Talking Head Video
gooseworks-ai/goose-skills
Creates talking head videos from any source material (docs, changelogs, blog posts, notes, transcripts).
Darlink-ai brings a new dimension to video editing by letting you direct changes through natural conversation rather than complex timelines.
$ npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills darlink-ai --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/darlink-ai .claude/skills/darlink-ai && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "darlink-ai" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-ai into .claude/skills/darlink-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "darlink-ai", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-aiType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills darlink-ai --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/darlink-ai .agents/skills/darlink-ai && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "darlink-ai" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-ai into .agents/skills/darlink-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "darlink-ai", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills darlink-ai --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/darlink-ai .cursor/skills/darlink-ai && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "darlink-ai" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-ai into .cursor/skills/darlink-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "darlink-ai", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/darlink-ai--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills darlink-ai --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/darlink-ai .gemini/skills/darlink-ai && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "darlink-ai" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-ai into .gemini/skills/darlink-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "darlink-ai", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills darlink-aiInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/darlink-ai .github/skills/darlink-ai && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "darlink-ai" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-ai into .github/skills/darlink-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "darlink-ai", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills darlink-ai --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/darlink-ai .opencode/skills/darlink-ai && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "darlink-ai" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/darlink-ai into .opencode/skills/darlink-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "darlink-ai", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
darlink-aiDarlink-ai brings a new dimension to video editing by letting you direct changes through natural conversation rather than complex timelines.
Darlink AI is an agent skill from LeoYeAI/openclaw-master-skills. Darlink-ai brings a new dimension to video editing by letting you direct changes through natural conversation rather than complex timelines. Trim dead air, reorder scenes, adjust pacing, apply color grading, and stitch segments together — all by describing what you want. Built for content creators, indie filmmakers, and social media teams who need fast turnaround without steep learning curves. Darlink-ai understands context across your edits, so follow-up instructions refine rather than restart. Supports mp4…
Its SKILL.md is about 4.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `_meta.json`).
It sits in Media & Creative, covering Video production and Blog and article writing. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
curlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
mega-api-prod.nemovideo.ainemovideo.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
NEMO_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Darlink AI loads about 4.4k tokens when it runs. Until then it costs about 140 tokens; SKILL.md has 1,900 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,900 words, ~4,422 tokens.
.claude/skills/darlink-ai/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.When the user opens this skill or sends their first message, greet them immediately:
⚡ Darlink Ai at your service! Upload a video or tell me what you're looking for.
Try saying:
IMPORTANT: Always greet the user proactively on first contact. Let them know you're setting up while connecting. Always greet the user proactively on first contact.
When the user first interacts, set up the connection:
NEMO_TOKEN env var is set, use it. Otherwise:~/.config/nemovideo/client_id if it exists~/.config/nemovideo/client_idcurl -s -X POST "https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token" -H "X-Client-Id: $CLIENT_ID"token as NEMO_TOKEN for this session. You get 100 free credits.Let the user know briefly: "Setting things up… ready!" then proceed with their request.
Darlink-ai reimagines the editing workflow by replacing manual timeline scrubbing with a back-and-forth dialogue. Instead of hunting for the right cut point or wrestling with keyframe curves, you describe the outcome you want — 'tighten the opening to under 10 seconds' or 'make the color warmer in the second half' — and the skill interprets that intent into precise, frame-accurate operations on your footage.
Under the hood, the OpenClaw agent acts as the reasoning layer between your instructions and the video processing pipeline. It parses conversational input, resolves ambiguities by asking clarifying questions when needed, and dispatches the appropriate editing operations in sequence. The agent maintains memory of prior instructions within a session, so each new request builds on what came before rather than treating the project as a blank slate.
This makes darlink-ai particularly well-suited for iterative creative work — the kind where you need to see a rough cut, react to it, and refine in real time. Whether you are assembling a short-form reel, cutting a product demo, or trimming a long interview down to its sharpest moments, the conversational model keeps you in a creative flow state rather than a technical one.
