📦

tiktok-scraper

Name: tiktok-scraper
Author: apidojo-io

Inhaltsrevision r1 Mittleres Risiko ⚙️ Externe Befehle🌐 Netzwerkzugriff

Extract TikTok Data Through Apify

TikTok research requires different requests for posts, profiles, comments, and location feeds. This skill documents four Apify actors and reusable API workflows for preparing those requests.

Unterstützt: Claude Codex Code(CC)

📊 68 Angemessen

Maintain this Skill? Claim it 📊 68 Angemessen

Mit meinem Agent installieren

Kopieren Sie diese Anfrage in Ihren Agent. Sie enthält die maßgebliche Skill-Seite und das Manifest.

Agent-Anfrage

Review the Skillstore skill "tiktok-scraper" from https://skillstore.io/skills/apidojo-io-tiktok-scraper.md and its manifest at https://skillstore.io/api/skills/apidojo-io-tiktok-scraper/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Ihr Agent sollte weiterhin seinen Plan anzeigen und alle von der Sicherheitsrichtlinie verlangten Bestätigungen anfordern.

Agent-lesbare Ressourcen

Verwenden Sie diese Links, wenn ein KI-Agent, Crawler oder Skript sauberen Kontext benötigt, statt die vollständige Seite zu lesen.

Markdown-Detailseite GET /skills/apidojo-io-tiktok-scraper.md Signiertes manifest GET /api/skills/apidojo-io-tiktok-scraper/manifest Signiertes lockfile GET /api/skills/apidojo-io-tiktok-scraper/lockfile

Testen

„tiktok-scraper“ wird verwendet. Summarize the documented sample Nike post.

Erwartetes Ergebnis:

Illustrative documentation sample, not a live scrape.
Creator: Nike; account verified.
Views: 340,916; likes: 13,939; comments: 464; shares: 812.
Published: September 4, 2025; video duration: approximately 60 seconds.

„tiktok-scraper“ wird verwendet. Describe the documented sample comment record.

Erwartetes Ergebnis:

Illustrative documentation sample, not a live scrape.
Comment author: superfan123; account not verified.
Comment likes: 1,234; reply count: 5.
Language: English; region: US; no parent comment identifier.

Sicherheitsaudit

Mittleres Risiko

v1 • 30.9.2026 Versionsbericht öffnen

All 102 static findings are false positives for the flagged threats: Markdown formatting, legitimate API substitutions, sample URLs, and subscription prose. Semantic findings identify misleading referral upgrade instructions and missing collection, polling, and error limits in the paid-run example. No evidence found of credential exfiltration, host reconnaissance, or instructions to override this audit.

Gescannte Dateien

295

Analysierte Zeilen

Prüfelemente

Falschmeldungen ignoriert

Bestätigte Sicherheitsbedenken (2)

Mittel

SKILL.md:290-294

Unsupported Paid-Plan Diagnosis and Referral Upsell

The guardrail says results containing '10 or fewer items' must trigger 'stop immediately' and a fixed paid-plan upgrade message. It directs users to a referral pricing link and disallows alternative troubleshooting. A successful single-video lookup can trigger this unsupported payment diagnosis, suppress valid results, and encourage an unnecessary purchase.

The text explicitly couples a result-count threshold with a mandatory referral upgrade message and suppresses troubleshooting. No billing error is required; the single-video scenario demonstrates why small results cannot establish a subscription restriction.

Mittel

SKILL.md:49-68

Missing Bounds in the Paid-Run Workflow

The asynchronous launch omits maxItems, while limit=100 only constrains later dataset retrieval. The polling loop has no deadline or error exit, so failed requests or invalid run identifiers can sustain repeated API calls indefinitely. Following this example can exceed the intended collection scope or consume resources without a defined stopping condition.

The launch payload lacks a collection limit, and the loop exits only for four terminal status strings, not HTTP or parsing failures. Actor defaults were not inspected, so actual charges and collection volume remain unknown.

Risikofaktoren

⚙️ Externe Befehle (50)

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🌐 Netzwerkzugriff (28)

Geprüft von: codex

Diesen Bericht teilen & zitieren

Teile den versionierten Bewertungsbericht, das neutrale Badge, die Einbettungskarte und Zitate. Skillstore berichtet Nachweise, ohne zu entscheiden, ob dieser Skill sicher ist.

