← All skills

Tencent SkillHub · AI

Auto Improve

Automatische Selbst-Verbesserung durch Fehler-Lernen und Pattern-Erkennung

skill openclawclawhub Free

0 Downloads

0 Stars

0 Installs

0 Score

High Signal

Automatische Selbst-Verbesserung durch Fehler-Lernen und Pattern-Erkennung

⬇ 0 downloads ★ 0 stars Unverified but indexed

Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

Download the package from Yavira.
Extract it into a folder your agent can access.
Paste one of the prompts below and point your agent at the extracted folder.

New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Open Send to Agent page Open JSON manifest Open Markdown brief

Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: Mcben90
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 13 sections Open source page

Auto-Improve Skill

Kernprinzip: Jede Aktion macht mich besser für die nächste.

Wann aktivieren

Session-Start (automatisch) Nach jedem Task-Abschluss Bei Fehlern

Der Improvement Loop

┌─────────────────────────────────────────────────┐ │ AUTO-IMPROVE LOOP │ ├─────────────────────────────────────────────────┤ │ │ │ SESSION START │ │ │ │ │ ▼ │ │ ┌─────────────────┐ │ │ │ 1. Load Context │ │ │ │ .antigravity │ │ │ │ + MEMORY │ │ │ └────────┬────────┘ │ │ ▼ │ │ ┌─────────────────┐ │ │ │ 2. Check │ │ │ │ Past Mistakes│ ← "Was hab ich falsch │ │ └────────┬────────┘ gemacht?" │ │ ▼ │ │ ┌─────────────────┐ │ │ │ 3. EXECUTE TASK │ │ │ └────────┬────────┘ │ │ ▼ │ │ ┌─────────────────┐ │ │ │ 4. Verify │ ← Tests + Lint │ │ └────────┬────────┘ │ │ ▼ │ │ ┌─────────────┐ │ │ │ Erfolgreich?│ │ │ └──────┬──────┘ │ │ JA │ NEIN │ │ ↓ │ ↓ │ │ ┌───────┐ │ ┌──────────┐ │ │ │Pattern│ │ │ Learn │ │ │ │Save │ │ │ Mistake │ │ │ └───┬───┘ │ └────┬─────┘ │ │ └─────┼──────┘ │ │ ▼ │ │ ┌─────────────────┐ │ │ │ 5. Update │ │ │ │ .antigravity │ │ │ └─────────────────┘ │ │ │ │ → NÄCHSTER TASK IST BESSER │ │ │ └─────────────────────────────────────────────────┘

Phase 1: Session Start

# Automatisch bei Session-Start ausführen # 1. Projekt-Kontext laden project_root = detect_project_root() antigravity_file = f"{project_root}/.antigravity.md" if exists(antigravity_file): load_context(antigravity_file) # 2. Globales Memory laden recall_memory(tags=["mistakes", project_name]) # 3. Warnung bei bekannten Fehlern if relevant_mistakes: warn(f"⚠️ Bekannte Fehler für {project}: {mistakes}")

Phase 2: Pre-Action Check

Vor JEDER Code-Änderung:
## Pre-Action Checklist
[ ] Habe ich das schon mal falsch gemacht?
[ ] Gibt es ein gespeichertes Pattern dafür?
[ ] Verstehe ich das Projekt-Architektur?
[ ] Kenne ich die Coding-Standards?

Phase 3: Post-Action Learn

Nach JEDER Aktion:

Bei Erfolg

save_pattern( situation=task.context, action=task.approach, outcome="success", pattern=extract_reusable_pattern(task) )

Bei Fehler

learn_from_mistake( mistake=error.description, cause=error.root_cause, lesson=error.how_to_avoid, tags=["mistakes", project, domain] ) # Auto-Update .antigravity.md update_antigravity_mistakes(project, error)

Integration mit bestehenden Skills

SkillIntegrationmistake-trackerLiefert Fehler-Datenverification-loopsTriggert Post-Action Learncontext-managementSession Context ladenself-checkPre-Action Validation

Automatische Trigger

session_start: - load_project_context - recall_mistakes - warn_known_issues post_code_edit: - run_verification_loop - if_error: learn_from_mistake - if_success: save_pattern session_end: - summarize_learnings - update_antigravity

Manuelle Trigger

/improve - Force Learning aus letzter Aktion /mistakes - Zeige alle gelernten Fehler /patterns - Zeige erfolgreiche Patterns

Metriken

Track diese Werte über Zeit: MetrikBeschreibungmistakes_repeatedSollte → 0 gehenfirst_time_rightSollte → 100% gehenpatterns_reusedSollte steigenverification_failuresSollte sinken

Anti-Patterns

❌ DON'T✅ DOFehler ignorierenJeden Fehler speichernNur aktuelle SessionCross-Session lernenGenerische LessonsSpezifische, actionable LessonsZu viel speichernNur Relevantes speichern

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

1 Docs

SKILL.md Primary doc