用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/MarcosCamara01/ecommerce-template --skill ai-cli命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then guards against regression. Use when asked to make a route's navigation instant (its static shell commits immediately), fix a route whose static shell isn't prerendered/served/prefetched, grow a route's static shell or fix its slow first paint, diagnose which Suspense boundary keeps a route out of its static shell, or write the instant() e2e guard for one. Requires Next.js 16.3+ with cacheComponents; directs an upgrade if older.
Stage changed files and produce a conventional commit message for approval. Use after completing any unit of work — bug fix, refactor, or a ticket closed by /implement.
Local drop-in API emulator for Vercel, GitHub, Google, Slack, Apple, Microsoft, AWS, Linear, and other developer APIs. Use when the user needs to start emulated services, configure seed data, write tests against local APIs, set up CI without network access, or work with the emulate CLI or programmatic API. Triggers include "start the emulator", "emulate services", "mock API locally", "create emulator config", "test against local API", "npx emulate", or any task requiring local service emulation.
基于 SOC 职业分类
正在显示 SKILL.md
| name | ai-cli |
| description | Generate text, images, video, and audio from the terminal using AI models. |
Generate text, images, video, and audio from the terminal using AI models.
Use when you need to:
Requires AI_GATEWAY_API_KEY or a provider-specific key (e.g. OPENAI_API_KEY) in the environment.
ai text "explain this code" # generate text
ai image "a sunset over mountains" # generate an image
ai video "a spinning triangle" # generate a video
ai audio speak "hello" # generate speech
ai audio transcribe recording.mp3 # transcribe audio
ai models --type audio # list speech and transcription models
-m, --model <id> Model ID (provider/name or short name), comma-separated for multi-model
-o, --output <path> Output file or directory
-n, --count <n> Number of generations per model
-q, --quiet Suppress progress output
--json Output structured metadata as JSON (paths, timing, success/failure)
Chain commands for agent workflows:
# Pipe content in for summarization
cat file.txt | ai text "summarize this"
git diff | ai text "write a commit message"
# Image-to-video pipeline
ai image "a dragon" | ai video "animate this"
# Image editing via stdin
cat photo.png | ai image "make it a watercolor"
# Audio workflows
echo "Ship the changelog" | ai audio speak -o changelog.mp3
cat recording.mp3 | ai audio transcribe -o transcript.txt
Use --json to get machine-readable results:
ai image "a sunset" --json
Returns:
{
"elapsed_ms": 3420,
"count": 1,
"results": [
{
"index": 1,
"model": "openai/gpt-image-2",
"elapsed_ms": 3420,
"success": true,
"file": "/path/to/resp_abc123.png"
}
]
}
ai image "a sunset" -m "openai/gpt-image-1,bfl/flux-2-pro,xai/grok-imagine-image"
-o <dir>: saves inside directory with auto-generated namesWhen the CLI chooses a filename, it uses a response ID when available and falls back to a random 8-character ID, such as resp_abc123.png or 7f3a9c1d.mp3.
Important for agents: Always use -o to save to a file when generating images, video, or speech audio. Without -o in a non-TTY context, raw binary data is written to stdout, which wastes context and is not useful for agents. Use -o output.png, -o speech.mp3, or an output directory and read the file path from --json output instead.
0 — success1 — all generations failed2 — partial failure (some succeeded)