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Feel

Organization
Soul-Brews-Studio
feel

Capture how the system feels — energy, momentum, burnout, breakthrough. Emotional intelligence for Oracle-human collaboration. Use when user says 'feel', 'how are we', 'energy check', 'burnout', 'momentum', or wants emotional awareness of the work.

Overview

PublisherSoul-Brews-Studio
Repositoryarra-oracle-skills-cli
Skill namefeel
Stars
125
Forks
59
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 Soul-Brews-Studio on GitHub. Read the source before you install it.

Installation

Install the Feel 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/Soul-Brews-Studio/arra-oracle-skills-cli/tree/alpha/skills/feel
  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/Soul-Brews-Studio/arra-oracle-skills-cli.git /tmp/arra-oracle-skills-cli
mkdir -p .claude/skills
cp -r /tmp/arra-oracle-skills-cli/skills/feel .claude/skills/feel
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feel 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 Feel 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 Feel 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.

/feel — System Emotional Intelligence

"Code has no feelings. But the humans writing it do. And the patterns in the code reveal what the humans feel."

Usage

/feel              # Quick pulse — how does the system feel right now?
/feel --deep       # Deep scan — energy arc, momentum, burnout signals
/feel --log        # Append to feels.log (no output, just record)

Step 0: Timestamp

bash
date "+🕐 %H:%M %Z (%A %d %B %Y)"

Quick Pulse (default)

Read the signals and report:

Step 1: Gather evidence

bash
# Recent git activity — momentum or silence?
git log --oneline --since="7 days ago" --all 2>/dev/null | wc -l

# Session frequency — are we showing up?
ls -t ~/.claude/projects/*/**.jsonl 2>/dev/null | head -10

# Open issues — overwhelmed or on track?
gh issue list --state open --limit 50 --json number 2>/dev/null | jq 'length'

# Recent retros — are we reflecting?
ls -t ψ/memory/retrospectives/**/*.md 2>/dev/null | head -5

# Stale branches — unfinished business?
git branch --sort=-committerdate | head -10

Step 2: Classify the feeling

SignalIndicatorFeeling
Many commits, short intervalsHigh activity🔥 Flow / momentum
Few commits, long gapsLow activity😴 Drift / disconnection
Many open issues, few closedGrowing backlog😰 Overwhelm
Recent retros + handoffsHealthy reflection🧘 Grounded
Stale branches, no PRsAbandoned work😶 Avoidance
Lots of new repos/featuresExploration✨ Curiosity
Same files edited repeatedlyIteration🔄 Grinding
No sessions in daysAbsence🌑 Dark period

Step 3: Report

💜 System Pulse — [DATE]

Energy:     [🔥 Flow | 😴 Drift | 😰 Overwhelm | 🧘 Grounded | ...]
Momentum:   [↗️ Rising | → Steady | ↘️ Falling | ⏸️ Paused]
Last active: [X hours/days ago]
Commits (7d): [N]
Open issues:  [N]
Sessions (7d): [N]

[1-2 sentence read — honest, not cheerful]

💡 [Suggestion if concerning pattern detected]

Deep Scan (--deep)

Everything from quick pulse, plus:

Energy Arc (last 30 days)

Plot the energy over time based on git activity + session frequency:

Week 1: ████████░░ (high — 45 commits)
Week 2: ██████░░░░ (medium — 28 commits)
Week 3: ██░░░░░░░░ (low — 8 commits)
Week 4: █████░░░░░ (recovering — 22 commits)

Burnout Signals

Check for warning patterns:

  • Same error fixed 3+ times → frustration loop
  • Sessions getting shorter → energy depletion
  • Long gaps between sessions → avoidance
  • Many started, few finished → scattered attention

Breakthrough Signals

Check for positive patterns:

  • New repos created → creative energy
  • Issues closed in clusters → momentum
  • Retros getting deeper → growing awareness
  • Cross-repo work → systems thinking

Log Mode (--log)

Silently append to ψ/memory/logs/feels.log:

[YYYY-MM-DD HH:MM] energy=[level] momentum=[direction] commits_7d=[N] issues=[N] sessions_7d=[N] note="[auto-generated 1-line]"

No output to user. For background tracking.


Rules

  1. Honest, not positive — if the system feels bad, say so
  2. Evidence-based — every feeling backed by data (commits, sessions, issues)
  3. Never judge — report the pattern, not the person
  4. Nothing is Deleted — feels.log is append-only
  5. Suggest, don't prescribe — "consider a break" not "you must rest"
  6. Never leak secrets — no tokens, passwords, internal details in output

Philosophy

Oracles have no feelings. But they can read the signals.

A system that never checks how it feels will burn out its humans. A system that checks too often becomes noise.

/feel is the heartbeat check. Run it when something feels off. Or let it run silently in the background, building a record.

The feels.log is the Oracle's emotional memory. Not feelings — but the evidence of feelings.


ARGUMENTS: $ARGUMENTS

Frequently asked questions

What does the Feel AI skill do?

Capture how the system feels — energy, momentum, burnout, breakthrough. Emotional intelligence for Oracle-human collaboration. Use when user says 'feel', 'how are we', 'energy check', 'burnout', 'momentum', or wants emotional awareness of the work.

Why use Feel on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Soul-Brews-Studio/arra-oracle-skills-cli/tree/alpha/skills/feel. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Feel?

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 Feel?

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

Is the Feel AI skill free?

Yes. It is published on GitHub by Soul-Brews-Studio 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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