linear-finish-install
tjcages/linear · Agent Skill
Complete Linear tracking installation by writing always-on rules and verifying Linear MCP authentication.
Jump to install ↓Overview
| Publisher | |
|---|---|
| Repository | tjcages/linear ↗ |
| Skill folder | linear-finish-install |
| Stars | 10 |
| Bundled files | 5 |
| License | MIT |
| Last updated | July 29, 2026 |
| Links | Skill source ↗ · Repository ↗ |
Mozgi check
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Installation
A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.
Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.
Install the “linear-finish-install” skill from mozgi.io (https://mozgi.io/skills/tjcages-linear-finish-install/) for me. 1. Download the archive: https://mozgi.io/skills/tjcages-linear-finish-install/download If it fails, take the skill folder from the source: https://github.com/tjcages/linear/tree/main/skills/linear-finish-install 2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me. 3. Put the “linear-finish-install” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.). 4. Make sure <skills folder>/linear-finish-install/SKILL.md exists. 5. Briefly tell me what this skill does and offer to try it on my task. If you cannot do a step yourself, tell me what to click or type.
git clone --depth 1 --branch main https://github.com/tjcages/linear.git /tmp/linear mkdir -p .claude/skills cp -r /tmp/linear/skills/linear-finish-install .claude/skills/linear-finish-install
Restart Claude Code — the skill appears in the list; call it manually with /linear-finish-install. For all projects use ~/.claude/skills.
git clone --depth 1 --branch main https://github.com/tjcages/linear.git /tmp/linear mkdir -p .agents/skills cp -r /tmp/linear/skills/linear-finish-install .agents/skills/linear-finish-install
Codex looks for skills in .agents/skills from the current folder up to the repo root; call one with /skills or $linear-finish-install. For all projects use ~/.agents/skills.
git clone --depth 1 --branch main https://github.com/tjcages/linear.git /tmp/linear mkdir -p .cursor/skills cp -r /tmp/linear/skills/linear-finish-install .cursor/skills/linear-finish-install
Cursor picks the skill up on start; call it with “/” in Agent chat. Cursor also reads .claude/skills and .agents/skills. For all projects use ~/.cursor/skills.
git clone --depth 1 --branch main https://github.com/tjcages/linear.git /tmp/linear mkdir -p .gemini/skills cp -r /tmp/linear/skills/linear-finish-install .gemini/skills/linear-finish-install
Gemini CLI offers to activate the skill when a task matches — you approve it. For all projects use ~/.gemini/skills.
Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.
SKILL.md contents
Original author text · read-onlyFinish Linear tracking install
Chat: RESPONSE.md ↗. Auth: AUTH.md ↗. Snippet: ALWAYS_ON.md ↗. Optional weekly health: AUTOMATION.md ↗.
Install is complete when always-on is loaded and Linear MCP auth works. Same skills + same SoT assumption on every harness. Cursor Automation is optional.
Do these in order. Lead with the next action each turn.
1. Always-on (required)
Cursor: list user rules. If no rule titled linear-tracking (always-on), add one with cursor_dialog (item=rule, scope=user, action=add, title + ALWAYS_ON.md body). If it exists, skip.
Claude Code / Codex / file-based: ensure ~/.claude/CLAUDE.md, ~/.codex/AGENTS.md, and/or ~/.agents/AGENTS.md contain the ALWAYS_ON block between markers:
<!-- linear-tracking-always-on -->
…ALWAYS_ON.md body…
<!-- /linear-tracking-always-on -->
Idempotent: replace the block if markers exist; else append.
2. Linear MCP (required)
Call list_teams (or get_user).
- Fail → AUTH.md steps for this agent; stop after giving links.
- Pass → continue.
Useful links:
- Cursor MCP: Cursor Settings → MCP ↗
- Linear MCP docs: Linear MCP ↗
- Claude connectors: claude.ai settings ↗ or
/mcpin Claude Code
3. Monitor Automation (optional — Cursor only)
If this is Cursor and the user wants a weekly digest: open Automations (open_automation) and point at AUTOMATION.md ↗. Default schedule Monday 7:00 AM local (convert cron to UTC — see AUTOMATION.md).
Non-Cursor: skip. They can run /linear-monitor anytime.
Do not block “install complete” on Automation.
4. Report
Restate:
1. Always-on: done / already present / failed (where)
2. Linear auth: ok / needs OAuth
3. Install: complete if 1+2 ok — Automation offered / skipped / deferred
One next action only.
Frequently asked questions
What does the linear-finish-install skill do?
Complete Linear tracking installation by writing always-on rules and verifying Linear MCP authentication.
How do I install linear-finish-install?
Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.
Which AI models work with linear-finish-install?
Skills are plain Markdown instructions (the Agent Skills format), so linear-finish-install works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.
Is linear-finish-install free?
The skill is published openly by tjcages under the MIT license. The skill itself costs nothing — you only pay your AI provider for the tokens you use.
Is it safe to install skills?
A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.
How is a skill different from an MCP server or a plugin?
An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.