KrillinAI CLI

Name: KrillinAI CLI
Author: krillinai

By krillinai· krillinai/OpenCreator· 0

Build and run KrillinAI commands for media processing and rendering.

Installation

1
Make sure Claude is on your device and in your terminal.
Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.
One-time setup
```
npm i -g @anthropic-ai/claude-code
```
Already have it? Skip ahead.

Paste into Claude Code or into your terminal.

Install

git clone ht•••••••••••••••••••••••••••••••••••••••••• ••••••••••••••••••••••••••• •• ••••• •• •••••••••••••••••••••••••••••••••••••••• •• •• •• •••••••••••••••••••••••••••••••••••••••••••••••••• •••••••••••••••••••••••••••••••••••••••••

This copies the whole skill folder into ~/.claude/skills/krillinai-cli-krillinai/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

Faster alternative (instruction-only skills)

Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

Quick install (SKILL.md only)

mkdir -p ~/.••••••••••••••••••••••••••••••••••••• •• •••• ••••• •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• •• •••••••••••••••••••••••••••••••••••••••••••••••••

Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.
Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Use when an agent needs to build or operate the embedded KrillinAI CLI, choose a supported command, or interpret its JSON, manifest, subtitle, dubbing, render, cover, speech, and voice outputs.

What this skill does

KrillinAI CLI

Use this as the top-level routing skill for KrillinAI command-line work.

Build And Locate The Binary

Build both KrillinAI binaries through the repository script:

pnpm krillinai:build

For the current machine, locate the CLI without assuming a platform or architecture:

TARGET="$(node -p "process.platform + '-' + process.arch")"
SUFFIX="$(node -p "process.platform === 'win32' ? '.exe' : ''")"
KRILLINAI_CLI="$PWD/.runtime/build/krillinai/$TARGET/bin/krillinai-cli$SUFFIX"
test -f "$KRILLINAI_CLI"

The CLI loads config/config.toml relative to its process working directory. For real runs from a source checkout, use runtime/krillinai as the process working directory and create its ignored config/config.toml from config/config-example.toml without overwriting an existing file. A release archive should be run from its unpacked package root.

For build layout, configuration, JSON, manifest, output, and error details, read:

skills/krillinai-cli/references/cli-contract.md

Choose The Command

User intent	Command / skill
Generate source, target, bilingual, and short vertical subtitles	`subtitle`; use `krillinai-subtitle`
Generate target-language dubbing from subtitles	`tts`; use `krillinai-tts`
Create landscape videos	`render-horizontal`; use `krillinai-render-horizontal`
Create portrait/short-form videos	`render-vertical`; use `krillinai-render-vertical`
Generate a cover from a complete image prompt	`cover`; use `krillinai-cover`
Generate speech from plain text	`speech`
List provider voice codes for Aliyun, OpenAI, or MiniMax	`voices`
Validate a requested multi-stage output plan	`pipeline --dry-run`; use `krillinai-pipeline`

pipeline only validates plans in dry-run mode; non-dry-run execution returns unsupported_command. status is reserved and unsupported.

Operating Rules For Agents

Use a dedicated --workdir; do not scatter outputs in the repo root.
Use --dry-run for command-shape validation before external calls.
Parse stdout as JSON lines. The terminal response is the object containing ok; OpenCreator mode may emit progress frames first.
Treat krillinai_manifest.json and actual output files as the source of truth after a real stage.
Reuse manifest outputs for later stages instead of guessing filenames.
If a command fails, classify by error.kind: usage, retryable, dependency, or internal.
Avoid rerunning expensive stages if the manifest already has valid upstream outputs.
Do not claim that cover consumed a reference image: the current CLI accepts a complete text prompt and size only.
Do not request an Edge TTS voice catalog: voices currently supports aliyun, openai, and minimax.

Minimal Workflow

REPO_ROOT="$PWD"
WORKDIR="$REPO_ROOT/tasks/demo"
mkdir -p "$WORKDIR"

(cd "$REPO_ROOT/runtime/krillinai" && "$KRILLINAI_CLI" subtitle \
  "https://www.youtube.com/watch?v=VIDEO_ID" \
  --origin-lang en \
  --target-lang zh_cn \
  --workdir "$WORKDIR" \
  --caption-source any \
  --prepare-video)

(cd "$REPO_ROOT/runtime/krillinai" && "$KRILLINAI_CLI" render-vertical \
  --workdir "$WORKDIR")

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