New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Jellyfin

by magnus919 in magnus919/agent-skills

Query your Jellyfin media server from the terminal — recently added media, search, item details, series navigation, next-up episodes, library browsing, server info, and user login.

MITAuto-check passed

Install Jellyfin

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

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

GitHub CLI
$ gh skill install magnus919/agent-skills jellyfin --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/jellyfin .claude/skills/jellyfin && 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
jellyfin
GitHub stars
115
Token cost
~2.8k tokens
SKILL.md length
925 words
Files
11 (incl. scripts, references)
Skills in repo
131
Repo updated
First seen
Licence
MIT

At a glance

Query your Jellyfin media server from the terminal — recently added media, search, item details, series navigation, next-up episodes, library browsing, server info, and user login.

  • Works in 3 steps: Make sure your Jellyfin server is… → Pick an authentication route → Set these environment variables
  • The user asks about Jellyfin
  • SKILL.md covers Setup, Essential Commands, Pipeline recipes and JSON and jq, plus 5 more sections
  • Runs Python scripts from its folder; calls jq; needs JELLYFIN_API_KEY and JELLYFIN_TOKEN

What it does

Jellyfin is an agent skill from magnus919/agent-skills. Query your Jellyfin media server from the terminal — recently added media, search, item details, series navigation, next-up episodes, library browsing, server info, and user login. Use when the user asks about Jellyfin, media servers, movies, TV shows, next episodes, or their media library. Do not use this skill for server installation, library management, playback control, or Emby/Plex servers.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts and reference files (for example `README.md`, `evals/evals.json` and `references/auth-and-sessions.md`). Compatibility notes: Requires Python 3.8+ and requests. Authenticate with JELLYFINAPIKEY (Dashboard → API Keys), a user access token from login, or Quick Connect; user-scoped…

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

  • The user asks about Jellyfin
  • Their media library
  • Server installation
  • Library management

Example prompts

  • “/jellyfin”

Requirements

  • Python 3
  • A credential in JELLYFIN_API_KEY
  • A credential in JELLYFIN_TOKEN
  • Compatibility (from SKILL.md): Requires Python 3.8+ and `requests`. Authenticate with JELLYFIN_API_KEY (Dashboard → API Keys), a user access token from `login`, or Quick Connect; user-scoped commands (`recent`, `next-up`, `item`, `seasons`, `episodes`) also need JELLYFIN_USER_ID or --user-id.

Workflow steps

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

  1. Make sure your Jellyfin server is running and accessible (default http://localhost:8096).
  2. Pick an authentication route
  3. Set these environment variables

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

    No URLs in SKILL.md.

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • JELLYFIN_API_KEY
    • JELLYFIN_TOKEN

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

  • Compatibility

    Requires Python 3.8+ and `requests`. Authenticate with JELLYFIN_API_KEY (Dashboard → API Keys), a user access token from `login`, or Quick Connect; user-scoped commands (`recent`, `next-up`, `item`, `seasons`, `episodes`) also need JELLYFIN_USER_ID or --user-id.

    From compatibility in the SKILL.md frontmatter.

Context cost

Jellyfin loads about 2.8k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 925 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~102
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

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). 925 words, ~2,803 tokens.

Download SKILL.mdSave it as .claude/skills/jellyfin/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
jellyfin
description
Query your Jellyfin media server from the terminal — recently added media, search, item details, series navigation, next-up episodes, library browsing, server info, and user login. Use when the user asks about Jellyfin, media servers, movies, TV shows, next episodes, or their media library. Do not use this skill for server installation, library management, playback control, or Emby/Plex servers.
compatibility
Requires Python 3.8+ and `requests`. Authenticate with JELLYFIN_API_KEY (Dashboard → API Keys), a user access token from `login`, or Quick Connect; user-scoped commands (`recent`, `next-up`, `item`, `seasons`, `episodes`) also need JELLYFIN_USER_ID or --user-id.
license
MIT
metadata.tags
jellyfin, media-server, movies, tv, episodes, recently-added, library, home-media, api-client
metadata.sources
https://api.jellyfin.org/, https://gist.github.com/nielsvanvelzen/ea047d9028f676185832e51ffaf12a6f

jellyfin — Jellyfin Media Server from the Terminal

Query recently added movies and TV episodes, search and inspect media, walk series → seasons → episodes, browse libraries, see next-up episodes, log in as a user, and check server stats — all from your Jellyfin server's REST API. Every command is read-only except login.

