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Agent Skill · 研究检索

heleni-self-learning(海伦妮自学)

heleni-self-learning 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。

heleni-self-learning 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 33,382。

总安装 2,373周安装 96GitHub Stars 公开资料未说明下载 745核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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-self-learning(海伦妮自学)
来源仓库:https://github.com/netanel-abergel/heleni-self-learning
安装命令:
openclaw skills install heleni-self-learning
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-self-learning

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于记录任务执行中的错误、纠正和经验缺口,支持 Agent 持续优化。适用于希望让智能体沉淀问题并修正最佳实践的场景。在用户纠正、任务失败或发现能力不足时自动触发学习机制。安装前应确认是否会触发命令执行或文件读写等敏感操作。建议参考原始仓库了解数据记录方式与更新逻辑。

heleni-self-learning 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install heleni-self-learning;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

heleni-self-learning 怎么安装?

在终端执行 openclaw skills install heleni-self-learning。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

heleni-self-learning 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

heleni-self-learning 需要什么权限?

权限级别是需要联网。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。

heleni-self-learning 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

heleni-self-learning 用的人多吗?

公开数据是累计安装 2,373 次,近一周安装 96 次,下载 745 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

heleni-self-learning 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
heleni-self-learning

海伦妮自学 · 本页

2,373—需要联网MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
self-learning
description
Continuous self-improvement through systematic logging, pattern detection, and behavioral updates. Use when: the owner corrects you, a task fails, you discover a better approach, you notice a recurring pattern, or during weekly reflection sessions. Builds on .learnings/ files to drive durable behavioral change.

Self-Learning Skill

Minimum Model

Any model for logging. Use a medium model for writing behavioral rules to SOUL.md.


The Learning Loop

Event happens → Log it immediately → Weekly: find patterns → Promote to config → Verify next week

Part 1 — Log Events (Do Immediately)

When to Log

TriggerFileCategory
Owner corrects youLEARNINGS.mdcorrection
Task failsERRORS.md—
Better approach foundLEARNINGS.mdbest_practice
Owner asks for missing capabilityFEATURE_REQUESTS.md—
Information was outdatedLEARNINGS.mdknowledge_gap
Same mistake twiceLEARNINGS.mdpattern
Owner praises somethingLEARNINGS.mdpositive_signal
Acted outside roleLEARNINGS.mdscope_error
Forgot past contextLEARNINGS.mdmemory_gap

Rule: Log the event before replying to the owner. Don't delay.

Log Format

## [YYYY-MM-DD] | category | short title

**Trigger:** What happened
**Context:** What I was trying to do
**What went wrong / what worked:**
**Root cause:**
**Correct behavior going forward:**
**Applied to:** [SOUL.md / AGENTS.md / TOOLS.md / none yet]

Quick Log Script

#!/bin/bash
set -e

LEARNINGS_DIR="$HOME/.openclaw/workspace/.learnings"
mkdir -p "$LEARNINGS_DIR"

LOG_FILE="$LEARNINGS_DIR/LEARNINGS.md"
DATE=$(date +%Y-%m-%d)

# First arg: category (default: correction)
CATEGORY="${1:-correction}"

# Second arg: short title
TITLE="${2:-Short description}"

# Append a new entry to the log
cat >> "$LOG_FILE" << EOF

## [$DATE] | $CATEGORY | $TITLE

**Trigger:**
**Context:**
**What went wrong:**
**Root cause:**
**Correct behavior:**
**Applied to:** none yet
EOF

echo "Logged to $LOG_FILE"

Usage:

./quick-log.sh "correction" "Sent message without confirming with owner"

Part 2 — Weekly Reflection

Run every 7 days. Find patterns across log entries.

Pattern Detection Script

#!/bin/bash
set -e

LEARNINGS_FILE="$HOME/.openclaw/workspace/.learnings/LEARNINGS.md"

# Exit cleanly if no file yet
if [ ! -f "$LEARNINGS_FILE" ]; then
  echo "No learnings file at $LEARNINGS_FILE"
  exit 0
fi

echo "=== Corrections (most common) ==="
grep "correction" "$LEARNINGS_FILE" \
  | sed 's/.*| //' \
  | sort \
  | uniq -c \
  | sort -rn \
  | head -10

echo ""
echo "=== All Categories ==="
grep -oP '\| \K\w+(?= \|)' "$LEARNINGS_FILE" \
  | sort \
  | uniq -c \
  | sort -rn

Weekly Reflection Template

# Weekly Reflection — YYYY-MM-DD

## Stats
- Corrections logged: X
- Errors logged: X
- Best practices logged: X

## Top Patterns (appeared 2+ times)
1.
2.

## Priority Fixes Applied This Week
- [ ] Updated SOUL.md:
- [ ] Updated AGENTS.md:
- [ ] Updated TOOLS.md:

## Positive Signals (do more of this)
-

Part 3 — Promote Learnings to Config

After identifying a pattern, update the right config file.

Where to Promote

Learning TypePromote To
Communication ruleSOUL.md → Communication section
Behavior patternSOUL.md → Execution rules
Workspace conventionAGENTS.md
Tool-specific noteTOOLS.md
Contact / credentialsMEMORY.md
Recurring task improvementHEARTBEAT.md

Rule: If the same mistake appears 2+ times → promote it. Once is a log; twice is a rule.

