Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Memory Architect
Restructure flat MEMORY.md files into a tiered memory system with an entity graph. Use when: (1) MEMORY.md is growing unwieldy or exceeds 150 lines, (2) user...
skill openclawclawhub Free
Restructure flat MEMORY.md files into a tiered memory system with an entity graph. Use when: (1) MEMORY.md is growing unwieldy or exceeds 150 lines, (2) user...
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
- 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
- 1.0.0
Provenance
- Publisher
- kapslap
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Memory Architect
Split a monolithic MEMORY.md into three tiers plus a structured entity graph.
Architecture
MEMORY.md β Router (30 lines max). Points to tiers. memory/protocols.md β HOT: Stable workflows, shortcuts, procedures. Read on session start. memory/active.md β WARM: Current projects, waiting-on, live context. Check before acting. memory/archive.md β COLD: Completed work, historical reference. Search when needed. memory/ontology/graph.jsonl β Structured entities + relations (JSONL append-only)
1. Analyze the existing MEMORY.md
Read the full file. Classify each section: Content typeTierExamplesStable workflow / procedureprotocolsEmoji shortcuts, deploy steps, tool usage rulesActive project / waiting-onactiveCurrent builds, pending replies, live URLsCompleted work / reference dataarchiveDone tasks, contact lists, account tables, old decisionsNamed entity with propertiesontologyPeople, orgs, projects, properties, locations
2. Create the tier files
Write each tier file with a header comment explaining its purpose and update frequency. protocols.md rules: Only procedures that rarely change Include the exact commands (copy-pasteable) No project-specific state active.md rules: Only things with a next action or pending status Include "Waiting On" section at bottom Prune completed items to archive on each update archive.md rules: Completed work grouped by date or category Reference data (contacts, accounts, chat IDs) Keep searchable β use headers and tables
3. Extract entities to ontology
For each named person, organization, project, property, or location, create a JSONL entry: {"op":"create","entity":{"id":"p_alice","type":"Person","properties":{"name":"Alice","email":"alice@example.com","role":"Engineer"}},"timestamp":"2026-01-01T00:00:00Z"} {"op":"relate","from":"p_alice","rel":"member_of","to":"org_acme","timestamp":"2026-01-01T00:00:00Z"} ID conventions: People: p_shortname Organizations: grp_name or org_name Projects: proj_name Properties/locations: prop_name or loc_name Relation types: member_of, owns, collaborates_on, interested_in, guides, uses, listed_by, located_at
4. Rewrite MEMORY.md as router
Replace MEMORY.md with a ~25-line index that: Lists the three tiers with one-line descriptions Notes the ontology location Preserves any system directives (NO_REPLY rules, heartbeat instructions) Contains zero project-specific content
5. Verify
wc -l MEMORY.md memory/protocols.md memory/active.md memory/archive.md memory/ontology/graph.jsonl Targets: MEMORY.md under 30, protocols under 100, active under 80, graph = 1 line per entity/relation.
On each session
Read memory/protocols.md (always) Scan memory/active.md (always) memory/archive.md β only on memory_search or explicit request
When adding new information
New procedure β protocols.md New project/active item β active.md Completed item β move active β archive New person/org/project β append to graph.jsonl
Entity queries
grep "p_forrest" memory/ontology/graph.jsonl grep '"type":"Project"' memory/ontology/graph.jsonl cat memory/ontology/graph.jsonl | jq -r 'select(.entity?.type=="Person") | .entity.properties.name'
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