📦

connector-tmdb

Name: connector-tmdb
Author: caffeinelabs

v0.1.2 Inhaltsrevision r1 Sicher ⚙️ Externe Befehle🌐 Netzwerkzugriff🔑 Umgebungsvariablen

Build TMDb Movie and TV Features

Movie and TV integrations often fail because generated clients hide authentication, response shapes, and unsupported operations. This skill gives Caffeine developers a tested implementation path for catalog reads, credential handling, and service limits.

Unterstützt: Claude Codex Code(CC)

🥈 82 Silber

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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 "connector-tmdb" from https://skillstore.io/skills/caffeinelabs-connector-tmdb.md and its manifest at https://skillstore.io/api/skills/caffeinelabs-connector-tmdb/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/caffeinelabs-connector-tmdb.md Signiertes manifest GET /api/skills/caffeinelabs-connector-tmdb/manifest Signiertes lockfile GET /api/skills/caffeinelabs-connector-tmdb/lockfile

Testen

„connector-tmdb“ wird verwendet. I need a movie search endpoint for a Caffeine app.

Erwartetes Ergebnis:

A backend plan with a protected bearer token, a bounded search request, optional-field normalization, and a stable movie result shape.

„connector-tmdb“ wird verwendet. Which TMDb features should my first release avoid?

Erwartetes Ergebnis:

Avoid account writes, ratings, list creation, and session creation until the generated request body is fixed.
Avoid movie recommendations because successful responses are decoded incorrectly.
Use catalog reads, TV recommendations, search, discover, and trending feeds instead.

Sicherheitsaudit

Sicher

v1 • 23.9.2026 Versionsbericht öffnen

All 127 static findings are false positives. They match Markdown code spans, documented TMDb URLs, credential terms, and Motoko identifiers in SKILL.md. No executable shell use, environment access, reconnaissance, or unauthorized network behavior is evidenced.

Gescannte Dateien

385

Analysierte Zeilen

Prüfelemente

Falschmeldungen ignoriert

Risikofaktoren

⚙️ Externe Befehle (50)

🌐 Netzwerkzugriff (3)

SKILL.md:25 SKILL.md:133 SKILL.md:343

🔑 Umgebungsvariablen (2)

SKILL.md:60 SKILL.md:63

Das letzte abgeschlossene statische und semantische Audit erkannte keine bestätigten Sicherheitsbefunde. Dies beweist nicht, dass der Skill keine Nebenwirkungen hat.

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/caffeinelabs-connector-tmdb/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown-Badge

[![Skillstore security assessment](https://skillstore.io/badges/skills/caffeinelabs-connector-tmdb/security.svg)](https://skillstore.io/skills/caffeinelabs-connector-tmdb?utm_source=security_passport_badge)

HTML-Badge

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

Einbettungskarte

<iframe src="https://skillstore.io/embed/skills/caffeinelabs-connector-tmdb.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

caffeinelabs. (2026). connector-tmdb security audit report (audit version 1) [Author version 0.1.2]. Skillstore. https://skillstore.io/skills/caffeinelabs-connector-tmdb/audits/1

BibTeX-Zitat

@techreport{caffeinelabs-caffeinelabs-connector-tmdb-2026,
  author = {caffeinelabs},
  title = {connector-tmdb security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/caffeinelabs-connector-tmdb/audits/1},
  note = {Author version 0.1.2}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "connector-tmdb security audit report (audit version 1)"
version: "0.1.2"
type: report
authors:
  - name: "caffeinelabs"
date-released: "2026-09-23"
url: "https://skillstore.io/skills/caffeinelabs-connector-tmdb/audits/1"
identifiers:
  - type: other
    value: "skillstore:caffeinelabs-connector-tmdb:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore-Score

Warum dieser Score Evidenzvertrauen: Mittel

Architektur

100

Wartbarkeit

Inhalt

Gemeinschaft

100

Spezifikationskonformität

Was Sie erstellen können

Create a movie search

Build a search endpoint that queries TMDb, maps optional fields, and returns a stable movie record to the frontend.

Launch a catalog home page

Combine now-playing, popular, trending, or discover reads into efficient landing-page feeds with bounded response sizes.

Plan a TV detail experience

Use TV detail, credits, season, episode, and recommendation operations while avoiding unsupported movie and account writes.

Diese Prompts ausprobieren

Start with a movie search

Show me the smallest Caffeine backend design for searching movies with tmdb-client. Include the required credential shape and a compact response record.

Add a detail page

Design a Motoko movie detail endpoint using tmdb-client. Include credits, images, and videos through one efficient request where supported.

Build a TV catalog feed

Create a TV catalog plan using search, popular, trending, discover, and recommendation operations. Mark unsupported operations and explain the response mapping.

Review integration risks

Audit this proposed TMDb integration against the connector guidance. Check credentials, replication mode, pagination, response limits, rate limits, and unsupported writes.

Bewährte Praktiken

Store long-lived tokens in protected actor state and restrict credential updates to authorized callers.
Normalize optional TMDb fields at the actor boundary and bound response sizes for each endpoint.
Cache configuration data, combine related detail resources, clamp page values, and back off after rate limits.

Vermeiden

Do not hand-roll ic.http_request calls when the generated client provides the required TMDb operation.
Do not expose tokens through query methods, logs, errors, or untrusted frontend parameters.
Do not build account writes or movie recommendations as working features before fixing their generated-client defects.

Häufig gestellte Fragen

Which credential does the client support?

Use a TMDb v4 read-access token with the generated bearer configuration. The v3 API key query parameter is not supported.

Can I store the token in the frontend?

Avoid frontend storage for a production app. Keep the token in protected actor state and authorize the setter.

Which TMDb operations work reliably?

Catalog reads such as search, details, trending, discover, now playing, and most TV reads are the intended surface.

Why should I avoid account writes?

The generated request body wraps payloads incorrectly, so twelve body-carrying operations are rejected by TMDb.

Why does movieRecommendations fail?

Its generated decoder expects a primitive, while TMDb returns a paginated object. TV recommendations use a normal generated type.

How should I handle images and limits?

Prepend the configured TMDb image base to relative paths, clamp pages to 500, bound response sizes, and back off after 429 responses.

Entwicklerdetails

Autor

caffeinelabs

Lizenz

MIT

Autorenversion

v0.1.2

Skillstore-Revision

Repository

https://github.com/caffeinelabs/skills/tree/c6bcba620fa151e28f2366205b35703d1c1e7864/skills/connector-tmdb

Ref.

2aa351cb09c29b7287d263bd8ea81e9bee3b2a61

Aktualität der Wartung

30.9.2026

Nutzung

0 Downloads · 0 Aufrufe

Dateistruktur

📄 SKILL.md