Agent skill

Trakt

by magnus919 in magnus919/agent-skills

Discover and compare public Trakt.tv trending, popular, and anticipated movies and shows from the terminal.

MITAuto-check passedBackend & APIs

Install Trakt

skills CLI
$ npx skills add magnus919/agent-skills --skill trakt -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install magnus919/agent-skills trakt --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/trakt .claude/skills/trakt && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
trakt
GitHub stars
115
Token cost
~1.8k tokens
SKILL.md length
748 words
Files
8 (incl. scripts, references)
Skills in repo
131
Repo updated
First seen
Licence
MIT

At a glance

Discover and compare public Trakt.tv trending, popular, and anticipated movies and shows from the terminal.

  • Works in 3 steps: Run trakt --json movie trending --limit… → Unwrap .movie, retaining .watchers as… → Pass an available .movie.ids.tmdb or…
  • Personal history
  • SKILL.md covers Setup and authentication, Essential commands, Pipeline recipes and JSON and pagination, plus 5 more sections
  • Runs Python scripts from its folder; calls jq

What it does

Trakt is an agent skill from magnus919/agent-skills. Discover and compare public Trakt.tv trending, popular, and anticipated movies and shows from the terminal. Do not use this skill for personal history, watchlist, collection, or list management; the bundled CLI has no user-scoped operations. Use tmdb for catalog metadata, credits, images, and provider lookups.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `README.md`, `evals/evals.json` and `references/auth-and-request-contract.md`). Compatibility notes: Requires TRAKTCLIENTID, Python 3.8+, and requests. Public discovery reads use an application Client ID; the CLI does not implement OAuth.

It sits in Backend & APIs. The repository describes itself as: Curated collection of AI agent skills for Hermes and other agent frameworks. The licence is MIT.

When your agent uses it

  • Personal history
  • List management
  • The bundled CLI has no user-scoped operations

Example prompts

  • “/trakt”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Requires TRAKT_CLIENT_ID, Python 3.8+, and requests. Public discovery reads use an application Client ID; the CLI does not implement OAuth.

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Run trakt --json movie trending --limit 20.
  2. Unwrap .movie, retaining .watchers as the watch signal.
  3. Pass an available .movie.ids.tmdb or .movie.ids.imdb to a downstream tool; do not assume a missing ID can be synthesized.

What it can do on your machine

Read from SKILL.md and the folder at commit 22b4723. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • trakt.tv

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires TRAKT_CLIENT_ID, Python 3.8+, and requests. Public discovery reads use an application Client ID; the CLI does not implement OAuth.

    From compatibility in the SKILL.md frontmatter.

Context cost

Trakt loads about 1.8k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 80 tokens; SKILL.md has 748 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~80
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from magnus919/agent-skills at commit 22b4723, republished under its MIT licence (© magnus919). 748 words, ~1,780 tokens.

Download SKILL.mdSave it as .claude/skills/trakt/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
trakt
description
Discover and compare public Trakt.tv trending, popular, and anticipated movies and shows from the terminal. Do not use this skill for personal history, watchlist, collection, or list management; the bundled CLI has no user-scoped operations. Use `tmdb` for catalog metadata, credits, images, and provider lookups.
compatibility
Requires TRAKT_CLIENT_ID, Python 3.8+, and requests. Public discovery reads use an application Client ID; the CLI does not implement OAuth.
license
MIT
metadata.tags
trakt, media-discovery, movies, tv-shows, trending, api-client
metadata.sources
https://docs.trakt.tv/docs/required-headers

Trakt media discovery

Use this skill to inspect what is being watched, what is broadly popular, and what is anticipated. It is a read-only discovery surface, not a catalog metadata service.

Setup and authentication

Register an app at Trakt OAuth applications and export its Client ID:

sh
export TRAKT_CLIENT_ID="YOUR_TRAKT_CLIENT_ID"

Every request must send trakt-api-key: <client id> together with the mandatory companion header trakt-api-version: 2, plus JSON content type and a descriptive User-Agent. Public discovery endpoints use the key header, not Authorization: Bearer. OAuth bearer tokens are for endpoints marked OAuth-required or for user-scoped lists, history, collection, watchlist, and mutations; a bearer token does not replace the key/version pair.

