Letter Maker

Get animated letter videos ready to post, without touching a single slider. Upload your text or images (MP4, MOV, PNG, JPG, up to 200MB), say something like...

Security Scan

The skill's declared purpose (cloud video rendering) matches most of its instructions, but there are inconsistencies and vague steps around token handling and filesystem access that warrant caution before installing.

Purpose & Capability

The skill claims to create letter videos via a Nemo cloud backend and all API endpoints in SKILL.md match that purpose. Requesting a NEMO_TOKEN is reasonable for this integration. However the YAML frontmatter inside SKILL.md lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths — this mismatch should be explained.

Instruction Scope

Runtime instructions include creating or using a NEMO_TOKEN, uploading user files to a remote service, using SSE, and polling render jobs (expected). Concerningly, the skill also instructs the agent to detect install path to set X-Skill-Platform and references a local config path (~/.config/nemovideo/). That means the agent may inspect the user's filesystem and possibly read/write configuration. The doc is also vague about whether an anonymous token it fetches will be stored locally or only held in-memory.

Install Mechanism

Instruction-only skill with no install spec and no code files. That is the lowest-risk install mechanism — nothing will be downloaded or written by an installer step according to the package metadata.

Credentials

Only one credential (NEMO_TOKEN) is declared as required, which is proportionate for a cloud rendering service. But the instructions explicitly describe obtaining an anonymous token if NEMO_TOKEN is not set, and the frontmatter suggests a config path that could contain credentials — it's unclear whether the skill will write tokens to disk or try to read existing Nemo credentials. This ambiguity should be clarified.

Persistence & Privilege

always:false and default autonomous invocation are appropriate. The skill may create short-lived cloud sessions and orphan jobs if a client disconnects (documented). There is no explicit request for permanent system-wide privileges, but the potential filesystem access/config-path use is a minor persistence/privilege concern until clarified.

What to consider before installing

This skill appears to do what it says (upload your text/images and use Nemo's cloud rendering), but there are a few unclear or concerning points to check before installing: 1) Ask the developer to confirm whether the skill will read or write ~/.config/nemovideo/ and exactly what it stores there (tokens, user IDs, etc.). 2) Confirm how an anonymous token is handled: will it only be held in memory, or will it be saved to disk or the environment? 3) Be aware that files you upload will be sent to an external service (mega-api-prod.nemovideo.ai); avoid uploading sensitive/private data unless you trust the service. 4) If you want to limit exposure, use an ephemeral/limited Nemo account or a throwaway token, and verify network activity in a safe environment. 5) The registry metadata and the SKILL.md frontmatter disagree about required config paths — get that discrepancy resolved. If the developer cannot clarify token storage and filesystem access, treat the skill as higher risk and avoid granting it access to production credentials or sensitive files.

Getting Started

Got text or images to work with? Send it over and tell me what you need — I'll take care of the AI letter video creation.

Try saying:

• "create a short message or letter text prompt into a 1080p MP4"
• "turn my written letter into a video with animated text and background music"
• "creating video letters to send to friends, family, or colleagues for content creators, students, marketers"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Letter Maker — Turn Written Letters Into Videos

This tool takes your text or images and runs AI letter video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a short message or letter text prompt and want to turn my written letter into a video with animated text and background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter letter text renders faster and fits better in short-form video formats.

Matching Input to Actions

User prompts referencing letter maker, 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.

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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is letter-maker, 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).

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

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

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.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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 "turn my written letter into a video with animated text and background music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social and messaging platforms.

Common Workflows

Quick edit: Upload → "turn my written letter into a video with animated text and background music" → Download MP4. Takes 30-60 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.