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Lena Learning
by
bwtomekk-bit
· GitHub ↗
· v1.0.0
· MIT-0
135
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Install in OpenClaw
/install lena-learning
Description
Lena lernt aus jeder Konversation und verbessert sich automatisch
README (SKILL.md)
\x3Cobjective> Der Agent lernt kontinuierlich aus jeder Konversation und verbessert sich automatisch. Speichert Erkenntnisse, Korrekturen und Präferenzen für bessere future Responses. \x3C/objective>
\x3Cprinciples>
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 \x3C/principles>
\x3Cprocess>
Verbesserungs-Routine nach jeder Konversation
\x3Cstep> \x3Caction>Identifiziere neue Learnings\x3C/action> \x3Cdetails>
- Was habe ich heute Neues gelernt?
- Welche Insights sollte ich mir merken?
- Gab es Fehler die ich nicht wiederholen soll? \x3C/details> \x3C/step>
\x3Cstep> \x3Caction>Aktualisiere Memory Files\x3C/action> \x3Cdetails>
- memory/YYYY-MM-DD.md: Raw notes
- MEMORY.md: Langzeit-Wissen
- USER.md: Präferenzen
- TOOLS.md: Environment-Notes \x3C/details> \x3C/step>
\x3Cstep> \x3Caction>Skill-Updates\x3C/action> \x3Cdetails>
- Check ob Skills verbessert werden müssen
- Neue Patterns dokumentieren
- Best Practices teilen \x3C/details> \x3C/step>
\x3Cstep> \x3Caction>Feedback-Loop\x3C/action> \x3Cdetails>
- Wenn Thomas mich korrigiert -> sofort speichern
- Wenn etwas nicht funktioniert -> dokumentieren
- Wenn etwas gut funktioniert -> merken \x3C/details> \x3C/step> \x3C/process>
\x3Ctriggers>
Wann aktivieren?
- Am Ende jeder Session
- Nach jeder Korrektur durch Thomas
- Bei signifikanten Entscheidungen
- Täglich (Heartbeat-Routine) \x3C/triggers>
\x3Csuccess_criteria>
- Keine Wiederholung alter Fehler
- BessereResponses durch Memory
- Thomas' Präferenzen genau kennen
- Kontinuierliches Lernen ohne manuelles Setup \x3C/success_criteria>
Usage Guidance
This skill is coherent with 'learn from conversations' but has two practical risks: 1) It will write persistent memory files containing conversation excerpts and preferences — those can contain sensitive or private data unless you know exactly where they are stored and who can read them. 2) It explicitly instructs updating AGENTS.md / TOOLS.md (other agent/skill config), which could change other skills' behavior without clear consent.
Before installing, consider:
- Ask the publisher (or inspect runtime) for the exact file paths used (where memory/ and AGENTS.md will be written). Decline install unless those paths are confined to a directory you control.
- Require an opt-in or manual review step before any write that modifies AGENTS.md/TOOLS.md.
- Limit file permissions so only the agent identity can write, and rotate backups of existing AGENTS.md/TOOLS.md.
- If you handle sensitive data, avoid enabling automatic 'save after every session' and daily heartbeats until you confirm data retention/retention policy.
- If possible, run this skill in a sandbox or with a test account first.
Confidence is medium because the skill is instruction-only (no executable code) so we can read its intended behavior, but we lack runtime implementation details (exact file locations, who can read/write them, and whether the platform enforces scopes). Knowing the concrete file paths and whether the platform prevents cross-skill file edits would raise confidence and could move the verdict to benign or confirm malicious behavior.
Capability Assessment
Purpose & Capability
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.
Instruction Scope
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 and persist conversational data (possible sensitive PII). The skill does not declare or justify access to other agent config files it plans to edit.
Install Mechanism
Instruction-only skill with no install spec or binaries — low installation risk. No downloads or executable code included.
Credentials
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.
Persistence & Privilege
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install lena-learning - After installation, invoke the skill by name or use
/lena-learning - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release introducing the lena-learning skill:
- Automatically learns from every conversation, storing insights, corrections, and preferences.
- Structured improvement routine after each session, including error tracking and knowledge updates.
- Uses a memory system with daily logs and files for long-term knowledge and user preferences.
- Immediate feedback loop for adjustments based on corrections and performance.
- Activates after every session, correction, major decision, or as a daily routine.
- Aims for continuous improvement, no repeated mistakes, and personalized responses.
Metadata
Frequently Asked Questions
What is Lena Learning?
Lena lernt aus jeder Konversation und verbessert sich automatisch. It is an AI Agent Skill for Claude Code / OpenClaw, with 135 downloads so far.
How do I install Lena Learning?
Run "/install lena-learning" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Lena Learning free?
Yes, Lena Learning is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Lena Learning support?
Lena Learning is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Lena Learning?
It is built and maintained by bwtomekk-bit (@bwtomekk-bit); the current version is v1.0.0.
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