Setup

  1. Make sure your Jellyfin server is running and accessible (default http://localhost:8096).
  2. Pick an authentication route:
    • API key — Dashboard → API Keys → +. Administrator-level, no user identity: every user-scoped command then needs an explicit user id.
    • User token — run scripts/jellyfin login --username NAME --prompt once; it prints the values to export.
  3. Set these environment variables:
bash
export JELLYFIN_URL="http://your-server:8096"   # include protocol and port
export JELLYFIN_API_KEY="your-api-key-here"     # or JELLYFIN_TOKEN after `login`
export JELLYFIN_USER_ID="your-jellyfin-user-id" # required by recent, next-up, item, seasons, episodes

Run the bundled CLI as scripts/jellyfin. --help and --dry-run work without credentials.

How authentication works

Jellyfin wants a MediaBrowser-scheme Authorization header on every call. The login endpoint requires its Client=..., Device=..., DeviceId=..., Version=... quartet before any token exists — the server rejects POST /Users/AuthenticateByName with 400 Error processing request. otherwise. Afterwards the access token (or API key) rides the same header as Token="..."; the legacy X-Emby-Token header means the same thing and is scheduled for removal from Jellyfin 12.0. The bundled CLI sends the modern form and puts the token in exactly that one channel per request (never co-sends X-Emby-Token). See references/auth-and-sessions.md.

Essential Commands

Authentication — get a session
bash
scripts/jellyfin login --username alice --prompt          # prints JELLYFIN_* exports
echo "pw" | scripts/jellyfin login --username alice --password-stdin
scripts/jellyfin login --username alice --dry-run --json  # preview the pre-token header

login demonstrates the full researched sequence: complete pre-token MediaBrowser header → POST /Users/AuthenticateByName → capture User.Id + AccessToken → print the post-token header for reuse. It never echoes the password.

info — Server information
bash
scripts/jellyfin info              # server name, version, OS, user count
scripts/jellyfin info --json
recent — Recently added media
bash
scripts/jellyfin recent                     # last 10 items added for JELLYFIN_USER_ID
scripts/jellyfin recent --movies --limit 5  # server-side includeItemTypes filter
scripts/jellyfin recent --episodes --limit 20 --json
scripts/jellyfin recent --user-id USER_ID   # override the env var

Hits /Items/Latest with userId; the response is a bare JSON array (no Items wrapper), and groupItems merges episodes by series, so treat it as "what's new".

search — Search your media library
bash
scripts/jellyfin search --query "dune"                  # everything
scripts/jellyfin search --query "dune" --type Movie     # comma-separated types
scripts/jellyfin search --query "star trek" --type Series,Episode --limit 5 --json

Search hits /Search/Hints; results carry id (with a deprecated ItemId twin on old servers — the CLI already prefers the modern field).

