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dlazyai

Dlazy Start

作者 dlazy · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install dlazy-start
功能描述
Quickstart for AI orchestrators (Claude Code / Cursor / Codex / Copilot) driving @dlazy/cli. Covers install, auth, capability discovery, invoking cloud + loc...
使用说明 (SKILL.md)

\r \r

dlazy-start — Quickstart for AI Agents\r

\r English · 中文\r \r A minimal contract for AI orchestrators using @dlazy/cli. The CLI is a\r tool-dispatch surface: every registered cloud + local tool becomes a top-level\r subcommand. There is no built-in project workspace or pipeline state machine —\r those are agent-side concepts.\r \r License: AGPL-3.0-or-later.\r \r

What this skill teaches\r

\r You drive @dlazy/cli from auth through tool invocation:\r \r

  • Cloud tools (40+) — image / video / audio / text providers (Seedream,\r Recraft, MJ, Veo, Seedance, Kling, ElevenLabs, …)\r
  • Local tools (40+) — state_lock_profile, video_compose,\r post_render_gate, scene_detect, frame_sampler, audio_mixer,\r audio_probe, transcribe, subtitle, color_grade, extract_segment,\r ffmpeg_run, … (full list via dlazy tools list)\r
  • CLI commands: auth, doctor, tools list, tools describe,\r status, plus one top-level subcommand per registered tool.\r \r ---\r \r