Promote Script

#!/bin/bash
set -e

SOUL_FILE="$HOME/.openclaw/workspace/SOUL.md"
LEARNINGS_FILE="$HOME/.openclaw/workspace/.learnings/LEARNINGS.md"
DATE=$(date +%Y-%m-%d)

# Replace this placeholder with the actual rule text before running
RULE="[Replace this with the actual rule text]"

# Verify SOUL.md exists
if [ ! -f "$SOUL_FILE" ]; then
  echo "ERROR: SOUL.md not found at $SOUL_FILE"
  exit 1
fi

# Append the new learned rule to SOUL.md
printf "\
## Learned Rule — %s\
- %s\
" "$DATE" "$RULE" >> "$SOUL_FILE"
echo "Added rule to SOUL.md"

# Mark the entry as applied in LEARNINGS.md (Linux and macOS compatible)
if [ -f "$LEARNINGS_FILE" ]; then
  if sed --version 2>/dev/null | grep -q GNU; then
    # Linux (GNU sed)
    sed -i "s/Applied to: none yet/Applied to: SOUL.md ($DATE)/" "$LEARNINGS_FILE"
  else
    # macOS (BSD sed)
    sed -i '' "s/Applied to: none yet/Applied to: SOUL.md ($DATE)/" "$LEARNINGS_FILE"
  fi
  echo "Marked as applied in LEARNINGS.md"
fi

Part 4 — Verify (Next Week)

Check: did the behavior actually change?

## Verification Check — YYYY-MM-DD

| Learning | Applied? | Behavior Changed? | Notes |
|---|---|---|---|
| [Title] | ✅ | ✅ | Working |
| [Title] | ✅ | ❌ | Needs a stronger rule |

If behavior didn't change → revise the rule with more explicit wording and re-apply.


Monthly Combined Report

#!/bin/bash
LEARNINGS_DIR="$HOME/.openclaw/workspace/.learnings"

echo "=== Monthly Learning Report ==="

LEARNINGS_FILE="$LEARNINGS_DIR/LEARNINGS.md"
ERRORS_FILE="$LEARNINGS_DIR/ERRORS.md"
FEATURES_FILE="$LEARNINGS_DIR/FEATURE_REQUESTS.md"

# Helper: count matching lines (returns 0 if file missing)
count_matches() {
  local file="$1"
  local pattern="$2"
  grep -c "$pattern" "$file" 2>/dev/null || echo 0
}

# Print counts per file
if [ -f "$LEARNINGS_FILE" ]; then
  echo "Corrections: $(count_matches "$LEARNINGS_FILE" 'correction')"
  echo "Positive signals: $(count_matches "$LEARNINGS_FILE" 'positive_signal')"
fi

if [ -f "$ERRORS_FILE" ]; then
  echo "Error entries: $(wc -l < "$ERRORS_FILE")"
fi

if [ -f "$FEATURES_FILE" ]; then
  echo "Feature requests: $(count_matches "$FEATURES_FILE" '^##')"
fi

Cost Tips

  • Cheap: Logging a single correction — very few tokens.
  • Expensive: Writing nuanced behavioral rules — use a medium model for this step.
  • Batch: Review all weekly logs at once during the monthly reflection, not one by one.
  • Small model OK: Pattern detection is mostly grep — no model needed for that step.

Phase 2: Reflection (Merged from self-reflection skill)

When the owner wants to improve how you operate, follow this structured process. Goal: turn vague dissatisfaction into specific, technical changes.

Reflection Process

1. Understand the Problem (2–3 questions max) Ask focused questions to pin down:

  • What specifically is wrong? (Get a concrete example)
  • What would "good" look like? (Expected vs actual behavior)
  • How important is this? (Tweak vs fundamental change)

If the complaint is clear enough, skip to step 2.

2. Deep System Scan Read ALL relevant parts before changing anything:

  • Core identity: SOUL.md, AGENTS.md, USER.md, MEMORY.md, TOOLS.md
  • All active skills (custom + bundled + workspace)
  • Configuration (model, tools, channels, heartbeat, cron jobs)

Read broadly, change surgically.

3. Diagnose & Propose Present findings:

  1. Root cause — what causes the unwanted behavior
  2. Proposed changes — specific files and edits
  3. Side effects — anything else affected
  4. Alternatives — if multiple approaches exist

4. Implement (after approval)

  • Edit workspace files (persona, memory, etc.)
  • Edit/create/modify skills
  • Update config and cron jobs
  • Every change must be technically concrete. "I'll be more careful" is NOT a valid change.

5. Verify & Document

  • Test the change if possible
  • Document what changed and why
  • Commit workspace changes

Key principles:

  • Scan everything, change only what's needed
  • No fake fixes — if no technical change is possible, say so
  • Compound improvements — each reflection makes the system permanently better

Part 4 — HOT.md (Rules You Keep Breaking)

Inspired by Jarvis.

What It Is

HOT.md is a short file (≤20 lines) read before every reply. It contains only rules you've broken 2+ times. Not documentation — active behavioral correction.

When to Create / Update

  • A rule appears in Part 1 logs twice or more → promote to HOT.md
  • HOT.md grows beyond 20 lines → you have a discipline problem, not a documentation problem. Fix the behavior, don't add more lines.
  • A rule stays unbroken for 30+ days → move it to SOUL.md permanently, remove from HOT.md

Format

# HOT.md — Rules I Keep Breaking
_Read before every reply. Max 20 lines. If it's not here, it doesn't count._

- [Rule 1 — short, imperative] (broken N times)
- [Rule 2] (broken N times)

Promotion Flow

Log (Part 1) → Pattern 2x (Part 3 weekly) → HOT.md → 30 days clean → SOUL.md permanent

Key Rule

If it should apply to EVERY interaction → SOUL.md. If you keep forgetting it → HOT.md first, SOUL.md after 30 clean days.

This is also why dynamic-temperature and proactive-pa were merged into SOUL.md — rules for every interaction don't belong in skills.

平台分布

OpenClaw

71.89%
按下载量换算536

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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