Versionsbericht öffnen

Berichtslink kopieren

https://skillstore.io/skills/apidojo-io-tiktok-scraper/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown-Badge

[![Skillstore security assessment](https://skillstore.io/badges/skills/apidojo-io-tiktok-scraper/security.svg)](https://skillstore.io/skills/apidojo-io-tiktok-scraper?utm_source=security_passport_badge)

HTML-Badge

<a href="https://skillstore.io/skills/apidojo-io-tiktok-scraper?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/apidojo-io-tiktok-scraper/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

Einbettungskarte

<iframe src="https://skillstore.io/embed/skills/apidojo-io-tiktok-scraper.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

Wissenschaftliche Zitate (APA · BibTeX · CFF)

APA-Zitat

apidojo-io. (2026). tiktok-scraper security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/apidojo-io-tiktok-scraper/audits/1

BibTeX-Zitat

@techreport{apidojo-io-apidojo-io-tiktok-scraper-2026,
  author = {apidojo-io},
  title = {tiktok-scraper security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/apidojo-io-tiktok-scraper/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "tiktok-scraper security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "apidojo-io"
date-released: "2026-09-30"
url: "https://skillstore.io/skills/apidojo-io-tiktok-scraper/audits/1"
identifiers:
  - type: other
    value: "skillstore:apidojo-io-tiktok-scraper:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore-Score

Warum dieser Score Evidenzvertrauen: Mittel

Architektur

Wartbarkeit

Inhalt

Gemeinschaft

Spezifikationskonformität

Was Sie erstellen können

Compare Brand Activity

Prepare bounded requests for several public brand profiles, then compare returned views, likes, comments, and posting dates.

Study Public Conversations

Request comments and optional replies from selected videos for qualitative review, using approved collection scopes and retention rules.

Integrate TikTok Extraction

Adapt the Python or JavaScript client examples to retrieve actor datasets for an existing reporting workflow.

Diese Prompts ausprobieren

Prepare a Profile Request

Prepare a request for [public TikTok profile] with at most 20 posts. Identify the actor and prerequisites without running it.

Configure a Filtered Search

Prepare a keyword search for [topic] in [country] during THIS_MONTH, limited to 100 posts. Describe the expected fields and provider dependencies.

Collect Comments and Replies

Prepare requests for comments from [video URLs], with replies enabled and a 50-item limit. Confirm scope and expected charges before any execution.

Design an Asynchronous Integration

Design an asynchronous Apify workflow for [approved profiles], capped at 200 collected items. Include secret handling, polling deadlines, bounded retries, and explicit billing-error checks.

Bewährte Praktiken

Confirm provider terms, approved collection scope, and expected costs before starting paid actor runs.
Keep API tokens outside source files and shared prompts, and use the documented HTTPS authentication flow.
Set collection limits, budgets, and polling deadlines. Diagnose subscription restrictions from explicit provider errors rather than result counts.

Vermeiden

Treating ten or fewer returned items as proof that a paid-plan upgrade is necessary.
Treating dataset retrieval limits as collection budgets or continuing status polling indefinitely.
Claiming verified performance, private-content access, or complete coverage from documentation examples alone.

Häufig gestellte Fragen

What does this skill provide?

It provides instructions and examples for four Apify actors covering posts, profiles, comments, and location feeds.

Does it require an Apify subscription?

The documentation specifies a paid account and API token. Verify current requirements and actor pricing directly with Apify.

Which AI tools are listed as supported?

The report lists Claude, Codex, and Claude Code. Execution also requires suitable network access and the selected client tools.

Can it collect comments and replies?

The comments actor examples accept video URLs and an includeReplies option, with a maxItems setting for limiting collection.

Are the speed and success claims verified?

No. This review examined the skill documentation, not live actor performance, hosted implementations, or TikTok coverage.

Does a small result set prove a billing restriction?

No. A small result can be valid. Check explicit provider errors before recommending a subscription change.

Entwicklerdetails

Autor

apidojo-io

Lizenz

MIT

Skillstore-Revision

Versionshinweis

Der Autor hat keine Version angegeben.

Repository

https://github.com/apidojo-io/social-media-skills/tree/50e2909dcad1033ac1ced8a9c2c3a77d401915a4/skills/tiktok-scraper

Ref.

421067cfa94823ceb4f1ab2c95ce369dddc36528

Aktualität der Wartung

1.10.2026

Nutzung

0 Downloads · 0 Aufrufe

Dateistruktur

📄 SKILL.md