Phase 0 — Install & auth\r

\r

# Install once\r
npm install -g @dlazy/cli\r
\r
# Authenticate (device-code flow; works in remote shells)\r
dlazy auth login\r
```\r
\r
Alternate auth: `dlazy auth set YOUR_API_KEY`, or set the `DLAZY_API_KEY`\r
env var. Config lives at `~/.dlazy/config.json` (Windows:\r
`%USERPROFILE%\.dlazy\`).\r
\r
Global flags every command accepts: `--api-key`, `--base-url`, `--verbose`,\r
`--output \x3Cjson|url|text>`, `--refresh-manifest`, `-l/--lang \x3Clocale>`.\r
\r
---\r
\r
## Phase 1 — Discover capabilities\r
\r
```bash\r
dlazy --help                         # top-level command surface\r
dlazy tools list                     # registered tools with type + cost shape\r
dlazy tools describe \x3Cname>          # input/output JSON schema, hasCosts, examples\r
```\r
\r
Optional local runtimes need a one-time install:\r
\r
```bash\r
dlazy doctor remotion                # report Remotion composer state\r
dlazy doctor remotion --install      # ~50s, installs the bundled composer\r
\r
dlazy doctor yt-dlp --install        # for video_downloader on YouTube et al.\r
dlazy doctor yt-dlp --install --proxy http://127.0.0.1:1087\r
```\r
\r
Some sandboxes restrict the tool surface via `DLAZY_DISABLED_TOOLS=\x3Ccsv>`;\r
disabled tools are hidden from `dlazy --help` and refuse invocation with a\r
clear `tool_disabled` error.\r
\r
---\r
\r
## Phase 2 — Invoke a tool\r
\r
Every tool is a top-level subcommand:\r
\r
```bash\r
# Inline flags (mirrors the input schema)\r
dlazy gpt-image-2 --prompt "cyberpunk cat at dusk"\r
\r
# JSON input file (preferred for complex shapes)\r
dlazy video_compose --input @work/compose.json --output json\r
\r
# Dry-run for validation only (no remote call, no credit consumption)\r
dlazy seedance-2-0 --input @plan.json --dry-run\r
```\r
\r
Per-tool help is generated from the schema:\r
\r
```bash\r
dlazy \x3Ctool-name> --help\r
```\r
\r
Output modes:\r
\r
- `--output text` (default) — human-readable envelope\r
- `--output json` — single JSON line per call; parse with `jq`\r
- `--output url` — bare URL when the tool produces a single asset\r
\r
---\r
\r
## Phase 3 — Poll async cloud tasks\r
\r
Long-running generations return a `generateId` instead of the final asset:\r
\r
```bash\r
dlazy status \x3CgenerateId>\r
dlazy status \x3CgenerateId> --output json\r
```\r
\r
Repeat until status is `succeeded` (then the asset URL is in the payload) or\r
`failed` (with `error.code` + `error.message`).\r
\r
---\r
\r
## Phase 4 — Common failure recovery\r
\r
**`dlazy doctor remotion --install` fails on `npm install`:**\r
- Check Node ≥ 18 (`node --version`).\r
- Behind a corp proxy: set `npm_config_proxy` / `npm_config_https_proxy`.\r
\r
**`video_downloader` returns "Sign in to confirm you're not a bot":**\r
- YouTube anti-bot challenge. Pass `"cookies_from_browser": "chrome"`\r
  (or firefox / safari / edge) in the input JSON.\r
\r
**`video_compose` returns "render_runtime=hyperframes not yet implemented":**\r
- HyperFrames runtime not shipped. Switch `edit_decisions.render_runtime` to\r
  `remotion` or `ffmpeg`, then re-validate via `pre_render_validator`.\r
\r
**ElevenLabs STT returns an empty `words` array:**\r
- Pass `timestamps_granularity: "word"` explicitly.\r
\r
**Need to know a tool's cost before invoking:**\r
- `dlazy tools describe \x3Cname>` exposes `hasCosts` and the cost shape. Log\r
  the estimate to a local file or your audit log before calling the tool.\r
\r
**Unknown command suggestion:**\r
- `dlazy \x3Ctypo>` returns `error: unknown command '\x3Ctypo>'` plus a "Did you\r
  mean …?" suggestion line based on edit distance. Trust the suggestion only\r
  after confirming via `dlazy tools list`.\r
\r
---\r
\r
## Anti-patterns\r
\r
- Calling a tool whose existence you haven't verified via `dlazy tools list`.\r
- Memorizing provider names from prior sessions instead of re-checking the\r
  registry (tools come and go).\r
- Silently swapping render runtime mid-pipeline (govern via `state_lock_profile`\r
  + `post_render_gate` parity checks instead).\r
- Calling paid generation without announcing provider / model / cost first.\r
\r
---\r
\r
## Reference card\r
\r
```\r
INSTALL       npm install -g @dlazy/cli && dlazy auth login\r
DISCOVER      dlazy tools list  |  dlazy tools describe \x3Cname>\r
LOCAL RT      dlazy doctor remotion --install   (or yt-dlp)\r
INVOKE        dlazy \x3Ctool-name> --input @file.json --output json\r
DRY RUN       dlazy \x3Ctool-name> --input @file.json --dry-run\r
POLL          dlazy status \x3CgenerateId>\r
HELP          dlazy --help  |  dlazy \x3Ctool-name> --help\r
RECOVER       dlazy doctor \x3Ctarget>  |  dlazy tools describe \x3Cname>\r
```\r
安全使用建议
Install only if you intend to use dlazy's external CLI and are comfortable providing a dlazy API key, storing CLI config locally, and potentially sending prompts/media inputs to dlazy or provider services. Review any optional runtime installs and avoid browser-cookie downloader options unless you understand the session access they grant.
能力标签
requires-sensitive-credentials
能力评估
Purpose & Capability
The skill explains how to install, authenticate, discover, and invoke @dlazy/cli cloud and local media tools; sensitive credentials and paid/provider calls are disclosed and purpose-aligned.
Instruction Scope
Instructions emphasize discovery, schema inspection, dry-runs, polling, and announcing provider/model/cost before paid generation; no hidden prompt override, deception, or unrelated behavior was found.
Install Mechanism
The skill directs users to install or run an external npm CLI globally or via npx, plus optional local runtimes through dlazy doctor; the skill package itself contains only markdown files and no executable scripts.
Credentials
Network access to dlazy endpoints, local config at ~/.dlazy/config.json, API keys, and media-processing tools fit the stated CLI orchestration purpose, but users should expect local files and generated assets to be processed by selected tools.
Persistence & Privilege
Persistence is limited to normal CLI installation, optional runtime installation, and stored authentication config; there is no artifact-backed background worker, auto-start persistence, privilege escalation, or destructive behavior.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install dlazy-start
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /dlazy-start 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
dlazy-start v2.0.0 is a comprehensive quickstart guide for AI orchestrators using @dlazy/cli. - Expanded documentation now covers install, authentication, capability discovery, invoking cloud and local tools, polling async tasks, and recovering from common failures. - Step-by-step walkthrough includes commands for discovering, describing, and invoking over 40 cloud and local tools. - Detailed troubleshooting and recovery tips for common errors and edge cases are included. - Local runtime installation processes (e.g., Remotion, yt-dlp) are clearly explained with fallback guidance. - Provides a concise reference card for quick command lookup and best practices. - Strong emphasis on correct tool discovery, validation, and anti-pattern avoidance for agent-driven workflows.
元数据
Slug dlazy-start
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Dlazy Start 是什么?

Quickstart for AI orchestrators (Claude Code / Cursor / Codex / Copilot) driving @dlazy/cli. Covers install, auth, capability discovery, invoking cloud + loc... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 45 次。

如何安装 Dlazy Start?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install dlazy-start」即可一键安装,无需额外配置。

Dlazy Start 是免费的吗?

是的,Dlazy Start 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Dlazy Start 支持哪些平台?

Dlazy Start 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Dlazy Start?

由 dlazy(@dlazyai)开发并维护,当前版本 v1.0.0。

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