# Tt Audience Insights

> Read your TikTok niche and audience from real data. Scan a hashtag for top videos with plays, likes, and comments, see which hooks and sounds are working, pull a profile's videos (yours or a competitor's), and read the commenters on a video (TikTok hides likers, so commenters are the signal). Powered by Apify, no login. Triggers on "what is trending on TikTok", "analyze this hashtag", "competitor…

- **Type:** Skill
- **Install:** `agentstack add skill-sergebulaev-tiktok-skills-tt-audience-insights`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [sergebulaev](https://agentstack.voostack.com/s/sergebulaev)
- **Installs:** 0
- **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [sergebulaev](https://github.com/sergebulaev)
- **Source:** https://github.com/sergebulaev/tiktok-skills/tree/main/skills/tt-audience-insights

## Install

```sh
agentstack add skill-sergebulaev-tiktok-skills-tt-audience-insights
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# TikTok Audience Insights

Turn real TikTok data into a read on what is working: which videos in your niche are exploding and why, what a competitor is posting, and what your commenters keep saying. The read layer sees actual play counts and comments instead of guessing.

One honest limit: TikTok keeps the list of who **liked** a video private (only counts). The engagement signal here is **commenters + video performance**, which is where the niche's questions and objections live.

## When to use

- "What is trending in [niche] on TikTok / analyze this hashtag"
- "What is [competitor] posting / analyze their profile"
- "Read the comments on this video"
- "Which sounds and hooks are working right now"

Not for writing a script (use `tt-hook-scripter`) or a caption (use `tt-caption-writer`).

## Setup (optional)

The read layer uses **Apify** (no login). Free token at `https://console.apify.com/account/integrations`, set `APIFY_TOKEN`. Video scanning is about $1.70 per 1,000, comments about $0.50 per 1,000. No token? Paste the videos or comments and the skill runs the same analysis.

## Input

- A hashtag (niche scan), a profile (self or competitor), or a video URL (comments)
- Optional: the goal (trend scan / competitor read / community management)

## Output

1. **Niche pulse** - top videos for the hashtag ranked by plays, the hooks and sounds behind the winners
2. **Competitor read** - a profile's recent videos ranked, the pattern in their hits
3. **Comment read** - what commenters keep asking, superfans, comments to reply to or pin
4. **Action list** - the hook/sound/format to try, who to engage, which comment to answer on camera

## Steps

1. **Pull the data.** Niche: `lib.ApifyClient().fetch_niche_videos(hashtag, max_items=20)`. Profile: `fetch_profile_videos(username)`. Comments: `fetch_video_comments(video_url)`. Falls back to pasted data if no token.
2. **Rank by performance.** Sort by plays, then engagement rate (likes+comments over plays). Normalize against the author's follower count so a small creator's breakout is not buried under a big account.
3. **Extract the pattern.** For the top videos, name the shared hook (first-second shape), the sound, the format (talking-head, text-overlay, skit), and the length. That is the repeatable part.
4. **Note the sounds.** Recurring sounds across the top videos are a trend to ride; flag them for `tt-trend-mapper`.
5. **Read the comments.** Cluster into questions, agreement, pushback. Recurring questions become video ideas (answer on camera); pinned/high-like comments show what the room cares about.
6. **Build the action list.** Try-this (winning hook + sound), engage (specific commenters), answer-on-camera (a recurring question). Route to `tt-hook-scripter` / `tt-caption-writer`.
7. **Deliver the report** in the Output shape, with the raw ranked videos attached.

## What the read layer exposes

| Method | Returns |
|---|---|
| `fetch_niche_videos(hashtag, max_items)` | top videos for a hashtag: text, plays, likes, comments, shares, author fans, sound |
| `fetch_profile_videos(username, max_items)` | a profile's recent videos with the same fields |
| `fetch_video_comments(video_url, max_items)` | comments (the engagement signal, since likers are private) |

## Hard rules

Global voice rules: see root `SKILL.md` Voice rules. Additional skill-specific rules:

- Be honest that this reads **commenters, not likers** (TikTok keeps likers private). Do not imply a full liker roster.
- **Normalize by follower count** before calling a video a winner, or you extract "big account" effects, not "good video" effects.
- Never invent a video, a count, a sound, or a comment. If the data is thin, say so.
- A pattern (hook or sound) is only a trend if it recurs across several top videos.

## Related skills

- `tt-hook-scripter` - script a video around the winning hook the data found
- `tt-trend-mapper` - ride a sound or format the scan surfaced
- `tt-caption-writer` - caption it
- `tt-content-planner` - feed the winning patterns into a plan

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [sergebulaev](https://github.com/sergebulaev)
- **Source:** [sergebulaev/tiktok-skills](https://github.com/sergebulaev/tiktok-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-sergebulaev-tiktok-skills-tt-audience-insights
- Seller: https://agentstack.voostack.com/s/sergebulaev
- Browse the marketplace: https://agentstack.voostack.com/browse

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