extracting-tiktok-comments-for-research

Extracts and analyzes TikTok comments from any video or creator using apidojo's TikTok Comments...

What this skill does for you

Extracts and analyzes TikTok comments from any video or creator using apidojo's TikTok Comments scraper on Apify. Triggers when the user asks to: scrape TikTok comments from a video, analyze what viewers say about a TikTok post, extract comment data for sentiment analysis, find top comments on a viral TikTok video, collect TikTok user feedback from comments, build a dataset of TikTok community reactions, study audience sentiment on TikTok content, or research what a target audience cares about from TikTok comments. Returns commenter username, comment text, likes on comment, reply count, and timestamp. Ideal for market researchers, brand managers, content creators, and academic researchers.

Quoted from the skill description in the pinned source

Who made it

Publisherapidojo-io

Repositoryapidojo-skills

Installs388as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the extracting-tiktok-comments-for-research skill from apidojo-io/apidojo-skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: ffbdc00cbd01d09802e7f389ac4f61d4803972a7. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: ffbdc00cbd01d09802e7f389ac4f61d4803972a7. Raw findings: . Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: ffbdc00cbd01d09802e7f389ac4f61d4803972a7. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/apidojo-io/apidojo-skills
Pinned skill file: View source at revision
Revision: ffbdc00cbd01d09802e7f389ac4f61d4803972a7
Package hash: sha256:1a244479eabd22670263b83eba8b05411d1c4adf2b99335d7a9c36f1a3cbf748
Licence: Apache-2.0