Wechat Video Free

Skip the learning curve of professional editing software. Describe what you want — trim and export this WeChat video as a free MP4 I can share anywhere — and...

Security Scan

The skill's requests and runtime instructions generally match its stated purpose (cloud video editing) but there are a few small inconsistencies and privacy/runtime details you should understand before installing.

Purpose & Capability

The skill is an instruction-only connector to a cloud video-editing backend. Requesting a single API credential (NEMO_TOKEN) and calling endpoints to upload, edit, and export video is consistent with the described functionality.

Instruction Scope

The SKILL.md contains concrete API workflows for authenticating (anonymous token flow), creating sessions, uploading files, streaming SSE responses, and exporting results — all within the expected scope for a cloud video editor. Items to note: it instructs the agent to generate/store a session_id and a token if NEMO_TOKEN is not present (storage location and lifetime are unspecified), and it directs the agent to inspect install paths to set an X-Skill-Platform header. The instructions also require sending user video files to an external service, which is expected but has privacy implications.

Install Mechanism

This is an instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. That minimizes install-time risk.

Credentials

Only one credential (NEMO_TOKEN) is declared as required, which fits the purpose. However, the SKILL.md frontmatter also lists a config path (~/.config/nemovideo/) that the top-level registry metadata did not — this mismatch should be clarified. The skill will generate and use an anonymous token if NEMO_TOKEN is not provided, which is reasonable but means the agent will make outbound calls and manage credentials at runtime.

Persistence & Privilege

The skill is not marked 'always' and is user-invocable; it does not request elevated or persistent system privileges. Autonomous invocation is enabled (platform default) but that is not a reason to flag it on its own.

Scan Findings in Context

[regex_scan_empty] expected: The repository contains no code files — only SKILL.md — so the static regex scanner had nothing to analyze. That is expected for an instruction-only connector.

Assessment

This skill appears to do what it says: it uploads videos to a remote backend and returns edited MP4s. Before installing, consider: 1) Privacy — your videos are uploaded to https://mega-api-prod.nemovideo.ai; confirm you trust that service and its retention policy. 2) Tokens — the skill will use NEMO_TOKEN if set, or will request an anonymous token for you; if you prefer control, set your own NEMO_TOKEN rather than letting the skill obtain one. 3) Storage/cleanup — the SKILL.md says to 'store' session_id and token but doesn't specify where or how to secure them; ask the author how credentials and session state are persisted and expired. 4) Clarify the minor metadata mismatch: SKILL.md references a config path (~/.config/nemovideo/) while registry metadata lists none. If any of these points are unacceptable, do not enable the skill until the author clarifies.

Getting Started

Send me your video clips and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "convert a 60-second WeChat video recording into a 1080p MP4"
• "trim and export this WeChat video as a free MP4 I can share anywhere"
• "converting and editing WeChat videos for free sharing for WeChat users"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

WeChat Video Free — Edit and Export WeChat Videos

Drop your video clips in the chat and tell me what you need. I'll handle the AI video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 60-second WeChat video recording, ask for trim and export this WeChat video as a free MP4 I can share anywhere, 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 — shorter clips under 60 seconds process fastest and stay within free tier limits.

Matching Input to Actions

User prompts referencing wechat video free, 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.

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

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

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

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.

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.

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

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)

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

Common Workflows

Quick edit: Upload → "trim and export this WeChat video as a free MP4 I can share anywhere" → 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 "trim and export this WeChat video as a free MP4 I can share anywhere" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 for widest compatibility across all platforms and devices.