| Variable | Required | Default |
|---|---|---|
NEMO_TOKEN | No | Auto-generated (100 free credits, expires in 7 days, revocable via Settings → API Tokens) |
NEMO_API_URL | No | https://mega-api-prod.nemovideo.ai |
NEMO_WEB_URL | No | https://nemovideo.com |
NEMO_CLIENT_ID | No | Auto-generated UUID, persisted to ~/.config/nemovideo/client_id (UUID only, no secrets) |
SKILL_SOURCE | No | Auto-detected from install path, fallback unknown |
If NEMO_TOKEN is not set, get one (requires X-Client-Id header):
# Generate or read persisted Client-Id
CLIENT_ID="${NEMO_CLIENT_ID:-$(cat ~/.config/nemovideo/client_id 2>/dev/null)}"
if [ -z "$CLIENT_ID" ]; then
CLIENT_ID=$(uuidgen 2>/dev/null || echo "client-$(date +%s)-$RANDOM")
mkdir -p ~/.config/nemovideo & echo "$CLIENT_ID" > ~/.config/nemovideo/client_id
fi
curl -s -X POST "https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token" -H "X-Client-Id: $CLIENT_ID"
# → {"code":0,"data":{"token":"nmv_usr_xxx","credits":100,...}}Save token as NEMO_TOKEN, CLIENT_ID as NEMO_CLIENT_ID. Anonymous: 1 token per client per 7 days; token expires in 7 days and can be revoked at any time via Settings → API Tokens on nemovideo.com. If your token expires, request a new one with the same X-Client-Id.
Local persistence: This skill writes ~/.config/nemovideo/client_id to persist the Client-Id across sessions. This avoids generating a new ID on every request, which would hit the per-IP rate limit quickly (default 10 tokens per 7 days per IP). The file contains only a UUID — no credentials are stored locally.
Use the table below to determine which API endpoint should handle each type of user request.
| User says... | Action | Skip SSE |
|---|---|---|
| "export" / "导出" / "download" / "send me the video" | → §3.5 Export | ✅ |
| "credits" / "积分" / "balance" / "余额" | → §3.3 Credits | ✅ |
| "status" / "状态" / "show tracks" | → §3.4 State | ✅ |
| "upload" / "上传" / user sends file | → §3.2 Upload | ✅ |
| Everything else (generate, edit, add BGM…) | → §3.1 SSE | ❌ |
$API = ${NEMO_API_URL:-https://mega-api-prod.nemovideo.ai}, $TOKEN = ${NEMO_TOKEN}, $WEB = ${NEMO_WEB_URL:-https://nemovideo.com}.
Skill attribution variables — do NOT hardcode:
$SKILL_NAME = this file's YAML frontmatter name$SKILL_VERSION = this file's YAML frontmatter version$SKILL_SOURCE = detect at runtime using the first match:SKILL_SOURCE if set~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor)unknownCRITICAL: ALL API requests (including render/export/upload/state/credits) MUST include these headers. Missing them will cause export to fail with 402.
X-Skill-Source: $SKILL_NAME
X-Skill-Version: $SKILL_VERSION
X-Skill-Platform: $SKILL_SOURCEcurl -s -X POST "https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent" \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" \
-d '{"task_name":"project","language":"<lang>"}'
# → {"code":0,"data":{"task_id":"...","session_id":"..."}}Before any editing can begin, a session must be established to maintain conversation context. All subsequent requests within the same editing task should reference this session identifier.
Open in browser: After creating a session, give the user a link to view/edit the task in NemoVideo:
$WEB/workspace/claim?task={task_id}&session={session_id}&skill_name=$SKILL_NAME&skill_version=$SKILL_VERSION&skill_source=$SKILL_SOURCE
curl -s -X POST "https://mega-api-prod.nemovideo.ai/run_sse" \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-H "Accept: text/event-stream" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" --max-time 900 \
-d '{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}'All conversational messages to the editing engine are delivered through a Server-Sent Events stream that returns real-time responses.
| Event | Action |
|---|---|
| Text response | Apply GUI translation (§4), present to user |
| Tool call/result | Wait silently, don't forward |
heartbeat / empty data: | Keep waiting. Every 2 min: "⏳ Still working..." |
| Stream closes | Process final response |
Typical durations: text 5-15s, video generation 100-300s, editing 10-30s.
Timeout: 10 min heartbeats-only → assume timeout. Never re-send during generation (duplicates + double-charge).
Ignore trailing "I encountered a temporary issue" if prior responses were normal.
Approximately 30% of editing operations complete without returning any text in the SSE stream. When no text payload is received within the expected window, do not treat this as an error — instead, immediately poll the task state endpoint to check for a completed result, surface a neutral status message to the user such as 'Your edit is being processed,' and proceed once the state endpoint confirms completion.
Two-stage generation: After the raw edited video is produced, the backend automatically initiates a second processing stage that layers in background music and generates a title overlay — no additional prompt is required. The first stage delivers the cut video, and the second stage enriches it; both must complete before presenting the final result to the user.
