Session Status

Organization

WellApp-ai

session-status

Generate breadcrumb headers/footers with takt time tracking and muda metrics

Overview

Publisher	WellApp-ai
Repository	`Well`
Skill name	`session-status`
Stars	342
Forks	48
Bundled files	Instructions only
License	MIT
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 WellApp-ai on GitHub. Read the source before you install it.

Installation

Install the Session 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.
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/WellApp-ai/Well.git /tmp/Well
mkdir -p .claude/skills
cp -r /tmp/Well/cursor-rules/skills/session-status .claude/skills/session-status

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

Use it in TypingMind

Enable Session 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 Session 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 Session 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.

Session Status Skill

Generate consistent navigation breadcrumbs showing current position, takt time, and session metrics.

When to Use

At START of every Ask/Agent/Plan mode response
At END of every Ask/Agent/Plan mode response
When session metrics are needed for Session Journal sync

Phase 1: Gather State

Collect current session state:

Data	Source
Feature name	From init context or branch name
Current phase	DIVERGE / CONVERGE / DEFINE / AGENT
Loop count	Incremented on each user feedback cycle
Progress	Validated items / total items
Duration	Time since phase started
Status	G (flow) / Y (waiting) / R (stopped)

Phase 2: Calculate Takt

Compare duration against targets from 03-shared.mdc:

Phase	Target	Warning	Stop
DIVERGE (per loop)	15min	30min	60min
CONVERGE	20min	40min	90min
DEFINE	10min	20min	45min
Commit (each)	10min	20min	30min

Determine suffix:

Under target: (none)
Warning exceeded: !
Stop exceeded: !!

Phase 3: Format Header

Generate single-line breadcrumb:

Examples by phase:

DIVERGE: G | Collaboration | DIVERGE ###....... | L3 | 5/9 | 18m
CONVERGE: G | Collaboration | DIVERGE OK | CONVERGE ##.... | L1 | 22m
DEFINE: G | Collaboration | DIVERGE OK | CONVERGE OK | DEFINE ###.. | L2 | 35m
AGENT: G | Collaboration | AGENT | C2/5 | 45m
Warning: Y | Collaboration | DIVERGE ###....... | L3 | 5/9 | 32m!
Stopped: R | Collaboration | AGENT | JIDOKA STOP

Progress bar: 10 chars, # filled, . empty, proportional to completion.

Phase 4: Format Footer

Generate context-specific footer:


---
Next: [action prompt]

Dynamic prompts by context:

Context	Footer Prompt
DIVERGE with DIG	`Provide OK/KO/DIG for: #4, #6, #7`
Gate 1 passed	`All validated. Say "converge" to proceed.`
Gate 2	`Choose option: A / B / C`
Gate 3	`Approve phasing: OK / REORDER / SPLIT`
AGENT	`Commit 2/5 in progress...`
Jidoka stop	`Reply with A, B, C, or D`
Autonomous	`Iteration 3/5...`

Phase 5: Track Muda (Silent)

Update session metrics in memory:

Metric	Tracking Rule
Loop count	Increment on user feedback
Waiting time	Time between user responses
Rework	Items DIG'd 3+ times
RED count	qa-commit failures
Escalations	Jidoka Tier 2/3 events

Output Format

markdown
## Session Status

**Header:** [formatted header string]
**Footer:** [formatted footer string]

### Metrics (Silent)
- Duration: [N]min
- Loops: [N]
- Rework: [N]
- Waiting: [N]min
- RED count: [N]

Header/Footer Examples

Ask Mode - DIVERGE L3

Header:


G | Collaboration | DIVERGE ###....... | L3 | 5/9 | 18m

Footer:


---
Next: Provide OK/KO/DIG for: #4, #6, #7

Ask Mode - Gate 1 Passed

Header:


G | Collaboration | DIVERGE OK | CONVERGE #......... | L1 | 22m

Footer:


---
Next: All wireframes validated. Say "converge" to proceed.

Agent Mode - Commit in Progress

Header:


G | Collaboration | AGENT | C2/5 | 45m

Footer:


---
Next: Implementing Commit 2: Add workspace membership entity...

Jidoka Stop

Header:


R | Collaboration | AGENT | JIDOKA STOP

Footer:


---
Next: Reply with A (different approach), B (skip), C (pause), or D (abort)

Integration

This skill is invoked by:

ask.mdc - At start and end of every response
agent.mdc - At start and end of every response
plan.mdc - At start and end of every response
push-pr.mdc - Collects final metrics for session-journal sync

Invocation

Auto-invoked by modes. Manual trigger: "show session status"

Tools Used

Tool	Purpose
(none)	Pure calculation, no external tools

Frequently asked questions

What does the Session Status AI skill do?

Generate breadcrumb headers/footers with takt time tracking and muda metrics

Why use Session Status on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WellApp-ai/Well/tree/main/cursor-rules/skills/session-status. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Session 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 Session Status?

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

Is the Session Status AI skill free?

Yes. It is published on GitHub by WellApp-ai 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

Session Status Skill

When to Use

Phase 1: Gather State

Phase 2: Calculate Takt

Phase 3: Format Header

Phase 4: Format Footer

Phase 5: Track Muda (Silent)

Output Format

Header/Footer Examples

Ask Mode - DIVERGE L3

Ask Mode - Gate 1 Passed

Agent Mode - Commit in Progress

Jidoka Stop

Integration

Invocation

Tools Used

Frequently asked questions

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