Essential commands

All six discovery commands accept --page N alongside --limit N; both default to 1 and 10 respectively and are forwarded to the API's query string.

sh
trakt movie trending --limit 20
trakt tv trending --limit 20 --page 2 --json

Trending responses wrap each media object in movie or show and include a watchers count.

sh
trakt movie popular --limit 25 --json
trakt tv popular --page 2 --limit 25

Popular is a ranking based on rating percentage and number of ratings, not a personalized recommendation.

Anticipated: upcoming interest
sh
trakt movie anticipated --page 3 --limit 10
trakt tv anticipated --limit 10 --json

Anticipated reflects list appearances and upcoming interest. It is not the same as a release calendar.

Global flags can appear before or after the resource: --json, --dry-run, --quiet, and --verbose.

Pipeline recipes

  1. Run trakt --json movie trending --limit 20.
  2. Unwrap .movie, retaining .watchers as the watch signal.
  3. Pass an available .movie.ids.tmdb or .movie.ids.imdb to a downstream tool; do not assume a missing ID can be synthesized.
sh
trakt --json movie trending --limit 20 |
  jq '.movies[] | {title: (.movie.title // .title), year: (.movie.year // null), watchers: (.watchers // null), ids: (.movie.ids // .ids)}'
Compare discovery signals

Fetch matching pages of trending, popular, and anticipated (e.g. --page 1 for each), then label each dataset before combining it. Trending is recent watching, popular is broad ranking, and anticipated is upcoming interest.

Page through anticipated until the feed ends

Loop --page, read pagination.page_count from JSON output to pick the stop page, and break early if a page returns no items:

sh
for p in $(seq 1 "$(trakt --json movie anticipated --page 1 --limit 100 | jq -r '.pagination.page_count')"); do
  trakt --json movie anticipated --page "$p" --limit 100 |
    jq --arg p "$p" '{page: ($p|tonumber), pagination: .pagination,
                      movies: [.movies[] | {title: (.movie.title // .title), year: (.movie.year // null)}]}'
done

Keep per-page output as labeled NDJSON; merge afterwards. On 429, wait out Retry-After before continuing the loop.

JSON and pagination

--json emits an object with a movies or shows array (trending entries retain their wrapper) plus a pagination object whose keys mirror the API's X-Pagination-* headers: page, limit, page_count, item_count. Pagination keys are ints when the headers were present and the object is empty {} when they were absent, so jq like .pagination.page_count // 1 degrades safely. Human output appends a Page N of M line when the headers are present and stays silent otherwise. The API defaults to page 1 with limit 10 for compatibility; set both explicitly for reproducible automation, and stop at page_count rather than assuming a short page is the end.

Show full SKILL.md (310 more words)Show less

Known gotchas

  • Header pair is mandatory: sending trakt-api-key without trakt-api-version: 2 (or vice versa) can yield an invalid-request/authentication-style failure. The bundled script injects both on every live request.
  • 401 versus 403: 401 commonly indicates an OAuth requirement or invalid authorization; 403 indicates an invalid or unapproved application key. Do not retry either blindly.
  • Rate limits: on 429, honor Retry-After and inspect X-Ratelimit. Use bounded retries; transient 502/503/504 responses may be retried with backoff.
  • OAuth refresh: access tokens last seven days and refresh tokens are single-use. Replace the stored refresh token after a successful refresh; invalid_grant requires reauthorization.
  • Trakt is not TMDb: Trakt IDs and discovery rankings are not TMDb metadata. Use the tmdb skill for credits, images, provider metadata, and catalog enrichment.
  • Trending shape: read .movie or .show before title/IDs, while preserving watchers.
  • Pagination is per invocation: one CLI call fetches exactly one page (--page); loop invocations reading pagination.page_count rather than expecting the script to follow links itself.

When to use

Use Trakt for current watching signals, broad popularity, anticipated interest, and identifiers that feed a media workflow.

