本文へ移動
cccskills
無料GitHub で公開

openviking-memory

OpenViking long-term memory plugin guide. Once installed, the plugin automatically remembers important facts from conversations and recalls relevant context before responding.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.6 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

OpenViking Memory Guide

How It Works

  • Auto-Capture: At afterTurn (end of one user turn run), automatically extracts memories from user/assistant messages
    • semantic mode: captures all qualifying user text, relying on OpenViking's extraction pipeline to filter
    • keyword mode: only captures text matching trigger words (e.g. "remember", "preference", etc.)
  • Auto-Recall: At before_prompt_build, automatically searches for relevant memories and injects them into context

Available Tools

memory_recall — Search Memories

Searches long-term memories in OpenViking, returns relevant results.

ParameterRequiredDescription
queryYesSearch query text
limitNoMaximum number of results (defaults to plugin config)
scoreThresholdNoMinimum relevance score 0-1 (defaults to plugin config)
targetUriNoSearch scope URI (defaults to plugin config)

Example: User asks "What programming language did I say I like?"

memory_store — Manual Store

Writes text to an OpenViking session and runs memory extraction.

ParameterRequiredDescription
textYesInformation text to store
roleNoSession role (default user)
sessionIdNoExisting OpenViking session ID

Example: User says "Remember my email is xxx@example.com"

memory_forget — Delete Memories

Delete by exact URI, or search and delete.

ParameterRequiredDescription
uriNoExact memory URI (direct delete)
queryNoSearch query (find then delete)
targetUriNoSearch scope URI
limitNoSearch limit (default 5)
scoreThresholdNoMinimum relevance score

Example: User says "Forget my phone number"

Configuration

FieldDefaultDescription
moderemotelocal (start local server) or remote (connect to remote)
baseUrlhttp://127.0.0.1:1933OpenViking server URL (remote mode)
apiKey—OpenViking API Key (optional)
agentIddefaultIdentifies this agent to OpenViking
configPath~/.openviking/ov.confConfig file path (local mode)
port1933Local server port (local mode)
targetUriviking://user/memoriesDefault search scope
autoCapturetrueAutomatically capture memories
captureModesemanticCapture mode: semantic / keyword
captureMaxLength24000Maximum text length per capture
autoRecalltrueAutomatically recall and inject context
recallLimit6Maximum memories injected during auto-recall
recallScoreThreshold0.01Minimum relevance score for recall
ingestReplyAssisttrueAdd reply guidance when detecting multi-party conversation text

Daily Operations

# Start (local mode: source env first)
source ~/.openclaw/openviking.env && openclaw gateway

# Start (remote mode: no env needed)
openclaw gateway

# Check status
openclaw status
openclaw config get plugins.slots.contextEngine

# Disable memory
openclaw config set plugins.slots.contextEngine legacy

# Enable memory
openclaw config set plugins.slots.contextEngine openviking

Restart the gateway after changing the slot.

Multi-Instance Support

If you have multiple OpenClaw instances, use --workdir to target a specific one:

# Install script
curl -fsSL ... | bash -s -- --workdir ~/.openclaw-openclaw-second

# Setup helper
npx ./examples/openclaw-plugin/setup-helper --workdir ~/.openclaw-openclaw-second

# Manual config (prefix openclaw commands)
OPENCLAW_STATE_DIR=~/.openclaw-openclaw-second openclaw config set ...

Troubleshooting

SymptomCauseFix
extracted 0 memoriesWrong API Key or model nameCheck api_key and model in ov.conf
port occupiedPort used by another processChange port: openclaw config set plugins.entries.openviking.config.port 1934
Plugin not loadedEnv file not sourced or slot not configuredCheck openclaw status output
Inaccurate recallrecallScoreThreshold too lowIncrease threshold or adjust recallLimit

🔗 Связи

  • [[MOC - MCP Servers]] — mcp-servers
  • [[000 - Map of Maps]] — Map of Maps

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

1password

無料

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.

日本語の概要は準備中です。原文の説明を表示しています。

ibragimov-oasis/vibe-coder22026年6月24日 更新

Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".

日本語の概要は準備中です。原文の説明を表示しています。

ibragimov-oasis/vibe-coder22026年6月24日 更新

Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.

日本語の概要は準備中です。原文の説明を表示しています。

ibragimov-oasis/vibe-coder22026年6月24日 更新

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

日本語の概要は準備中です。原文の説明を表示しています。

ibragimov-oasis/vibe-coder22026年6月24日 更新

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

日本語の概要は準備中です。原文の説明を表示しています。

ibragimov-oasis/vibe-coder22026年6月24日 更新

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

日本語の概要は準備中です。原文の説明を表示しています。

ibragimov-oasis/vibe-coder22026年6月24日 更新

ibragimov-oasis のスキルをすべて見る

このスキルの問題を報告する