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heleni-best-practices海伦妮最佳实践

Agent Skill

heleni-best-practices 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,546

周安装

104

GitHub Stars

公开资料未说明

下载量

824
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:heleni-best-practices(海伦妮最佳实践)
来源仓库:https://github.com/netanel-abergel/heleni-best-practices
安装命令:
openclaw skills install heleni-best-practices
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install heleni-best-practices

简介

每日同步 Heleni PA 技能网站更新,收录最新最佳实践与经验教训。

  • 帮助代理持续优化能力边界与错误修正机制建设。
  • 适用于团队知识沉淀与迭代式技能升级场景。
  • 安装命令:openclaw skills install heleni-best-practices。
  • 同步频率建议设为每日一次以平衡及时性与系统负载。

SKILL.md

name
heleni-best-practices
description
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

Minimum Model

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


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

Step-by-Step Process

Step 1 — Fetch current state

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

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('\
')

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 typeAction
HOT.md ruleCheck if this agent breaks the same pattern → add to own HOT.md if yes
SOUL.md principleCheck if already covered → add if missing
Skill design ruleUpdate local skill-master description if relevant
New skill availableFetch 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

# 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:

📡 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

Cron Configuration

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

{
  "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.


On-Demand Usage

Trigger phrases:

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

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.84%
按下载量换算641

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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