hdhr-jellyfin-livetv-setup

hdhr-jellyfin-livetv-setup is a skill for Claude Code, Codex from Knuckles-Team/hdhomerun-mcp. It costs 191 tokens per session (2,129 once invoked), scanned A, original, MIT.

A setup workflow for connecting an HDHomeRun TV tuner to Jellyfin Live TV, including free XMLTV programme-guide data. Jellyfin is a media server, and XMLTV is a standard format for TV listings.

In plain words
What is it for?
Use it to configure the tuner host, obtain guide data, map tuner channels to listings, and validate live television in Jellyfin.
Why use it?
It covers the full setup from finding the tuner and adding it to Jellyfin through matching channels and checking live playback, including cases without a Schedules Direct subscription.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to configure the tuner host, obtain guide data, map tuner channels to listings, and validate live television in Jellyfin.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Knuckles-Team/hdhomerun-mcp --skill hdhr-jellyfin-livetv-setup
Clone the repo
git clone --depth 1 https://github.com/Knuckles-Team/hdhomerun-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hdhr-jellyfin-livetv-setup

README.md
[![agentmods](https://agentmods.dev/badge/skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup/github.svg)](https://agentmods.dev/skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup)
Your own site
<a href="https://agentmods.dev/skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup"><img src="https://agentmods.dev/badge/skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hdhr-jellyfin-livetv-setup

Your own site · 80×15
<a href="https://agentmods.dev/skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup"><img src="https://agentmods.dev/badge/skills/knuckles-team/hdhomerun-mcp/hdhr-jellyfin-livetv-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 191 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,129 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00191 $0.02129
Opus 5 $0.00096 $0.01064
Sonnet 5 $0.00038 $0.00426
Haiku 4.5 $0.00019 $0.00213

Measured 11d ago against content hash ed05e37f1bb0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

hdhr-jellyfin-livetv-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

hdhomerun_mcp/skills/hdhr-jellyfin-livetv-setup/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

HDHomeRun -> Jellyfin Live TV Setup

A verified, four-step workflow to wire an HDHomeRun tuner into Jellyfin Live TV, including free (non-Schedules-Direct) guide data. Every step below was run against a real HDHomeRun FLEX 4K (DeviceID 10ACFCDE) and a real Jellyfin 10.11.11 server serving an Austin, TX OTA market.

When to use

  • Onboarding a new HDHomeRun tuner into an existing Jellyfin server.
  • The user has no Schedules Direct subscription and wants free XMLTV guide data.
  • Diagnosing "channels show up but no guide data" or "tuner add fails" issues.

When NOT to use

  • Fixing the jellyfin-mcp dynamic-router bug itself (see Gotchas) — out of scope for this package; file/track it against jellyfin-mcp.
  • SiliconDust cloud DVR recording rules — that's Jellyfin's own DVR scheduling once Live TV is wired (Jellyfin /LiveTv/Timers etc.), a separate system from the SiliconDust cloud rules in hdhr-dvr-ops.

Prerequisites

  • A reachable HDHomeRun tuner (hdhr-http-api-ops's discover action confirms this) with its DeviceID and TunerCount known.
  • A Jellyfin server with an API key (X-Emby-Token). If you don't have one, the jellyfin-mcp MCP server's jell__system tool exposes a get_keys action that returns one.
  • Optional: a free XMLTV guide URL for US OTA/diginet coverage — verified working: https://epgshare01.online/epgshare01/epg_ripper_US_LOCALS1.xml.gz (confirmed to include call-sign-matched entries like KVUE-DT, KLRU-DT, KEYE-DT, KAKW-DT, KNVA-DT, KBVO-DT/CD, KION-DT).

Execution

Steps 1 and 2 are independent of each other and can run in parallel; step 3 depends on both (it needs the tuner's lineup from step 1 and the XMLTV channel list pulled in by step 2); step 4 depends on step 3.

  • In parallel: Step 1 (add tuner host) and Step 2 (add XMLTV guide data).
  • Then: Step 3 (channel mapping), once both above have completed.
  • Then: Step 4 (validate playback).

If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.

Read the full file on GitHub · 151 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 151 lines · 191 tokens per session scan A ed05e37f1bb0

Subscribe to this mod's changes

hdhr-jellyfin-livetv-setup is a skill published in the GitHub repository Knuckles-Team/hdhomerun-mcp (0 stars, last pushed 15d ago), licensed MIT. It adds 191 tokens to every session and 2,129 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

intent-recognition

Classifies automation requests using two decisions: anchor (which primitive owns the top-level control flow — workflow-anchored, agent-anchored, needs-clarification, or out-of-scope) and embedsother (whether the other primitive appears embedded inside — an agent step inside a workflow, or a workflow invoked as an…

n8n-io/n8n · 146 tokens

tao-run-deft-aoi

Run the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models: baseline evaluate, RCA, Cosmos AnomalyGen / AMP synthetic defects, k-NN mining, retraining, and deployment gating against a customer-defined primary metric and optional constraints. Use only when the request…

NVIDIA-TAO/tao-skill-bank · 155 tokens

freecad-scripts

Expert skill for writing FreeCAD Python scripts, macros, and automation. Use when asked to create FreeCAD models, parametric objects, Part/Mesh/Sketcher scripts, workbench tools, GUI dialogs with PySide, Coin3D scenegraph manipulation, or any FreeCAD Python API task. Covers FreeCAD scripting basics, geometry creation…

boshi-xixixi/TraeSkill · 85 tokens

legacy-circuit-mockups

Generate breadboard circuit mockups and visual diagrams using HTML5 Canvas drawing techniques. Use when asked to create circuit layouts, visualize electronic component placements, draw breadboard diagrams, mockup 6502 builds, generate retro computer schematics, or design vintage electronics projects. Supports 555…

boshi-xixixi/TraeSkill · 111 tokens

memory-merger

Merges mature lessons from a domain memory file into its instruction file. Syntax: /memory-merger >domain [scope] where scope is global (default), user, workspace, or ws.

boshi-xixixi/TraeSkill · 49 tokens

mspm0-ccs

Tool-neutral CLI agent rules for TI MSPM0 development with Code Composer Studio, Keil/uVision, CMake/GCC/OpenOCD, SysConfig, and DriverLib. Use when an agent needs to inspect or modify MSPM0 projects, edit .syscfg configuration, avoid generated SysConfig/build files, use DriverLib APIs, validate SysConfig output…

Ibook000/ibook-skill · 101 tokens