# Analyze WeChat Channels Video Structure and Feedback

Popular videos can be difficult to explain from engagement counts alone. This skill combines available details, transcripts, and sampled comments into an evidence-based creative analysis.

## Install

```bash
npx skillstore add devinchen2014/wechat-channels-viral-video-breakdown
```

## Metadata

- Status: approved
- Slug: devinchen2014-wechat-channels-viral-video-breakdown
- Skillstore revision: r2
- Version status: missing
- Tree hash: 9e791c50a9c5462846805db7a94a9f932bca7a7c77e5dd839e6e707123afe173
- Author: devinchen2014
- GitHub username: devinchen2014
- Repository: https://github.com/devinchen2014/socialdatax-skills/tree/1a2597b6943935ac2b00e637fb7ab469b79e4d41/modelscope-skills/wechat-channels-viral-video-breakdown
- Ref: 281bf91388b8f173a996554eb0c0cdf91dec2cc7
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network, env\_access
- Quality score: 72
- Public page: https://skillstore.pages.dev/skills/devinchen2014-wechat-channels-viral-video-breakdown
- Manifest: https://skillstore.pages.dev/api/skills/devinchen2014-wechat-channels-viral-video-breakdown/manifest

## Capabilities

- Retrieve available public video details from a WeChat Channels link or share text through SocialDataX CLI or configured MCP tools.
- Submit speech transcription tasks and query an existing job without resubmitting the video.
- Analyze opening hooks, content structure, spoken pacing, and interaction prompts using returned descriptions and transcripts.
- Retrieve sampled comments and selected reply threads, reporting pagination scope and incomplete results.
- Suggest three to five reusable creative approaches while separating public facts, transcript evidence, comment evidence, and interpretation.
- Export SRT subtitles through CLI version 0.2.64 or newer when requested and valid timed segments are available.

## Use Cases

- Develop a video outline: Analyze a reference video's hook and structure, then identify transferable approaches supported by the returned transcript.
- Research audience questions: Review a bounded comment sample and selected replies to identify recurring questions, objections, and possible follow-up topics.
- Prepare an editorial case study: Separate public metrics, transcript evidence, audience comments, and interpretation in a structured report with explicit sampling limits.

## Prompt Templates

### Analyze one video

```
Analyze this WeChat Channels video: [link or share text]. Use available details and its transcript. Identify the opening hook, structure, and missing evidence.
```

### Review audience feedback

```
Review [video link] using details, transcript, and one comment page. Summarize repeated questions and objections. Do not retrieve replies. State the sample limits.
```

### Develop reusable approaches

```
Analyze [video link] for [target audience]. Separate facts from interpretations. Propose three to five reusable approaches with supporting evidence. Mark missing data and avoid performance guarantees.
```

### Resume transcription and export subtitles

```
Query existing transcription job [job_id] without resubmitting. If successful, analyze its hook and structure. Export SRT to [new writable path] only if valid timed segments exist.
```

## Limitations

- Requires authenticated SocialDataX access and sufficient service credits; direct CLI also requires Node.js, npm, and network access.
- Conclusions cover only the supplied video and returned samples, not complete platform coverage, hidden demographics, or recommendation mechanisms.
- Missing transcripts, metrics, or timestamps limit analysis; hosted MCP alone does not create a local SRT file.
- Does not publish, log in, modify accounts, or guarantee viral results; reviewed files do not include the external CLI implementation.

## Best Practices

- Provide the complete video link, share text, or existing job identifier, and define comment and reply limits before retrieval.
- Keep credentials in supported secret storage, approve CLI execution, and use a reviewed package version rather than a mutable latest release.
- Keep facts, transcript evidence, comment samples, and interpretations separate; reuse job identifiers and continuation tokens when recovering partial results.

## Anti Patterns

- Treating sampled comments or public engagement counts as proof of platform ranking rules or guaranteed future performance.
- Pasting API keys into chat, logs, screenshots, or tracked files, or concatenating raw user input into shell commands.
- Resubmitting existing transcription jobs, repeatedly retrying insufficient-balance errors, or restarting partial pagination from the first page.

## Security Audit

- Audited at: 2026-11-06T05:01:00.539\+00:00
- Summary: Of 55 alerts, 54 are false positives involving Markdown, readable Chinese text, service links, identifiers, or scoped credential checks. One confirmed risk involves automatically executing an unpinned npm package with access to the agent environment. No evidence found of embedded credentials, credential exfiltration, reconnaissance, encoded payloads, or prompt injection in the reviewed files.

## Stats

- Views: 0
- Downloads: 3
- Favorites: 0
- Popularity score: 0