Real Skill packageSource verifiedClawHub registry

monitoring-tiktok-mentions-of-brand

Monitors TikTok for brand mentions and product discussions using apidojo's TikTok scraper on Apify. Triggers when the user asks to: track mentions of a brand on TikTok, monitor TikTok hashtags for brand content, find TikTok videos talking about a product or company, see what TikTok says about a brand this week, track TikTok reactions to a product launch, find TikTok creators who mentioned a competitor brand, monitor brand sentiment on TikTok, or discover viral TikTok content about a specific brand or product. Retu…

Identity and source

Publisher attributionAPI Dojoregistry owner unverified by skillvetai
Functional categoryDevOps, Cloud & Observabilityautomatically inferred · 60% rule confidence
Package forminstruction bundle2 recorded files
Canonical sourceClawHub registryclawhub:apidojo-io:monitoring-tiktok-mentions-of-brand
Open canonical source ↗

Platform declarations

These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.

OpenClawnative officialProvenance: registry distribution

Independent structural checks

These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.

Claude Codepasses structure
Checker 0.1.0 · agent-skills-2026-08-13+claude-code-docs-2026-08-13 · 9/3/2026.claude/skills/monitoring-tiktok-mentions-of-brand

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenAI Codexpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+codex-docs-2026-08-13 · 9/3/2026.agents/skills/monitoring-tiktok-mentions-of-brand

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenClawpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+openclaw-docs-2026-08-13 · 9/3/2026skills/monitoring-tiktok-mentions-of-brand

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

Installation and inspection

This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.

clawhub install @apidojo-io/monitoring-tiktok-mentions-of-brand
clawhub inspect @apidojo-io/monitoring-tiktok-mentions-of-brand --version 1.0.0

Security evidence

SkillVetAI static result: no findings detected

This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.

Status
completed
Coverage
full text content
Files
1 / 1 inspected as text
Checked
9/3/2026, 4:23:02 AM
Scanner
0.1.3
Policy
1.0.3
2 inferred permission indicators
  • network access — automatically inferred
  • filesystem write — automatically inferred
1 dependency and API indicators
  • api: api.apify.com
External clawhub result: clean

This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.

Evidence checked
9/3/2026, 6:38:13 AM
Release binding
Matches this record
  • vt: clean
  • skillspector: suspicious
  • llm: clean

Recorded files

The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.

Package content hashsha256:257c70fb13ce1725a3415718bd65810ddce39d4c366a236cdf1cc7861beb4a6e
Show up to 2 recorded paths
  • skill-card.md
  • SKILL.md

Source changelog

Initial release — monitors TikTok for brand mentions and provides sentiment and virality analysis. - Tracks TikTok brand mentions using apidojo’s TikTok scraper via Apify. - Returns creator handle, views, likes, comments, sentiment signal, and caption preview. - Classifies content (e.g., unboxing, review, complaint) and flags trending or crisis posts based on engagement. - Designed for brand managers, community, and marketing teams to detect viral praise or criticism. - Includes step-by-step usage instructions, example scripting, and output report template.