Best Image Creator

Turn a short text description like 'sunset over a mountain lake' into 1080p AI created images just by typing what you need. Whether it's generating images fr...

Security Scan

The skill's requirements and runtime instructions mostly line up with an image-generation connector for the Nemo (nemovideo.ai) backend; there are minor metadata inconsistencies to clarify but nothing that indicates the skill is trying to do something other than call that API and handle uploads.

Purpose & Capability

The skill claims to generate images/video via a cloud rendering pipeline and requests a single credential (NEMO_TOKEN) used as a Bearer token to call endpoints at mega-api-prod.nemovideo.ai — this is coherent. One inconsistency: the registry summary listed no required config paths, but the SKILL.md frontmatter metadata includes a configPaths entry (~/.config/nemovideo/). That could be legitimate (reuse local Nemo config) but should be clarified.

Instruction Scope

SKILL.md stays focused on the Nemo API flow: use NEMO_TOKEN or obtain an anonymous token, create a session, send SSE messages, upload files, poll export jobs, and return download URLs. It does instruct the agent to read the skill's YAML frontmatter and to detect an install path (to set X-Skill-Platform), and it may read local files only when uploading user-provided media. These local reads are plausible for this skill but are broader than pure prompt-to-API text flows — expect the agent to access provided file paths and optionally ~/.config/nemovideo/ if present.

Install Mechanism

No install spec and no code files (instruction-only). That is the lowest-risk install pattern — nothing is downloaded or written by an installer step.

Credentials

Only one credential (NEMO_TOKEN) is required and declared as primaryEnv, which matches the API usage. The skill also documents a fallback to obtain an anonymous token via the Nemo auth endpoint (no extra secrets). The small issue to flag: the SKILL.md frontmatter lists a configPaths entry (~/.config/nemovideo/) which was not listed in the registry summary; if the skill reads that config path at runtime it could access locally-stored Nemo credentials or settings. That access can be reasonable for convenience but should be explicit to the user.

Persistence & Privilege

The skill is not always-enabled, does not request elevated platform privileges, and does not include install-time modifications. It does instruct the agent to create and maintain a session token for rendering jobs (normal for this workflow), but it does not ask to modify other skills or system-wide settings.

Assessment

This skill appears to be a straightforward connector to the Nemo (nemovideo.ai) image/video rendering API and only needs a single API token (NEMO_TOKEN). Before installing: 1) Confirm you trust mega-api-prod.nemovideo.ai and the source of the NEMO_TOKEN you will provide. 2) If you don't want the skill to reuse local Nemo credentials, avoid placing tokens in ~/.config/nemovideo/ or ask the author to remove that behavior; the frontmatter suggests the skill may look there. 3) Treat uploaded files and prompts as data sent to an external service — don't upload sensitive private files or secrets. 4) If you prefer tighter control, run without a long-lived NEMO_TOKEN and allow the skill to obtain a short-lived anonymous token, or create a scoped token with limited permissions. 5) Ask the publisher to resolve the registry vs SKILL.md metadata mismatch (configPaths declared in frontmatter but not in registry) so it's clear what local paths, if any, will be accessed.

Getting Started

Share your text prompts and I'll get started on AI image generation. Or just tell me what you're thinking.

Try saying:

• "generate my text prompts"
• "export 1080p MP4"
• "generate a realistic photo of a"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Best Image Creator — Generate Images from Text Prompts

This tool takes your text prompts and runs AI image generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a short text description like 'sunset over a mountain lake' and want to generate a realistic photo of a futuristic city at night with neon lights — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.

Tip: shorter and more specific prompts tend to produce sharper, more accurate results.

Matching Input to Actions

User prompts referencing best image creator, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

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	❌

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: best-image-creator
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Error Codes

• 0 — success, continue normally
• 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
• 1002 — session not found; create a new one
• 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
• 4001 — unsupported file type; show accepted formats
• 4002 — file too large; suggest compressing or trimming
• 400 — missing X-Client-Id; generate one and retry
• 402 — free plan export blocked; not a credit issue, subscription tier
• 429 — rate limited; wait 30s and retry once

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

• "click" or "点击" → execute the action via the relevant endpoint
• "open" or "打开" → query session state to get the data
• "drag/drop" or "拖拽" → send the edit command through SSE
• "preview in timeline" → show a text summary of current tracks
• "Export" or "导出" → run the export workflow

SSE Event Handling

Event	Action
Text response	Apply GUI translation (§4), present to user
Tool call/result	Process internally, don't forward
heartbeat / empty data:	Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes	Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a realistic photo of a futuristic city at night with neon lights" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, MP4 for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "generate a realistic photo of a futuristic city at night with neon lights" → Download MP4. Takes 20-40 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.