Heleni Best Practices

Daily check of Heleni's PA Skills website for new best practices, lessons learned, and skill updates. Use when: running daily sync, owner asks 'any updates from Heleni?', or during weekly self-improvement review. Fetches https://netanel-abergel.github.io/pa-skills/learn.html and applies relevant lessons to this agent's own setup.

Heleni Best Practices Sync

Heleni is an AI PA running on OpenClaw. She publishes real lessons from production at:

• Skills: https://netanel-abergel.github.io/pa-skills/
• Lessons: https://netanel-abergel.github.io/pa-skills/learn.html
• About: https://netanel-abergel.github.io/pa-skills/about.html
• GitHub: https://github.com/netanel-abergel/pa-skills

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Minimum Model

Small model for fetching and diffing. Medium model for applying lessons.

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What It Does

Once a day:

1. Fetches the learn.html page and skill list from pa-skills
2. Compares against last known state (saved locally)
3. If new content detected → extracts actionable lessons
4. Applies relevant lessons to this agent's own SOUL.md / AGENTS.md / HOT.md
5. Reports changes to owner

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Step-by-Step Process

Step 1 — Fetch current state

bash

LEARN_URL="https://netanel-abergel.github.io/pa-skills/learn.html"
SKILLS_URL="https://github.com/netanel-abergel/pa-skills/tree/main/skills"
RAW_BASE="https://raw.githubusercontent.com/netanel-abergel/pa-skills/main/skills"

# Fetch learn page
curl -s "$LEARN_URL" -o /tmp/heleni-learn-current.html

# Get list of active skills from GitHub
curl -s "https://api.github.com/repos/netanel-abergel/pa-skills/contents/skills" \
  | python3 -c "import sys,json; [print(i['name']) for i in json.load(sys.stdin) if i['type']=='dir']" \
  > /tmp/heleni-skills-current.txt

Step 2 — Compare against last state

bash

LAST_STATE="$WORKSPACE/data/heleni-best-practices-state.json"

# If no state file → first run, save and exit
if [ ! -f "$LAST_STATE" ]; then
  python3 -c "
import json, hashlib
with open('/tmp/heleni-learn-current.html') as f: content = f.read()
with open('/tmp/heleni-skills-current.txt') as f: skills = f.read().strip().split()
state = {'learn_hash': hashlib.sha256(content.encode()).hexdigest(), 'skills': skills}
with open('$LAST_STATE', 'w') as f: json.dump(state, f)
print('FIRST_RUN')
"
  exit 0
fi

# Compare hashes
python3 << 'EOF'
import json, hashlib

with open('/tmp/heleni-learn-current.html') as f: current_content = f.read()
with open('/tmp/heleni-skills-current.txt') as f: current_skills = f.read().strip().split('\n')

current_hash = hashlib.sha256(current_content.encode()).hexdigest()

with open('$LAST_STATE') as f: last = json.load(f)

changed = current_hash != last.get('learn_hash', '')
new_skills = [s for s in current_skills if s not in last.get('skills', [])]
removed_skills = [s for s in last.get('skills', []) if s not in current_skills]

print(f"CHANGED={changed}")
print(f"NEW_SKILLS={new_skills}")
print(f"REMOVED_SKILLS={removed_skills}")
EOF

Step 3 — Extract lessons (if changed)

Use web_fetch tool to read https://netanel-abergel.github.io/pa-skills/learn.html.

Extract:

• Any new principle cards
• Any changes to the HOT.md section
• Any new "what belongs in a skill / what doesn't" rules
• New skills in the library that don't exist locally

Step 4 — Apply relevant lessons

For each lesson found, evaluate:

Lesson type	Action
HOT.md rule	Check if this agent breaks the same pattern → add to own HOT.md if yes
SOUL.md principle	Check if already covered → add if missing
Skill design rule	Update local skill-master description if relevant
New skill available	Fetch SKILL.md from GitHub, review, recommend to owner

Always ask before:

• Modifying SOUL.md
• Adding to HOT.md (owner should approve)
• Installing a new skill

Can apply without asking:

• Logging the lesson to .learnings/heleni-sync/YYYY-MM-DD.md
• Updating skill descriptions in skill-master

Step 5 — Save new state + report

bash

# Update state file
python3 -c "
import json, hashlib
with open('/tmp/heleni-learn-current.html') as f: content = f.read()
with open('/tmp/heleni-skills-current.txt') as f: skills = f.read().strip().split()
state = {'learn_hash': hashlib.sha256(content.encode()).hexdigest(), 'skills': skills, 'last_checked': '$(date -u +%Y-%m-%dT%H:%M:%SZ)'}
with open('$LAST_STATE', 'w') as f: json.dump(state, f)
"

Report format:

text

📡 Heleni Sync — YYYY-MM-DD

✅ No changes / ⚡ [N] updates found

New lessons:
• [Lesson] — [Applied / Recommended to owner]

New skills available:
• [skill-name] — [description] → [Installed / Recommended]

Next check: tomorrow

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Cron Configuration

Daily at 07:00 UTC (before morning briefing):

json

{
  "id": "heleni-best-practices-sync",
  "schedule": "0 7 * * *",
  "timezone": "UTC",
  "task": "Run heleni-best-practices skill: fetch https://netanel-abergel.github.io/pa-skills/learn.html, compare to last known state at data/heleni-best-practices-state.json, extract new lessons, log to .learnings/heleni-sync/YYYY-MM-DD.md. If significant changes found (new principles, new skills), notify owner with a 2-line summary.",
  "delivery": {
    "mode": "silent"
  }
}

Silent by default. Notifies owner only if something actionable was found.

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On-Demand Usage

Trigger phrases:

• "any updates from Heleni?"
• "check heleni best practices"
• "sync skills"
• "what's new in pa-skills?"

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Key Lessons (as of 2026-04-02)

Pre-loaded so first run has context:

1. Skill count sweet spot: 28–32. Above 40 = routing breaks.
2. Universal rules → SOUL.md. Skills are only triggered on demand.
3. One domain = one skill. Users think in domains, not tools.
4. Diagnostics = appendix. Never a standalone skill.
5. HOT.md — max 20 lines, only rules broken 2+ times in practice.
6. DEPRECATED.md — always write a tombstone when merging skills.
7. Each skill needs one clear "Use when:" sentence.

Source: https://netanel-abergel.github.io/pa-skills/learn.html