📦

connector-tmdb

Name: connector-tmdb
Author: caffeinelabs

v0.1.2 Ревизия содержимого r1 Безопасно ⚙️ Внешние команды🌐 Доступ к сети🔑 Переменные окружения

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.

Поддерживает: Claude Codex Code(CC)

🥈 82 Серебро

Maintain this Skill? Claim it 🥈 82 Серебро

Установить с помощью моего Агента

Скопируйте этот запрос в своего Агента. Он содержит каноническую страницу Skill и манифест.

Запрос агента

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.

Ваш Агент по-прежнему должен показать план и запросить все подтверждения, требуемые политикой безопасности.

Ресурсы для AI-агентов

Используйте эти ссылки, когда AI-агенту, crawler или script нужен чистый контекст вместо полной страницы.

Markdown-детали GET /skills/caffeinelabs-connector-tmdb.md Подписанный manifest GET /api/skills/caffeinelabs-connector-tmdb/manifest Подписанный lockfile GET /api/skills/caffeinelabs-connector-tmdb/lockfile

Протестировать

Использование «connector-tmdb». I need a movie search endpoint for a Caffeine app.

Ожидаемый результат:

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

Использование «connector-tmdb». Which TMDb features should my first release avoid?

Ожидаемый результат:

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.

Аудит безопасности

Безопасно

v1 • 23.09.2026 Открыть версионный отчет

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.

Просканировано файлов

385

Проанализировано строк

Пункты проверки

Ложные срабатывания проигнорированы

Факторы риска

⚙️ Внешние команды (50)

🌐 Доступ к сети (3)

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

🔑 Переменные окружения (2)

SKILL.md:60 SKILL.md:63

Последний завершенный статический и семантический аудит не обнаружил подтвержденных проблем безопасности. Это не доказывает отсутствие побочных эффектов у навыка.

Аудитор:: codex

Поделиться и цитировать этот отчет

Делитесь версионным отчетом об оценке, нейтральным значком, встраиваемой карточкой и цитатами. Skillstore публикует доказательства, не решая, безопасен ли этот Skill.

Открыть версионный отчет

Копировать ссылку на отчёт

https://skillstore.io/skills/caffeinelabs-connector-tmdb/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Значок Markdown

[![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)

Значок HTML

<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>

Встраиваемая карточка

<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>

Академические ссылки (APA · BibTeX · CFF)

Цитата APA

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

Цитата BibTeX

@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"

Оценка Skillstore

Почему такая оценка Достоверность доказательств: Средний

Архитектура

100

Сопровождаемость

Контент

Сообщество

100

Соответствие спецификации

Что вы можете построить

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.

Попробуйте эти промпты

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.

Лучшие практики

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.

Избегать

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.

Часто задаваемые вопросы

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.

Сведения для разработчиков

Автор

caffeinelabs

Лицензия

MIT

Версия автора

v0.1.2

Ревизия Skillstore

Репозиторий

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

Ссылка

2aa351cb09c29b7287d263bd8ea81e9bee3b2a61

Актуальность поддержки

30.09.2026

Использование

0 загрузок · 0 просмотров

Структура файлов

📄 SKILL.md