cli; use this frozen skill only for an explicit classic-CLI request.

This skill is intentionally short. Detailed flags and supported values belong to the CLI itself, so always treat dreamina -h and dreamina <subcommand> -h as the primary reference.

Read references progressively:

• For installation, authentication, account checks, every public command family, Session CRUD, update, and log troubleshooting, read references/official-cli-install-to-use.md.
• For v1.4.18 model, resolution, duration, and ratio constraints, read references/dreamina-cli-v1.4.18-contract.md.

When to use and boundary

Use this umbrella skill from first-time installation through troubleshooting, or when login, sessions, task history, async follow-up, or command routing spans multiple modalities. Do not use it as a replacement for the four execution skills' mode-specific workflow or for prompt-only authoring.

What this tool is for

dreamina is the local CLI entrypoint for all currently exposed Dreamina（即梦） image and video generation workflows, plus the account/session operations around them.

Use it for:

• checking or reusing an existing Dreamina login session
• checking account credit
• managing sessions with dreamina session
• clearing the local OAuth login state with dreamina logout
• submitting image generation tasks
• submitting video generation tasks
• querying async task results and downloading result media
• reviewing saved task history

Default workflow

When using this CLI as an agent:

Step 1：验证环境

If dreamina is missing, read the install-to-use reference and obtain explicit authorization before installing or updating software. Otherwise start with dreamina version and dreamina -h, then run dreamina <subcommand> -h before real use.

Step 2：完成认证与路由

Reuse login unless the user requests a login-state change. Use user_credit as the post-login readiness check. Route generation to the matching execution skill.

Step 3：提交与终态闭环

Warn about credit consumption, distinguish help inspection from real submit, and follow every accepted task until success or fail.

Validation

• Validate the installed CLI help against the reviewed contract before changing model or resolution assumptions.
• Discover video ratio support at runtime with dreamina <subcommand> --help: four video commands expose --ratio, while multiframe2video infers it from the first image.
• Validate local files before upload and preserve every returned submit_id.
• Validate terminal status from query_result, not shell exit code alone.

Gotchas

1. Help drift: release notes are not a substitute for current subcommand help.
2. Double fact source: keep parameter matrices in the v1.4.18 contract reference.
3. Accepted versus successful: querying is not terminal success.
4. Paid action: warn before any real generation submit.
5. OAuth pause: always report whether login succeeded, was reused, or failed.
6. Troubleshooting order: capture the exact command, error, dreamina version, and relevant ~/.dreamina_cli/logs/ excerpt; redact secrets, update the CLI with authorization, then retry the same command once.

Login completion: mandatory user-visible confirmation

dreamina login / dreamina relogin prints OAuth Device Flow instructions and then waits for authorization. When the command finishes successfully, tell the user explicitly that login succeeded or the local OAuth state was reused.

• Do not wait for the user to ask “登录好了吗”.
• Do not stop after only sending the device code: keep the login command running, read stdout to the end, then confirm success/reuse/failure.
• Failure must still be reported with the concrete error and the next step.

Choosing the right command

At a high level:

• Use user_credit to check budget.
• Use session to create, list, search, rename, or delete sessions; all generator commands accept --session=<id> and 0 is the default session.
• Use query_result when you already have a submit_id; add --download_dir when you want the generated media saved locally.
• Use list_task to review recent saved tasks, especially when you want to filter by status or task type.
• Use text2image for prompt-only image generation, image2image for image-guided editing, and image_upscale for upscaling.
• Use text2video for prompt-only video generation.
• Use image2video when one main image is enough; if the user has multiple images for a coherent story, prefer multiframe2video.
• Use frames2video for first-and-last-frame driven video generation.
• Use multiframe2video for Dreamina's intelligent multi-frame flow: multiple images in, one coherent story video out.
• Use multimodal2video for Dreamina's flagship video mode when the task needs all-around references across images, video, and audio; it supports the seedance2.0 family. If the legacy name ref2video appears, trust dreamina -h for the current command surface.

For the exact flags and supported combinations, rely on each subcommand's -h.

Model selection rule

Do not hardcode model support from this skill.

If the user specifies a model, always check the relevant subcommand help before running it:

dreamina <subcommand> -h

Use the subcommand help to confirm:

• whether that command exposes model selection
• whether the requested model is supported on that command
• what other constraints apply to that model, such as duration, ratio, resolution, or whether the command supports model_version at all

Additional guidance:

• some commands do not expose model selection at all
• some models, especially the seedance2.0 family, can be capacity-constrained
• if the user cares more about speed than maximum quality, do not default to seedance2.0 unless they explicitly ask for it

How to judge submit acceptance and terminal success

Do not rely on shell exit code alone.