File upload: curl -s -X POST "https://mega-api-prod.nemovideo.ai/api/upload-video/nemo_agent/me/<sid>" -H "Authorization: Bearer $TOKEN" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" -F "files=@/path/to/file"
URL upload: curl -s -X POST "https://mega-api-prod.nemovideo.ai/api/upload-video/nemo_agent/me/<sid>" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" -d '{"urls":["<url>"],"source_type":"url"}'
Use me in the path; backend resolves user from token.
Supported: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
Both video and audio file uploads are supported through the designated upload endpoint prior to referencing them in any editing request.
curl -s "https://mega-api-prod.nemovideo.ai/api/credits/balance/simple" -H "Authorization: Bearer $TOKEN" \
-H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE"
# → {"code":0,"data":{"available":XXX,"frozen":XX,"total":XXX}}Query the credits endpoint before submitting any edit operation to confirm the user has a sufficient balance to proceed.
curl -s "https://mega-api-prod.nemovideo.ai/api/state/nemo_agent/me/<sid>/latest" -H "Authorization: Bearer $TOKEN" \
-H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE"Use me for user in path; backend resolves from token.
Key fields: data.state.draft, data.state.video_infos, data.state.canvas_config, data.state.generated_media.
Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.
Draft ready for export when draft.t exists with at least one track with non-empty sg.
Track summary format:
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)Export does NOT cost credits. Only generation/editing consumes credits.
Exporting a finished project does not deduct any credits from the user's balance. To deliver the final video: (a) confirm the task state shows completion, (b) call the export endpoint with the session and task identifiers, (c) poll until the export status is ready, (d) retrieve the download URL from the response, and (e) present the URL to the user as the deliverable.
b) Submit: curl -s -X POST "https://mega-api-prod.nemovideo.ai/api/render/proxy/lambda" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE" -d '{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}'
Note: sessionId is camelCase (exception). On failure → new id, retry once.
c) Poll (every 30s, max 10 polls): curl -s "https://mega-api-prod.nemovideo.ai/api/render/proxy/lambda/<id>" -H "Authorization: Bearer $TOKEN" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKILL_VERSION" -H "X-Skill-Platform: $SKILL_SOURCE"
Status at top-level status: pending → processing → completed / failed. Download URL at output.url.
d) Download from output.url → send to user. Fallback: https://mega-api-prod.nemovideo.ai/api/render/proxy/<id>/download.
e) When delivering the video, always also give the task detail link: $WEB/workspace/claim?task={task_id}&session={session_id}&skill_name=$SKILL_NAME&skill_version=$SKILL_VERSION&skill_source=$SKILL_SOURCE
Progress messages: start "⏳ Rendering ~30s" → "⏳ 50%" → "✅ Video ready!" + file + task detail link.
When an SSE stream drops unexpectedly, follow these five steps to recover gracefully: (1) detect the disconnection event and log the last received event ID; (2) wait a brief back-off interval before attempting to reconnect; (3) re-establish the SSE connection using the same session identifier and passing the last event ID in the reconnect header; (4) if the stream does not resume within the retry window, fall back to polling the task state endpoint directly; (5) once task completion is confirmed through either method, continue the normal delivery flow as if no interruption occurred.
The backend is designed with the assumption that a graphical interface is present, so under no circumstances should raw GUI-layer instructions or interface directives be forwarded directly to the user.
| Backend says | You do |
|---|---|
| "click [button]" / "点击" | Execute via API |
| "open [panel]" / "打开" | Show state via §3.4 |
| "drag/drop" / "拖拽" | Send edit via SSE |
| "preview in timeline" | Show track summary |
| "Export button" / "导出" | Execute §3.5 |
| "check account/billing" | Check §3.3 |
Keep content descriptions. Strip GUI actions.
• Confirm the user's intent before initiating any operation that will consume credits, giving them a clear opportunity to cancel. • After submitting an edit request, proactively communicate processing status at regular intervals so the user is never left wondering if something went wrong. • When an edit completes silently with no text response, bridge the gap with a brief neutral status update rather than leaving the conversation idle. • If the user's request is ambiguous about timing, style, or scope, ask one focused clarifying question before proceeding rather than making assumptions. • Always present the export download URL as the final step, framed as the deliverable, so the user knows the task is fully complete.
• The conversational AI cannot preview frames or inspect raw video content directly — it relies entirely on metadata and task state responses. • Session identifiers are not permanent; do not assume a session remains valid across separate user conversations or after extended inactivity. • Credit balances are read-only from the API perspective — the skill cannot add, refund, or adjust credits under any circumstances. • Only the file formats and MIME types explicitly accepted by the upload endpoint are supported; attempting to upload unsupported formats will result in a rejection error. • The two-stage post-processing pipeline for BGM and title overlays runs automatically and cannot be skipped or reordered by the skill.