When not to use

Do not use this CLI to read or update personal history, watchlists, collections, or lists. It implements neither those commands nor OAuth; supplying a token does not enable them. Explain the limitation and use the Trakt website or a separately implemented, authenticated client for personal operations. Do not invent CLI commands or claim a requested update succeeded. Use tmdb for catalog metadata, credits, images, and provider availability.

Reference files

FileTopic
references/auth-and-request-contract.mdRequired headers, OAuth boundary, errors, and rate limits
references/discovery-endpoints.mdEndpoint semantics, filters, response shapes, and pagination
references/recipes-and-operations.mdPipelines, jq normalization, and operational handling

Available script and prerequisites

  • scripts/trakt is an executable Python CLI using only stdlib and requests.
  • --dry-run works without a Client ID and never performs network I/O.
  • Live discovery requires TRAKT_CLIENT_ID; tests are mock-only.

© magnus919, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references) in trakt of magnus919/agent-skills.

  • SKILL.md
  • README.md
  • evals/evals.json
  • references/auth-and-request-contract.md
  • references/discovery-endpoints.md
  • references/recipes-and-operations.md
  • scripts/test_trakt.py
  • scripts/trakt

Open the folder on GitHubat commit 22b4723

Compare with similar skills

Trakt next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Trakt compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Trakt this skillmagnus919/agent-skills115—~1.8kAutomated safety check: PassMIT
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Nestjs Best Practicesrolling-scopes/rsschool-app10k6 repos~1.2kAutomated safety check: PassMIT
Sub2API AdminWei-Shaw/sub2api44k1 repos~717Automated safety check: PassLGPL-3.0
Firecrawl Build Onboardingfirecrawl/firecrawl190k1 repos~1.4kAutomated safety check: NotesISC
Obsidian BasesAtmosphere/atmosphere3.8k22 repos~3.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Trakt

What does Trakt do?

Discover and compare public Trakt.tv trending, popular, and anticipated movies and shows from the terminal. Trakt is an agent skill from magnus919/agent-skills.tv trending, popular, and anticipated movies and shows from the terminal.

When should I use Trakt?

Trakt fits situations like: personal history; list management; the bundled CLI has no user-scoped operations.

How do I install Trakt in Claude Code?

Run `npx skills add magnus919/agent-skills --skill trakt -a claude-code`. Or copy the skill folder (trakt in magnus919/agent-skills) into .claude/skills/trakt in your project. Claude Code loads it when a task matches its description.

How do I install Trakt in Codex?

Run `npx skills add magnus919/agent-skills --skill trakt -a codex`. Or copy the skill folder (trakt in magnus919/agent-skills) into .agents/skills/trakt in your project. Codex loads it when a task matches its description.

Can I use Trakt in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add magnus919/agent-skills --skill trakt -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trakt, .gemini/skills/trakt, .github/skills/trakt and .opencode/skills/trakt in your project.

What does Trakt need to run?

Going by SKILL.md and its folder, Trakt needs Python for the scripts in its folder and the command-line tools its instructions call (jq). Our summary lists: Python 3. Compatibility (from SKILL.md): Requires TRAKT_CLIENT_ID, Python 3.8+, and requests. Public discovery reads use an application Client ID; the CLI does not implement OAuth..

Does Trakt access the network?

SKILL.md names 1 domain. As links in the text: trakt.tv. This is read from the text; nothing was executed.

Is Trakt safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Trakt use?

Trakt is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Trakt use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Trakt?

Skills that share tags, products or a category with Trakt: Configuring Horizon (coollabsio/coolify, 63k stars), Nestjs Best Practices (rolling-scopes/rsschool-app, 10k stars), Sub2API Admin (Wei-Shaw/sub2api, 44k stars) and Firecrawl Build Onboarding (firecrawl/firecrawl, 190k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Trakt?

magnus919 (a GitHub user) maintains it in magnus919/agent-skills, which has 115 GitHub stars. The repository holds 131 skills in this directory. The repository was last updated on October 10, 2026.

Source: magnus919/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.