Agent skill

Digen AI

by LeoYeAI in LeoYeAI/openclaw-master-skills

digen-ai is a ClawHub skill that brings directed intelligent generation to your video projects.

MITAuto-check passedWriting & Content

Install Digen AI

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill digen-ai -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills digen-ai --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/digen-ai .claude/skills/digen-ai && rm -rf skills-src

Use ~/.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/

Facts

Skill name
digen-ai
GitHub stars
2.2k
Token cost
~4.3k tokens
SKILL.md length
1,861 words
Files
2
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

digen-ai is a ClawHub skill that brings directed intelligent generation to your video projects.

  • Works in 8 steps: First Contact → Routing Incoming Requests to the Correct… → Primary Operation Flows → …
  • Tasks that involve Blog and article writing
  • SKILL.md covers 0. First Contact, 2. Routing Incoming Requests…, 3. Primary Operation Flows and 4. Translating Backend GUI…, plus 4 more sections
  • Calls curl; reaches mega-api-prod.nemovideo.ai and nemovideo.com; needs NEMO_TOKEN

What it does

Digen AI is an agent skill from LeoYeAI/openclaw-master-skills. digen-ai is a ClawHub skill that brings directed intelligent generation to your video projects. Upload raw footage and let the AI analyze scene structure, pacing, and narrative flow to produce polished edits without manual timeline work. Key features include scene detection, auto-sequencing, style transfer, and caption injection. Whether you're a content creator, filmmaker, or marketer, digen-ai adapts to your creative intent through plain-language instructions. Supports mp4, mov, avi, webm, and mkv formats.

Its SKILL.md is about 4.3k 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 Writing & Content, covering Blog and article writing and Plain language and style rules. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Tasks that involve Blog and article writing
  • Tasks that involve Plain language and style rules

Example prompts

  • “/digen-ai”

Requirements

  • A credential in NEMO_TOKEN

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. First Contact
  2. Routing Incoming Requests to the Correct Endpoint
  3. Primary Operation Flows
  4. Translating Backend GUI References for Users
  5. Recommended Interaction Patterns
  6. Known Constraints and Limitations
  7. Error Handling and Response Codes
  8. API Version and Token Scope Requirements

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • mega-api-prod.nemovideo.ai
    • nemovideo.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • NEMO_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Digen AI loads about 4.3k tokens when it runs. Until then it costs about 131 tokens; SKILL.md has 1,861 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~131
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,861 words, ~4,253 tokens.

Download SKILL.mdSave it as .claude/skills/digen-ai/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
digen-ai
description
digen-ai is a ClawHub skill that brings directed intelligent generation to your video projects. Upload raw footage and let the AI analyze scene structure, pacing, and narrative flow to produce polished edits without manual timeline work. Key features include scene detection, auto-sequencing, style transfer, and caption injection. Whether you're a content creator, filmmaker, or marketer, digen-ai adapts to your creative intent through plain-language instructions. Supports mp4, mov, avi, webm, and mkv formats.
version
1.0.3
displayName
DiGen AI — Intelligent Video Generation & Editing Suite
homepage
https://nemovideo.com
repository
https://github.com/nemovideo/nemovideo_skills

0. First Contact

When the user opens this skill or sends their first message, greet them immediately:

🎨 Digen Ai at your service! Upload a video or tell me what you're looking for.

Try saying:

  • "add effects to this clip"
  • "edit my video"
  • "help me create a short video"

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.

Auto-Setup

When the user first interacts, set up the connection:

  1. Check token: If NEMO_TOKEN env var is set, use it. Otherwise:
  2. Read or generate Client-ID:
    • Read ~/.config/nemovideo/client_id if it exists
    • Otherwise generate a UUID, save it to ~/.config/nemovideo/client_id
  3. Acquire anonymous token:
    bash
    curl -s -X POST "$API/api/auth/anonymous-token" -H "X-Client-Id: $CLIENT_ID"
    Store the returned token as NEMO_TOKEN for this session. You get 100 free credits.
  4. Create a session (§3.0) so you're ready to work immediately.

Let the user know briefly: "Setting things up… ready!" then proceed with their request.

