Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Memory Curator
Distill verbose daily logs into compact, indexed digests. Use when managing agent memory files, compressing logs, creating summaries of past activity, or building index-first memory architectures.
skill openclawclawhub Free
Distill verbose daily logs into compact, indexed digests. Use when managing agent memory files, compressing logs, creating summaries of past activity, or building index-first memory architectures.
β¬ 0 downloads β
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.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, scripts/generate-digest.sh
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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- 77Darius77
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Memory Curator
Transform raw daily logs (often 200-500+ lines) into ~50-80 line digests while preserving key information.
Quick Start
# Generate digest skeleton for today ./scripts/generate-digest.sh # Generate for specific date ./scripts/generate-digest.sh 2026-01-30 Then fill in the <!-- comment --> sections manually.
Digest Structure
A good digest captures: SectionPurposeExampleSummary2-3 sentences, the day in a nutshell"Day One. Named Milo. Built connections on Moltbook."StatsQuick metricsLines, sections, karma, time spanKey EventsWhat happened (not everything, just what matters)Numbered list, 3-7 itemsLearningsInsights worth rememberingBullet pointsConnectionsPeople interacted withNames + one-line contextOpen QuestionsWhat you're still thinking aboutFor continuityTomorrowWhat future-you should prioritizeActionable items
Index-First Architecture
Digests work best with hierarchical indexes: memory/ βββ INDEX.md β Master index (scan first ~50 lines) βββ digests/ β βββ 2026-01-30-digest.md β βββ 2026-01-31-digest.md βββ topics/ β Deep dives βββ daily/ β Raw logs (only read when needed) Workflow: Scan index β find relevant digest β drill into raw log only if needed.
Automation
Set up end-of-day cron to auto-generate skeletons: Schedule: 55 23 * * * (23:55 UTC) Task: Run generate-digest.sh, fill Summary/Learnings/Tomorrow, commit
Tips
Compress aggressively β if you can reconstruct it from context, don't include it Names matter β capture WHO you talked to, not just WHAT was said Questions persist β open questions create continuity across sessions Stats are cheap β automated extraction saves tokens on what's mechanical
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
2 Docs1 Scripts
- SKILL.md
- README.md
- scripts/generate-digest.sh