Free Image Text

Get text-overlaid videos ready to post, without touching a single slider. Upload your images with text (JPG, PNG, WEBP, PDF, up to 200MB), say something like...

Security Scan

The skill's requirements and runtime instructions are consistent with its stated purpose: it uploads user images to a nemovideo backend to extract text and produce captioned videos and only needs a NEMO_TOKEN (or an anonymous token) to operate.

Purpose & Capability

Name/description (extract text from images and overlay as video captions) align with required credentials (NEMO_TOKEN) and the API endpoints described; no unrelated credentials or binaries are requested.

Instruction Scope

SKILL.md confines actions to the nemovideo API (session creation, upload, render, SSE polling). It will upload user files to the external service and may obtain an anonymous token if NEMO_TOKEN is not present. A minor mismatch: metadata advertises a config path (~/.config/nemovideo/) and X-Skill-Platform detection based on install paths, but the instructions do not explicitly describe reading that config path — this is plausible (for cached tokens) but worth noting.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer; lowest install risk.

Credentials

Only NEMO_TOKEN is required (primaryEnv). The instructions explain using an anonymous-token endpoint when no token is present. No other unrelated secrets or credentials are requested.

Persistence & Privilege

always is false, model invocation is allowed (normal). The skill does not request elevated or persistent system privileges and does not modify other skills' configurations.

Assessment

This skill uploads any images you provide to an external service (mega-api-prod.nemovideo.ai) to extract text and render videos. Before installing/use: (1) confirm you trust that external service with the image content (avoid sending sensitive PII or credentials in images); (2) provide a NEMO_TOKEN only if you trust the provider, otherwise the skill will request an anonymous 7‑day token from the public endpoint; (3) note the skill may read its install path to set an attribution header (minor metadata mismatch with the declared config path), and it will make network calls and store session tokens for rendering — revoke tokens if you suspect misuse. If you need stronger guarantees about where data is stored or retention, contact the service owner or avoid sending sensitive images.

Getting Started

Send me your images with text and I'll handle the text extraction generation. Or just describe what you're after.

Try saying:

• "convert a product photo with a price tag or a scanned document image into a 1080p MP4"
• "extract the text from this image and overlay it as captions on my video"
• "extracting text from images and adding it as on-screen captions or subtitles to videos for content creators, marketers, students"

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.

Free Image Text — Extract image text into video

Drop your images with text in the chat and tell me what you need. I'll handle the text extraction generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a product photo with a price tag or a scanned document image, ask for extract the text from this image and overlay it as captions on my video, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — higher contrast images produce more accurate text extraction results.

Matching Input to Actions

User prompts referencing free image text, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-image-text, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says	You do
"click [button]" / "点击"	Execute via API
"open [panel]" / "打开"	Query session state
"drag/drop" / "拖拽"	Send edit via SSE
"preview in timeline"	Show track summary
"Export button" / "导出"	Execute export workflow

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)

Common Workflows

Quick edit: Upload → "extract the text from this image and overlay it as captions on my video" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "extract the text from this image and overlay it as captions on my video" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.