Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Engram
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
skill openclawclawhub Free
Persistent semantic memory for AI agents — local, fast, free. Use when agent needs to recall past decisions, store new facts/preferences, search conversation history, or maintain context across sessions.
⬇ 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.
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.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.2.0
Provenance
- Publisher
- Dannydvm
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Engram — Agent Memory
Local semantic memory with biological decay, typed memories, and relationship graphs. No API keys. No cloud.
Boot Sequence
engram search "<current task or context>" --limit 10 Always recall before working. Accessed memories get salience-boosted.
Storing
engram add "Client uses React with TypeScript" --type fact --tags react,client engram add "We decided to pause ads" --type decision --tags ads echo "Raw conversation text" | engram ingest Types: fact, decision, preference, event, relationship
Searching
engram search "what tech stack" engram search "pricing decisions" --type decision engram search "client status" --agent client-agent
Relationships
engram relate <src> <tgt> --type supports engram auto-relate <id> engram relations <id> Types: related_to, supports, contradicts, caused_by, supersedes, part_of, references
Key Concepts
Decay: Unused memories lose salience daily. Recalled ones get boosted. Types: Filter by fact, decision, preference, event, relationship. Scoping: global, agent, private, shared. Dedup: >92% similarity auto-merges.
Quick Reference
engram stats engram recall --limit 10 engram export > backup.json engram import backup.json
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md