Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
OpenClaw Universal Memory
Generic Postgres and pgvector memory layer for connector-agnostic data ingestion, incremental sync, and searchable chunk storage with cursor history.
skill openclawclawhub Free
Generic Postgres and pgvector memory layer for connector-agnostic data ingestion, incremental sync, and searchable chunk storage with cursor history.
โฌ 0 downloads โ
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, scripts/run_memory.py, setup.json
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
- marcosathanasoulis
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
OpenClaw Universal Memory
This skill provides a generic memory layer for heterogeneous data: canonical entity/chunk schema, connector-style ingestion with cursors, searchable memory in Postgres.
Use Cases
Normalize records from multiple systems into one schema. Keep incremental sync history (cursor per connector/account). Build RAG-ready chunk storage in pgvector.
Prerequisites
Postgres with vector extension. Local package installed: pip install -e .. Python dependency for DB I/O: pip install "psycopg[binary]>=3.2" DSN provided via environment variable (DATABASE_DSN by default).
Security Boundaries
Do not pass raw passwords/tokens in command-line arguments. Prefer OS secret store or process environment injection for DSN. This skill only reads/writes your configured Postgres database; it does not call external APIs directly. Use least-privilege DB credentials (SELECT/INSERT/UPDATE/DELETE on um_* tables only). Review and trust any custom connector before running it.
Responsible Use Caveat
Use this only for accounts/data you legitimately control or are authorized to process. You are responsible for privacy, retention, and regulatory compliance. This project is provided under Apache 2.0 without operational warranty. This implementation is mostly AI-generated code with experienced engineer oversight; validate before production use.
Commands
Store DB credentials once (recommended): python skills/openclaw-universal-memory/scripts/run_memory.py \ --action configure-dsn Initialize schema: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action init-schema \ --dsn-env DATABASE_DSN Ingest JSON/NDJSON: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action ingest-json \ --dsn-env DATABASE_DSN \ --source gmail \ --account marcos@athanasoulis.net \ --entity-type email \ --input /path/to/records.ndjson Ingest from built-in connectors: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action ingest-connector \ --connector google \ --account you@example.com \ --dsn-env DATABASE_DSN \ --limit 300 Validate connector auth/config before ingest: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action validate-connector \ --connector google \ --account you@example.com \ --dsn-env DATABASE_DSN \ --limit 1 Search: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action search \ --dsn-env DATABASE_DSN \ --query "Deryk" \ --limit 20 Recent ingest history: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action events \ --dsn-env DATABASE_DSN \ --limit 20 Doctor check: python skills/openclaw-universal-memory/scripts/run_memory.py \ --action doctor Scheduling reference: docs/SCHEDULING.md (cron examples, 15-minute default, connector toggles)
Connector Contract (for custom adapters)
A connector returns normalized records + next cursor: external_id entity_type title body_text raw_json meta_json next_cursor This keeps ingestion generic and supports arbitrary source systems. Starter connector templates: src/openclaw_memory/connectors/templates.py Step-by-step setup guide (Gmail/Slack/Asana/iMessage): docs/CONNECTOR_SETUP_WALKTHROUGH.md
Community
We welcome connector contributions via PR. See docs/CONNECTOR_CONTRIBUTING.md for required contract, tests, and setup instructions.
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 Docs1 Scripts1 Config
- SKILL.md
- scripts/run_memory.py
- setup.json