For async generation commands, submit_id plus gen_status=querying means only that the submission was accepted. Treat the generation as terminally successful only when gen_status=success. If gen_status=fail, inspect fail_reason and reply proactively.

Follow-up pattern for async tasks

After a submit returns querying:

1. Save the submit_id.
2. Use query_result --submit_id=<id> for follow-up.
3. Use list_task when you want to review saved tasks in bulk.
4. Continue until the task reaches success or fail.

If you are running a test sweep, keep results in a machine-readable format so you can query the returned submit_id values later.

Important user-facing rules

• Some generation commands are asynchronous; submit and query are separate steps.
• Some models may require a one-time authorization on Dreamina Web. If the CLI returns AigcComplianceConfirmationRequired, reply proactively: ask them to complete that web-side confirmation first, then retry.
• Do not assume that different commands support the same models, ratios, durations, or resolutions. Check each subcommand's -h before use.
• In v1.4.18, text2video and multimodal2video accept explicit --ratio; image2video and frames2video expose the flag but reject it with seedance2.5; multiframe2video has no ratio flag. Re-discover these rules at runtime instead of generalizing across commands.

Good agent behavior

• Relay OAuth Device Flow instructions exactly enough for the user to complete login.
• Always close the loop when the login command finishes with a user-visible confirmation.
• Prefer small, reviewable batches when running real generation tasks.
• Keep a record of the command, arguments, submit_id, and final status for every paid test you run.
• When the user cares about generation speed, do not default to the seedance2.0 family unless they explicitly ask for it or clearly prioritize output quality.
• If you are preparing a report, separate:
  • help-only inspection
  • submit-stage validation
  • later async result follow-up

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When to use（什么时候使用）

当用户需要 为当前请求选择并执行可验证、可恢复的专业工作流 时加载本技能。先从请求中提取目标、输入、约束、交付格式和验收标准；描述摘要为：Use when an agent needs to install, update, authenticate, troubleshoot, or operate Dreamina（即梦） CLI across account, session, image, video, task-query, and download workflows.。

Rules

• 先读后写：先确认当前状态与真实能力，再执行会改变外部状态的动作。
• 权限最小化：只使用完成当前步骤所需的文件、工具、账户与网络范围。
• 证据优先：运行结果、资源 ID、版本、哈希或测试输出缺失时，明确标记为 NOT_VERIFIED。
• 幂等优先：保留请求标识与阶段状态；结果不明确时先查询，不进行盲目重试。
• 隐私安全：日志、示例、回执和错误信息不得包含 token、cookie、密钥或个人敏感数据。

Workflow

Step 1：澄清意图

确认本技能是否匹配目标；若只是相邻需求，交给更精确的技能。

Step 2：执行预检

确认目标、输入、约束、可用工具、成功标准和失败边界；任一关键条件未知时停止在只读阶段。

Step 3：形成计划

列出将调用的工具、会改变的对象、成功标准以及失败后的安全退出方式。

Step 4：执行动作

按最小充分步骤执行，并在关键状态变化处记录证据；每个外部调用均保留可关联的状态或回执。

Step 5：验证交付

输出结果、验证证据、未完成项、风险和明确的下一步，并把事实、推断和未验证项分开陈述。

Validation checklist

• 技能触发条件与用户意图一致，没有把相邻任务误路由到本技能。
• 输入、目标对象、版本和输出位置均已明确，且没有使用猜测值替代必填值。
• 所有写入、付费、发布或不可逆动作都在用户授权范围内。
• 结果已用独立检查验证；仅有“命令成功”或“文件存在”不算完整验收。
• 输出包含实际证据、失败/跳过项、剩余风险和可执行的下一步。

Gotchas

1. 把计划当结果：文档或提示词不等于真实执行；必须标明实际运行层级。
2. 错误重试：超时或响应丢失可能已经产生远端状态，先查询再决定是否重试。
3. 隐式扩大范围：批量、全量、发布、覆盖和付费不是普通读写的自然延伸。
4. 版本漂移：引用外部资源时记录版本、tag 或提交；不要把可变分支当发布证据。
5. 证据过期：缓存、旧截图和历史测试不能证明当前环境；在交付前刷新关键证据。

不适用与边界

不超出用户给定范围；写入、付费、发布和不可逆动作需要明确授权。 如果请求需要别的技能，不复制其正文；按技能名称进行交接，并保留当前任务上下文。

Progressive disclosure

• 需要确定输入/输出、状态和授权点时，读取 references/workflow-contract.md。
• 需要交付前自检时，读取 references/validation-checklist.md。
• 遇到超时、部分成功或恢复场景时，读取 references/error-recovery.md。
• 首次运行、拒绝越权和失败恢复分别参考 examples/happy-path.md、examples/boundary-refusal.md、examples/failure-recovery.md。