agentleFS
Soul-Brews-StudioSoul-Brews-Studio/arra-oracle-skills-cli/skills/resonance/SKILL.md

resonance

Skill121 starsChanged 7 months agoMITView on GitHub

Capture a resonance moment — when something clicks, sparks joy, or feels right. Logs what resonated, when, why, and how. Use when user says "resonance", "yes!", "cool!", "very cool!", "love it", "that's it!", "exactly!", or expresses strong positive reaction to something just discussed. Do NOT trigger for general praise like "thanks" or "ok".

1 other project uses a version of this, 1 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When something clicks — log it.

    line 9
  2. Distinctive:

    Look back at the last 5-10 messages.

    line 48
  3. Very specific:

    Write to $PSI/memory/learnings/YYYY-MM-DD_resonance-<slug>.md with frontmatter:

    line 88

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

/resonance — Capture What Resonates

When something clicks — log it. The pattern, the insight, the spark.

Usage

/resonance                    # Auto-detect from recent conversation
/resonance "skills as marketplace"  # With explicit note

When to Trigger

AI should consider auto-suggesting /resonance when user says:

  • "yes!", "cool!", "very cool!", "love it!", "exactly!"
  • "that's it!", "perfect!", "นี่แหละ!", "ใช่เลย!"
  • Strong agreement after a design decision or insight

Steps

0. Anchor (date-stamp + root)

date "+🕐 %H:%M %Z (%A %d %B %Y)"

# Find oracle root — git toplevel that has CLAUDE.md + ψ/
ORACLE_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
if [ -n "$ORACLE_ROOT" ] && [ -f "$ORACLE_ROOT/CLAUDE.md" ] && { [ -d "$ORACLE_ROOT/ψ" ] || [ -L "$ORACLE_ROOT/ψ" ]; }; then
  PSI="$ORACLE_ROOT/ψ"
elif [ -f "$(pwd)/CLAUDE.md" ] && { [ -d "$(pwd)/ψ" ] || [ -L "$(pwd)/ψ" ]; }; then
  ORACLE_ROOT="$(pwd)"
  PSI="$ORACLE_ROOT/ψ"
else
  echo "⚠️ Not in oracle repo (no CLAUDE.md + ψ/ at git root). Writing to pwd."
  ORACLE_ROOT="$(pwd)"
  PSI="$ORACLE_ROOT/ψ"
fi

1. Analyze Recent Conversation

Look back at the last 5-10 messages. Find:

  • What: The specific idea, pattern, or decision that sparked the reaction
  • When: Timestamp (from hook context or current time)
  • Why: Why did this resonate? What problem does it solve?
  • How: How was it discovered? What led to this moment?
  • Connection: Does this connect to existing Oracle learnings?

2. Log to Vault

mkdir -p "$PSI/memory/resonance"

Write to: $PSI/memory/resonance/YYYY-MM-DD_HHMM_slug.md

# Resonance: [short title]

**When**: YYYY-MM-DD HH:MM
**Session**: [session-id]
**Context**: [what we were working on]

## What Resonated
[The specific idea/pattern/decision]

## Why It Matters
[Why this clicked — what problem it solves, what it enables]

## How We Got Here
[The conversation path that led to this moment]

## Connection
[Links to existing patterns, principles, or learnings]

## Tags
[concept tags for future search]

3. Sync to Oracle (if available, two-layer pattern)

  1. Write to $PSI/memory/learnings/YYYY-MM-DD_resonance-<slug>.md with frontmatter:
    ---
    pattern: "[resonance title]: [what resonated]"
    date: <today>
    source: resonance: [repo-name]
    concepts: ["resonance", <tags>]
    ---
    
    # [resonance title]
    [what resonated and why]
  2. The Oracle's auto-memory layer picks up new files in $PSI/memory/learnings/ automatically — no separate API call needed.

4. Confirm (announce-mode — absolute paths required)

announce-mode → absolute path (no ψ/, no ~/, no $VAR, no ...).

Use: echo "marker: $RESOLVED_PATH" — bash substitutes. See CONVENTIONS.md.

RES_FILE="$PSI/memory/resonance/$(date +%Y-%m-%d)_$(date +%H%M)_${SLUG}.md"
LESSON_FILE="$PSI/memory/learnings/$(date +%Y-%m-%d)_resonance-${SLUG}.md"
echo "✨ Resonance captured: ${TITLE}"
echo "📥 Saved:   $RES_FILE"
echo "💡 Lesson:  $LESSON_FILE"

Short. Don't over-explain. The moment speaks for itself.

Philosophy

Resonance is the signal. When something resonates, it means the pattern matches reality. Log it before it fades.

Resonance logs are different from learnings:

  • Learnings = what you figured out (head)
  • Resonance = what clicked (heart)

Over time, resonance logs reveal what matters most — not what's logical, but what's alive.

ARGUMENTS: $ARGUMENTS

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.