Ktlo

Organization

coinbase

ktlo

Instructions to fetch assigned Linear issues in the current cycle and potentially kick off a development session.

Overview

Publisher	coinbase
Repository	`cds`
Skill name	`ktlo`
Stars	506
Forks	114
Bundled files	Instructions only
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by coinbase on GitHub. Read the source before you install it.

Installation

Install the Ktlo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/coinbase/cds/tree/master/.claude/skills/ktlo
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/coinbase/cds.git /tmp/cds
mkdir -p .claude/skills
cp -r /tmp/cds/.claude/skills/ktlo .claude/skills/ktlo

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ktlo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ktlo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ktlo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Use the Linear MCP server to get my assigned issues in the active cycle. Follow these steps exactly:

Call get_user with query "me" to retrieve my user info and the list of teams I belong to.
For each of my teams, call list_cycles with type: "current" and that team's teamId to get the active cycle ID(s). Skip teams with no active cycle.
For each active cycle found, call list_issues with assignee: "me", the explicit cycle id (NOT the string "current"), and the corresponding team ID. Do NOT pass "current" as the cycle value — it must be the actual cycle ID returned in step 2.
Deduplicate and combine all results.

Present them to me as a list of options. It is possible that I have no issues assigned to me in the active cycle.

Also remind me to check the Jira Bug Sprint board for any bugs that may be assigned to me as they are still not tracked in Linear.

If I have any issues assigned to me in the active cycle, ask for the issue id/name/etc. that I may want to work on. If provided, fetch the rest of the issue's details and think about the best way to implement the feature/bug/etc. If there is not enough context on the issue, ask me clarifying questions.

You must always execute on designated issue in PLAN MODE. Never start coding a solution to the issue without consent from me on a well thought out plan.

Frequently asked questions

What does the Ktlo AI skill do?

Instructions to fetch assigned Linear issues in the current cycle and potentially kick off a development session.

Why use Ktlo on TypingMind?

Because you install it once and use it with any model. Ktlo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ktlo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coinbase/cds/tree/master/.claude/skills/ktlo. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ktlo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ktlo?

As many as you like. As long as a model supports skills, you can use Ktlo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ktlo AI skill free?

It is published on GitHub by coinbase. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Skill instructions

Frequently asked questions

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