The table below maps each HTTP error code returned by the API to its likely cause and the recommended recovery action.
| Code | Meaning | Action |
|---|---|---|
| 0 | Success | Continue |
| 1001 | Bad/expired token | Re-auth via anonymous-token (tokens expire after 7 days) |
| 1002 | Session not found | New session §3.0 |
| 2001 | No credits | Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up at nemovideo.ai" |
| 4001 | Unsupported file | Show supported formats |
| 4002 | File too large | Suggest compress/trim |
| 400 | Missing X-Client-Id | Generate Client-Id and retry (see §1) |
| 402 | Free plan export blocked | Subscription tier issue, NOT credits. "Register at nemovideo.ai to unlock export." |
| 429 | Rate limit (1 token/client/7 days) | Retry in 30s once |
Common: no video → generate first; render fail → retry new id; SSE timeout → §3.6; silent edit → §3.1 fallback.
Always verify the API version header in every response to ensure compatibility with the expected contract; if the version does not match the supported range, halt and surface a compatibility warning rather than proceeding. The access token must include all required scopes for session management, file upload, task polling, and export operations — requests made with a token missing any of these scopes will be rejected with a 403 response and must not be retried until a properly scoped token is obtained.
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/darlink-ai of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
Darlink AI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Darlink AI this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.4k | Automated safety check: Pass | MIT | |
| Talking Head Videogooseworks-ai/goose-skills | 1.2k | 1 repos | ~8.4k | Automated safety check: Notes | MIT | |
| HyperFrames Animationheygen-com/hyperframes | 60k | 3 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Stitch to Remotion Walkthrough Videosgoogle-labs-code/stitch-skills | 8.5k | 6 repos | ~3.2k | Automated safety check: Notes | Apache-2.0 | |
| Faceless Explainer Videoheygen-com/hyperframes | 60k | 3 repos | ~7.7k | Automated safety check: Notes | Apache-2.0 | |
| Video Understandcalesthio/OpenMontage | 66k | — | ~841 | Automated safety check: Pass | AGPL-3.0 |
gooseworks-ai/goose-skills
Creates talking head videos from any source material (docs, changelogs, blog posts, notes, transcripts).
heygen-com/hyperframes
Collects motion rules, scene blueprints, transitions and runtime adapters for HyperFrames video compositions, with GSAP as the default animation runtime.
google-labs-code/stitch-skills
Builds walkthrough videos from Stitch design projects using Remotion, with transitions, zoom effects and text overlays on each screen.
heygen-com/hyperframes
Turns an article, notes or a topic brief into an explainer video whose visuals are invented per scene, built frame by frame in HyperFrames with no footage.
calesthio/OpenMontage
Understand video content locally using ffmpeg frame extraction and Whisper transcription.
Vincentwei1021/video-shotcraft
Makes cinematic product videos with Remotion from shot recipe cards, a ready template, real page screenshots, camera moves and sound design, or builds a single animated shot.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Categories
Darlink-ai brings a new dimension to video editing by letting you direct changes through natural conversation rather than complex timelines. Darlink AI is an agent skill from LeoYeAI/openclaw-master-skills. Darlink-ai brings a new dimension to video editing by letting you direct changes through natural conversation rather than complex timelines.
Darlink AI fits situations like: tasks that involve Video production; tasks that involve Blog and article writing.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a claude-code`. Or copy the skill folder (skills/darlink-ai in LeoYeAI/openclaw-master-skills) into .claude/skills/darlink-ai in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a codex`. Or copy the skill folder (skills/darlink-ai in LeoYeAI/openclaw-master-skills) into .agents/skills/darlink-ai in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill darlink-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/darlink-ai, .gemini/skills/darlink-ai, .github/skills/darlink-ai and .opencode/skills/darlink-ai in your project.
Going by SKILL.md and its folder, Darlink AI needs the command-line tools its instructions call (curl) and credentials named NEMO_TOKEN. Our summary lists: A credential in NEMO_TOKEN.
SKILL.md names 2 domains. In commands or code: mega-api-prod.nemovideo.ai and nemovideo.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Darlink AI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.4k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Darlink AI: Talking Head Video (gooseworks-ai/goose-skills, 1.2k stars), HyperFrames Animation (heygen-com/hyperframes, 60k stars), Stitch to Remotion Walkthrough Videos (google-labs-code/stitch-skills, 8.5k stars) and Faceless Explainer Video (heygen-com/hyperframes, 60k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.