Wf Status

Community

tomsej

wf-status

Show the truthful state of workflow contracts from git, gh, worktrees, and transient launch claims; offer archive, resume, reconciliation, or wf-run actions.

Overview

Publisher	tomsej
Repository	`pi-ext`
Skill name	`wf-status`
Stars	80
Forks	8
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 tomsej on GitHub. Read the source before you install it.

Installation

Install the Wf Status 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/tomsej/pi-ext/tree/main/skills/wf-status
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/tomsej/pi-ext.git /tmp/pi-ext
mkdir -p .claude/skills
cp -r /tmp/pi-ext/skills/wf-status .claude/skills/wf-status

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

Use it in TypingMind

Enable Wf Status 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 Wf Status 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 Wf Status 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.

/wf-status — contract overview

GATE = node ~/Workspace/pi-ext/wf/wf-gate.mjs

Run GATE status --json from the repo root (human table: without --json). States are derived live: ready / blocked (after) / cycle / launching (claim before worktree begin) / running / duplicate / pr-open / done.
Present the table in Czech and add recommended actions:
- done → offer to archive: mv <adresář kontraktu> <specs dir>/_archive/ (each contract is a directory ~/Workspace/specs/<project>/<name>/ holding contract.md and its artifacts, outside any repo — no commits or PRs involved; derive the directory from the file path in the status JSON).
- pr-open with unresolved threads → offer dispatching the worktree session via wf-run's resolve-comments action.
- blocked → name unmet prerequisites; cycle → require contract repair.
- launching → never retry create; wait for claim transition or expiry.
- duplicate → list every worktree and require reconciliation to one canonical.
- running with an old last commit → flag as possibly stalled; offer resume via wf-run. A running implementation can be inspected via /subagents.
- ready specs → mention wf-run to launch them.
Take no action without the user's approval. This skill reads; it mutates only the approved archive commits.

Frequently asked questions

What does the Wf Status AI skill do?

Show the truthful state of workflow contracts from git, gh, worktrees, and transient launch claims; offer archive, resume, reconciliation, or wf-run actions.

Why use Wf Status on TypingMind?

Because you install it once and use it with any model. Wf Status 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 Wf Status in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tomsej/pi-ext/tree/main/skills/wf-status. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wf Status?

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 Wf Status?

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

Is the Wf Status AI skill free?

Yes. It is published on GitHub by tomsej 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

/wf-status — contract overview

Frequently asked questions

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