Navigation — inspect items and walk series
bash
scripts/jellyfin search --query "dune" --type Movie --json   # find an item ID
scripts/jellyfin item --id ITEM_ID                           # full metadata (needs user)
scripts/jellyfin seasons --series-id SERIES_ID               # list seasons
scripts/jellyfin episodes --series-id SERIES_ID --season-id SEASON_ID
scripts/jellyfin next-up --limit 10                          # next unwatched episodes
scripts/jellyfin next-up --series-id SERIES_ID --user-id USER_ID

item, seasons, episodes, and next-up are user-scoped: they require JELLYFIN_USER_ID or --user-id and fail before any network call without one.

libraries — browse a collection
bash
scripts/jellyfin libraries                                   # library IDs and types
scripts/jellyfin browse --library-id LIBRARY_ID --type Movie --limit 50
scripts/jellyfin browse --library-id LIBRARY_ID --start-index 50   # paginate
scripts/jellyfin browse --library-id LIBRARY_ID --user-id USER_ID  # userId sent explicitly

libraries reads /Library/MediaFolders, which is admin-only — non-admin tokens get 403 and should use /UserViews (see references). browse pages /Items with startIndex/limit and passes userId when provided, since servers using non-API-key auth reject unscoped queries with 400 userId is required.

stats — Library statistics
bash
scripts/jellyfin stats    # movie, series, episode, song counts (/Items/Counts)

Pipeline recipes

Find a series, then its next unwatched episode
bash
scripts/jellyfin search --query "breaking bad" --type Series --json | jq -r '.results[0].id'
scripts/jellyfin next-up --series-id "$SERIES_ID" --user-id "$JELLYFIN_USER_ID" --json | jq -r '.items[0].name'
Page through a whole library
bash
scripts/jellyfin browse --library-id "$LIB_ID" --limit 100 --start-index 0 --json | jq -c '.items'
# loop: advance --start-index by the returned count until .total_record_count is reached
Log in and persist a session
bash
scripts/jellyfin login --username alice --prompt --json | jq -r '"\(.user_id) \(.access_token)"'

JSON and jq

Put --json before or after the subcommand. Output keys are stable snake_case: items (with id, name, type, year, series, season_number, episode_number), results, libraries, total_record_count, start_index. --dry-run emits a plan carrying dry_run, path, and params (login adds authorization_header; info composes a requests list), matching what would be sent, so jq can verify a chain before running it live. Exit codes: 0 success (including dry-run), 1 CLI/API errors, 2 argument errors. Use jq -r '.items[] | [.name, .year] | @tsv' for tabular handoff.

Show full SKILL.md (453 more words)Show less

Known Gotchas

  • JELLYFIN_URL must include protocol and port — e.g. http://192.168.1.100:8096.
  • User-scoped commands require an explicit user — recent, next-up, item, seasons, episodes refuse to run without JELLYFIN_USER_ID/--user-id. The CLI never picks an administrator for you. A missing userId on user-token requests makes the server answer 400 userId is required.
  • API keys have no user — /Users/Me answers 400 Token is not owned by a user. to API keys by design; per-user queries need an explicit user id (see references/user-scoping-and-errors.md).
  • The login 400 vs 401 trap — missing/partial MediaBrowser header → 400 with plain text Error processing request.; wrong credentials → 401. Same endpoint, different failures.
  • Response shapes differ per endpoint — /Items and /Shows/* wrap results in {Items, TotalRecordCount, StartIndex}; /Items/Latest returns a bare array; search uses a SearchHints key. Generic clients must branch (the CLI already does).
  • Recent type filtering is server-side — --movies/--episodes become includeItemTypes before limit; no local filtering.
  • NextUp needs userId on every server version — omitting it crashed servers ≤10.8 and silently scopes to the session user on ≥10.9. The CLI always sends it.
  • libraries is admin-only — /Library/MediaFolders requires an administrator token; non-admin tokens get 403.
  • Legacy auth is going away — X-Emby-Token, X-MediaBrowser-Token, and the api_key query parameter are deprecated; admins can already disable them (10.11+), and removal targets 12.0. Prefer the modern Authorization header the CLI sends.
  • Lazy auth — --help and --dry-run work without credentials; dry-run never touches the network.

When to use

Use this skill for read-only interaction with a running Jellyfin server: discovery of what's new, searching and inspecting items, walking series and seasons, next-up planning, library inventories, and obtaining a user session via login or Quick Connect.