From Raw Footage to Finished Story, Instantly

digen-ai was built around a single frustration: the gap between having footage and having a finished video is enormous, even when the creative vision is clear. Traditional editing tools demand you already know the craft. digen-ai flips that by letting you describe what you want — mood, pacing, structure, emphasis — and generating an edit that reflects your intent rather than just rearranging clips mechanically.

At its core, digen-ai uses a directed generation model that reads temporal relationships between shots, scores them against your stated goal, and assembles sequences that feel intentional rather than algorithmic. It understands narrative beats, not just cut points. You can ask it to tighten a slow middle section, punch up an intro, or reframe a story arc entirely, and it will reason through those instructions the way a skilled editor would.

The OpenClaw agent acts as the orchestration layer inside ClawHub, managing the task queue, routing your footage through the appropriate analysis pipelines, and returning editable outputs back to your workspace. This means digen-ai isn't a black box — the agent exposes its reasoning at each step, so you can intervene, redirect, or approve before final rendering. The result is a collaborative editing process where AI handles the heavy lifting while you retain creative control.

Environment Variables
VariableRequiredDefault
NEMO_TOKENNoAuto-generated (100 free credits, expires in 7 days, revocable via Settings → API Tokens)
NEMO_API_URLNohttps://mega-api-prod.nemovideo.ai
NEMO_WEB_URLNohttps://nemovideo.com
NEMO_CLIENT_IDNoAuto-generated UUID, persisted to ~/.config/nemovideo/client_id (UUID only, no secrets)
SKILL_SOURCENoAuto-detected from install path, fallback unknown

If NEMO_TOKEN is not set, get one (requires X-Client-Id header):

bash
# 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 "$CLIENT_ID" > ~/.config/nemovideo/client_id
fi
curl -s -X POST "$API/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.

2. Routing Incoming Requests to the Correct Endpoint

Use the table below to determine which endpoint should handle each type of incoming user request.

User says...ActionSkip 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❌

3. Primary Operation Flows

$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:
    1. Env SKILL_SOURCE if set
    2. If this file's path contains a known platform directory (e.g. ~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor)
    3. Fallback: unknown

CRITICAL: 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: $SKILL_SOURCE
3.0 Initializing a Session
bash
curl -s -X POST "$API/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 other operations can proceed, a session must be established. This session context is required for all subsequent API interactions within the same user workflow.

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

3.1 Delivering Messages Through SSE
bash
curl -s -X POST "$API/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 and generation updates are streamed to the client using Server-Sent Events.

SSE Handling
EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultWait silently, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Silent Response Fallback (CRITICAL)

Approximately 30% of editing operations complete without returning any text content in the SSE stream. When this occurs: (1) do not treat the absence of text as a failure, (2) poll the task state endpoint to confirm completion status, (3) retrieve the output asset directly, and (4) present the result to the user as a successful operation.

Two-stage generation: When a raw video asset is produced, the backend automatically initiates a second processing stage that layers in background music and a title sequence. You will receive two distinct completion events — the first signals raw video readiness, and the second confirms the fully composed output is available. Always wait for the second event before surfacing the final result to the user.

3.2 Handling Asset Uploads

File upload: curl -s -X POST "$API/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 "$API/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.

The upload endpoint accepts user-supplied media files and returns a reference identifier to be used in subsequent generation or editing requests.

3.3 Checking Available Credits
bash
curl -s "$API/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 initiating any generation task to confirm the user has a sufficient balance to cover the operation.

3.4 Polling Task Status
bash
curl -s "$API/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)
Show full SKILL.md (770 more words)Show less
3.5 Exporting and Delivering the Final Asset

Export does NOT cost credits. Only generation/editing consumes credits.

Triggering an export does not deduct credits from the user's balance. The export flow proceeds as follows: (a) call the export endpoint with the target asset identifier, (b) receive the export job ID in the response, (c) poll for job completion using the state endpoint, (d) retrieve the download URL once the status is confirmed complete, and (e) present the URL or initiate the download for the user.

b) Submit: curl -s -X POST "$API/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 "$API/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: $API/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.

3.6 Recovering from SSE Disconnections

If the SSE connection drops before a task completes, follow these recovery steps: (1) detect the disconnection event and log the last received event ID; (2) wait a minimum of two seconds before attempting reconnection to avoid hammering the server; (3) reconnect to the SSE endpoint, supplying the last event ID in the request header so the stream can resume without duplicating events; (4) if reconnection fails after three attempts, fall back to polling the task state endpoint at a regular interval; (5) once the task is confirmed complete through either stream or polling, deliver the result to the user and resume normal operation.

