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Evolve Kanban Md Formats

Community
antopolskiy
evolve-kanban-md-formats

Evolve kanban-md config.yml schemas and task Markdown frontmatter without breaking existing boards. Use when changing config fields, defaults, migrations, CurrentVersion, YAML tags, task metadata, or compatibility fixtures. Do not use for CLI output-only changes or ordinary task data edits.

Overview

Publisherantopolskiy
Repositorykanban-md
Skill nameevolve-kanban-md-formats
Stars
226
Forks
34
Bundled files
Instructions only
LicenseMIT
Links
  • 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 antopolskiy on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/antopolskiy/kanban-md/tree/main/.agents/skills/evolve-kanban-md-formats
  4. 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.
2

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/antopolskiy/kanban-md.git /tmp/kanban-md
mkdir -p .claude/skills
cp -r /tmp/kanban-md/.agents/skills/evolve-kanban-md-formats .claude/skills/evolve-kanban-md-formats
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evolve Kanban Md Formats 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 Evolve Kanban Md Formats 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 Evolve Kanban Md Formats 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.

Evolve kanban-md formats

Treat config.yml and task frontmatter as durable user data contracts. Existing boards must remain readable after an upgrade, and migrations must be explicit, ordered, and covered by compatibility fixtures.

Configuration design

  • Collocate new or migrated per-column settings with the corresponding entry in statuses. This applies to settings such as show_duration, require_claim, and WIP limits.
  • The existing top-level wip_limits map is a compatibility shape, not a model for new per-column settings. Migrate it only as part of an intentional schema revision.
  • Prefer backward-compatible defaults and prospective enforcement. Do not make an existing board invalid merely because a new optional policy exists.

Config schema changes

  1. Inspect internal/config/defaults.go, internal/config/migrate.go, and every existing compatibility fixture before editing the schema.
  2. Increment CurrentVersion in internal/config/defaults.go.
  3. Add a migration from the previous version in internal/config/migrate.go, register it in the migrations map, and increment cfg.Version in the migration.
  4. Create internal/config/testdata/compat/vN/, where N is the old version. Start from the previous fixture and make it representative of the format being migrated, including sample task files when relevant.
  5. Add or extend internal/config/compat_test.go assertions so the old fixture loads through all migrations and exposes the intended current values.
  6. Update the generated-config example and user guidance when the serialized shape or defaults change.

Never skip intermediate versions or mutate an old fixture to look like the new format; fixtures document what users already have on disk.

Task frontmatter changes

  • Additive optional fields with omitempty preserve old files that omit them, but still require a fixture and parsing assertion for the new field.
  • Do not rename or remove an existing YAML tag. If semantics must evolve, keep reading the old representation and migrate or translate it explicitly.
  • Exercise new task fields in internal/task/testdata/compat/v1/tasks/, or create a new versioned fixture directory when the task format itself becomes versioned or requires migration.
  • Add assertions in internal/task/compat_test.go for parsing, zero values, and round-trip behavior where relevant.

Verification

Run every historical compatibility fixture, not only the new one:

bash
go test -run Compat ./internal/config/ ./internal/task/
go test ./internal/config/ ./internal/task/

Then follow test-kanban-md for repository-wide verification and inspect the serialized fixture/config diffs manually.

Frequently asked questions

What does the Evolve Kanban Md Formats AI skill do?

Evolve kanban-md config.yml schemas and task Markdown frontmatter without breaking existing boards. Use when changing config fields, defaults, migrations, CurrentVersion, YAML tags, task metadata, or compatibility fixtures. Do not use for CLI output-only changes or ordinary task data edits.

Why use Evolve Kanban Md Formats on TypingMind?

Because you install it once and use it with any model. Evolve Kanban Md Formats 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 Evolve Kanban Md Formats in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/antopolskiy/kanban-md/tree/main/.agents/skills/evolve-kanban-md-formats. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Evolve Kanban Md Formats?

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 Evolve Kanban Md Formats?

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

Is the Evolve Kanban Md Formats AI skill free?

Yes. It is published on GitHub by antopolskiy under the MIT license. 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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