When not to use

Do not use this skill for server installation or administration (installing Jellyfin or Emby, editing libraries, managing users) — every bundled command is read-only except login. It does not target Plex or Kodi (different APIs — use their own tools), and it is not a playback remote: route streaming or remote-control automation to Jellyfin's official clients.

Reference Files

FileUse it for
references/auth-and-sessions.mdMediaBrowser header scheme, login flow, token channels, legacy deprecation, error signatures
references/endpoint-catalog.mdEvery read endpoint's parameters, response shapes, image URLs, pagination loop
references/user-scoping-and-errors.mdThe userId requirement matrix, API-key identity quirks, 400-vs-404 diagnosis
references/gotchas-field-guide.mdWire-level failure signatures, version-drift ledger, mock shapes
references/worked-recipes.mdMulti-step curl/jq and CLI recipes: login → latest, libraries → browse, search → seasons → episodes
references/quick-connect.mdPasswordless Quick Connect login flow

Available Scripts and Prerequisites

  • scripts/jellyfin — the bundled Python CLI (--json, --dry-run, lazy auth). Imports only the standard library and requests.
  • scripts/test_jellyfin_cli.py — offline test suite (pytest + unittest compatible); all HTTP behavior is mocked, zero network egress.
  • Requires Python 3.8+ and requests. A running Jellyfin server (10.8+ assumed; tested behaviors anchored to the 12.0-era OpenAPI spec). No service is started by this skill.

© 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 10 other files (scripts, references) in jellyfin of magnus919/agent-skills.

  • SKILL.md
  • README.md
  • evals/evals.json
  • references/auth-and-sessions.md
  • references/endpoint-catalog.md
  • references/gotchas-field-guide.md
  • references/quick-connect.md
  • references/user-scoping-and-errors.md
  • references/worked-recipes.md
  • scripts/jellyfin
  • scripts/test_jellyfin_cli.py

Open the folder on GitHubat commit 22b4723

Compare with similar skills

Jellyfin 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.

Jellyfin compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Jellyfin this skillmagnus919/agent-skills115—~2.8kAutomated safety check: PassMIT
Terminal Openeraffaan-m/ECC277k—~635Automated safety check: PassMIT
Terminal Opsaffaan-m/ECC277k2 repos~750Automated safety check: PassMIT
Terminal Opsaffaan-m/ECC276k—~439Automated safety check: PassMIT
Terminal Opsaffaan-m/ECC276k—~323Automated safety check: PassMIT
Terminal Bench Looppaperclipai/paperclip100k—~6.3kAutomated safety check: PassMIT

Similar skills

  • Terminal Opener

    affaan-m/ECC

    Open an executable and its argument array in a visible terminal window through a reusable, shell-free launch plan with dry-run, JSON, capability detection, detached fallback, and standalone recovery…

    277k GitHub stars~635 tokensUpdated today
    Marketing & SEOAuto-check passed

  • Terminal Ops

    affaan-m/ECC

    Evidence-first repo execution workflow for ECC. An agent skill from affaan-m/ECC.

    277k GitHub starsUsed in 2 repos~750 tokens
    Testing & QAAuto-check passed

  • Terminal Ops

    affaan-m/ECC

    ECCのための証拠優先のリポジトリ実行ワークフロー。ユーザーがコマンドの実行、リポジトリの確認、CIの失敗のデバッグ、正確な実行と検証の証明を伴う狭い修正のプッシュを必要とする場合に使用する。

    276k GitHub stars~439 tokensUpdated yesterday
    DevelopmentAuto-check passed

  • Terminal Ops

    affaan-m/ECC

    基于证据优先的仓库执行工作流，适用于ECC。当用户需要运行命令、检查仓库、调试CI失败或推送带有精确执行和验证证明的窄修复时使用。

    276k GitHub stars~323 tokensUpdated yesterday
    DevelopmentAuto-check passed

  • Terminal Bench Loop

    paperclipai/paperclip

    Run one Terminal-Bench task through a bounded Paperclip smoke/diagnosis/fix loop.