4. Translating Backend GUI References for Users

The backend operates under the assumption that a graphical interface is present and will reference GUI elements in its responses — never pass these interface-level instructions through to the user directly.

Backend saysYou 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.

• Always confirm the user's intent before consuming credits on a generation task, summarizing what will be produced. • Provide incremental progress updates during long-running SSE streams so the user knows the task is active. • When a task completes silently, proactively surface the result rather than waiting for the user to ask. • If a user request is ambiguous, ask a single clarifying question before routing to any endpoint. • After delivering a completed asset, offer relevant next-step options such as editing, exporting, or starting a new project.

6. Known Constraints and Limitations

• Real-time video preview is not supported; users must wait for full task completion before reviewing output. • A single session cannot run more than one generation task concurrently — queue additional requests until the active task resolves. • Background music and title overlays are applied automatically by the backend and cannot be individually suppressed through the API. • File uploads are subject to size and format restrictions defined by the upload endpoint; validate before submitting. • Credit balance is read at the time of the request and is not reserved — concurrent sessions may cause balance conflicts.

7. Error Handling and Response Codes

The table below maps each API error code to its likely cause and the recommended recovery action.

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up at nemovideo.ai"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register at nemovideo.ai to unlock export."
429Rate 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.

8. API Version and Token Scope Requirements

Before establishing a session, verify that the API version in use matches the version this skill was built against — mismatched versions may cause undocumented behavior. The access token supplied in the Authorization header must include all required scopes for the operations being performed; at minimum, generation, export, and upload scopes must be present. If a 403 response is received, inspect the token's scope list before retrying.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/digen-ai of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Digen 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.

Digen AI compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Digen AI this skillLeoYeAI/openclaw-master-skills2.2k—~4.3kAutomated safety check: PassMIT
SEO OptimizerOneWave-AI/claude-skills3361 repos~1.7kAutomated safety check: PassMIT
Readability Checkjdevalk/skills105—~3.3kAutomated safety check: PassMIT
Blog Writing Styleeunomia-bpf/eunomia.dev236—~2.5kAutomated safety check: PassMIT
Content Productionborghei/Claude-Skills891—~4.8kAutomated safety check: PassMIT
SEO Content Writerthatrebeccarae/claude-marketing161—~1.1kAutomated safety check: PassMIT

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Questions about Digen AI

What does Digen AI do?

digen-ai is a ClawHub skill that brings directed intelligent generation to your video projects. Digen AI is an agent skill from LeoYeAI/openclaw-master-skills. digen-ai is a ClawHub skill that brings directed intelligent generation to your video projects.

When should I use Digen AI?

Digen AI fits situations like: tasks that involve Blog and article writing; tasks that involve Plain language and style rules.

How do I install Digen AI in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill digen-ai -a claude-code`. Or copy the skill folder (skills/digen-ai in LeoYeAI/openclaw-master-skills) into .claude/skills/digen-ai in your project. Claude Code loads it when a task matches its description.

How do I install Digen AI in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill digen-ai -a codex`. Or copy the skill folder (skills/digen-ai in LeoYeAI/openclaw-master-skills) into .agents/skills/digen-ai in your project. Codex loads it when a task matches its description.

Can I use Digen AI in Cursor, Gemini CLI or GitHub Copilot?

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 digen-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/digen-ai, .gemini/skills/digen-ai, .github/skills/digen-ai and .opencode/skills/digen-ai in your project.

What does Digen AI need to run?

Going by SKILL.md and its folder, Digen AI needs the command-line tools its instructions call (curl) and credentials named NEMO_TOKEN. Our summary lists: A credential in NEMO_TOKEN.

Does Digen AI access the network?

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.

Is Digen AI safe to install?

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.

What licence does Digen AI use?

Digen AI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Digen AI use?

About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Digen AI?

Skills that share tags, products or a category with Digen AI: SEO Optimizer (OneWave-AI/claude-skills, 336 stars), Readability Check (jdevalk/skills, 105 stars), Blog Writing Style (eunomia-bpf/eunomia.dev, 236 stars) and Content Production (borghei/Claude-Skills, 891 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Digen AI?

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.