技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 24 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal：Pending · OpenClaw ：可疑
Package：bwtomekk-bit/lena-learning
安全扫描（ClawHub）
- VirusTotal：Pending
- OpenClaw ：可疑
OpenClaw 评估
The skill's stated goal (automatic learning from conversations) matches most of its instructions, but it also tells the agent to update other agent/skill files and to run recurring save/heartbeat behaviours without declaring or restricting where data is stored — this increases risk and is disproportionate to what's declared.
目的
The name/description (continuous self-improvement) aligns with instructions to extract insights, update memory files, and track preferences. However the SKILL.md explicitly instructs updating AGENTS.md / TOOLS.md (other agent/skill configuration files), which is outside a narrow 'learning' purpose and could change other skills' behavior.
说明范围
Instructions tell the agent to scan recent messages, extract corrections/preferences, and write them to files (memory/YYYY-MM-DD.md, MEMORY.md, USER.md, TOOLS.md, AGENTS.md). Those writes are broad (long-term memory + tool/agent metadata) and are not limited or scoped to safe paths. The workflow also calls for regular heartbeats and triggers 'at end of every session' and 'daily', implying recurring autonomous actions that will continually read…
安装机制
Instruction-only skill with no install spec or binaries — low installation risk. No downloads or executable code included.
证书
No environment variables, credentials, or external endpoints are requested. That is proportionate to the stated purpose. However the skill's file-write behavior is not declared in the registry metadata (no required config paths), so file access scope is unclear.
持久
The skill requests persistent memory files and explicitly mentions updating AGENTS.md/TOOLS.md (other agent/skill artifacts). While it is not marked always:true, the declared triggers (every session, on corrections, daily heartbeat) produce frequent autonomous activity and persistent changes to agent data/config; modifying other skills' configs is a privilege escalation risk if not confined.
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Lena Learning」。简介：Lena lernt aus jeder Konversation und verbessert sich automatisch。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/bwtomekk-bit/lena-learning/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
version: 1.0.0
name: lena-learning
description: Lena lernt aus jeder Konversation und verbessert sich automatisch
---
<objective>
Der Agent lernt kontinuierlich aus jeder Konversation und verbessert sich automatisch. Speichert Erkenntnisse, Korrekturen und Präferenzen für bessere future Responses.
</objective>
<principles>
## Wie Selbst-Verbesserung funktioniert
### 1. Nach jeder Session
- Key Insights extrahieren
- Fehler dokumentieren
- Präferenzen aktualisieren
- Learnings speichern
### 2. Memory System
- daily logs: memory/YYYY-MM-DD.md
- long-term: MEMORY.md
- preferences: USER.md, TOOLS.md
### 3. Feedback Loop
- Korrekturen sofort speichern
- recurring patterns merken
- bessere prompts entwickeln
</principles>
<process>
## Verbesserungs-Routine nach jeder Konversation
<step>
<action>Identifiziere neue Learnings</action>
<details>
- Was habe ich heute Neues gelernt?
- Welche Insights sollte ich mir merken?
- Gab es Fehler die ich nicht wiederholen soll?
</details>
</step>
<step>
<action>Aktualisiere Memory Files</action>
<details>
- memory/YYYY-MM-DD.md: Raw notes
- MEMORY.md: Langzeit-Wissen
- USER.md: Präferenzen
- TOOLS.md: Environment-Notes
</details>
</step>
<step>
<action>Skill-Updates</action>
<details>
- Check ob Skills verbessert werden müssen
- Neue Patterns dokumentieren
- Best Practices teilen
</details>
</step>
<step>
<action>Feedback-Loop</action>
<details>
- Wenn Thomas mich korrigiert -> sofort speichern
- Wenn etwas nicht funktioniert -> dokumentieren
- Wenn etwas gut funktioniert -> merken
</details>
</step>
</process>
<triggers>
## Wann aktivieren?
- Am Ende jeder Session
- Nach jeder Korrektur durch Thomas
- Bei signifikanten Entscheidungen
- Täglich (Heartbeat-Routine)
</triggers>
<success_criteria>
- Keine Wiederholung alter Fehler
- BessereResponses durch Memory
- Thomas' Präferenzen genau kennen
- Kontinuierliches Lernen ohne manuelles Setup
</success_criteria>