    100k GitHub stars~6.3k tokensUpdated today
    Auto-check passed

  • Terminal Screenshot Capture

    QwenLM/qwen-code

    Drives a CLI through a TypeScript scenario and saves terminal screenshots at each step, so pull requests that change command output can be checked visually.

    28k GitHub stars~2k tokensUpdated today
    Testing & QAAuto-check passed

More from magnus919/agent-skills

All 131 skills in this repo

  • Artifact Pyramids

    magnus919/agent-skills

    Organize durable agent research outputs as summaries, analysis, and evidence dossiers.

    119 GitHub stars~2.7k tokensUpdated today
    Auto-check passed

  • Ascii City Engine

    magnus919/agent-skills

    Build portable, first-person colored ASCII city engines and small GIS-derived city packs.

    119 GitHub stars~1.1k tokensUpdated today
    Auto-check passed

  • Color Management

    magnus919/agent-skills

    Manage color workflows with ICC profiles, working spaces, gamut mapping, and color science.

    119 GitHub stars~2.6k tokensUpdated today
    Auto-check: notes

  • Data Scientist

    magnus919/agent-skills

    A skill your agent uses for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research…

    119 GitHub stars~4.1k tokensUpdated today
    Auto-check passed

  • Docker Compose

    magnus919/agent-skills

    Use Docker Compose to define, run, debug, and harden multi-container applications.

    119 GitHub stars~2k tokensUpdated today
    Auto-check: notes

  • Fpga Development

    magnus919/agent-skills

    Design, review, simulate, and verify FPGA logic using explicit RTL contracts, clock and reset models, CDC analysis, timing constraints, and reproducible implementation evidence.

    119 GitHub stars~2.7k tokensUpdated today
    Auto-check passed

Questions about Jellyfin

What does Jellyfin do?

Query your Jellyfin media server from the terminal — recently added media, search, item details, series navigation, next-up episodes, library browsing, server info, and user login. Jellyfin is an agent skill from magnus919/agent-skills. Query your Jellyfin media server from the terminal — recently added media, search, item details, series navigation, next-up episodes, library browsing, server info, and user login.

When should I use Jellyfin?

Jellyfin fits situations like: the user asks about Jellyfin; their media library; server installation; library management.

How do I install Jellyfin in Claude Code?

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

How do I install Jellyfin in Codex?

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

Can I use Jellyfin 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 jellyfin -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jellyfin, .gemini/skills/jellyfin, .github/skills/jellyfin and .opencode/skills/jellyfin in your project.

What does Jellyfin need to run?

Going by SKILL.md and its folder, Jellyfin needs Python for the scripts in its folder, the command-line tools its instructions call (jq) and credentials named JELLYFIN_API_KEY and JELLYFIN_TOKEN. Our summary lists: Python 3; A credential in JELLYFIN_API_KEY; A credential in JELLYFIN_TOKEN. Compatibility (from SKILL.md): Requires Python 3.8+ and `requests`. Authenticate with JELLYFIN_API_KEY (Dashboard → API Keys), a user access token from `login`, or Quick Connect; user-scoped commands (`recent`, `next-up`, `item`, `seasons`, `episodes`) also need JELLYFIN_USER_ID or --user-id..

Does Jellyfin access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Jellyfin 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 Jellyfin use?

Jellyfin 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 Jellyfin use?

About 2.8k tokens (SKILL.md is roughly 11k 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 12k tokens, read only when the agent opens those files.

What are the alternatives to Jellyfin?

Skills that share tags, products or a category with Jellyfin: Terminal Opener (affaan-m/ECC, 277k stars), Terminal Ops (affaan-m/ECC, 277k stars), Terminal Ops (affaan-m/ECC, 276k stars) and Terminal Ops (affaan-m/ECC, 276k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jellyfin?

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.