Skill

Valence Memory

Persistent knowledge substrate for OpenClaw. Replaces flat-file memory with a structured knowledge system featuring semantic search, automatic compilation, and organic forgetting.

What It Does

Valence gives your agent real memory — not conversation logs, but a structured knowledge base that grows smarter over time:

• Memory Management — Store and recall memories with semantic search, importance scoring, and optional tags
• Auto-recall — Relevant memories are injected into context before the agent runs, no manual searching needed
• Auto-capture — Insights from conversations are extracted as memories automatically
• Knowledge Articles — Raw sources are automatically compiled into coherent, right-sized knowledge articles via LLM summarization
• Contention Detection — Contradictions between sources and articles are surfaced for resolution
• Organic Forgetting — Bounded-memory capacity with usage-based eviction keeps the knowledge base focused
• MEMORY.md sync — Disaster-recovery fallback so you lose nothing if you uninstall

Prerequisites

Valence v2 requires a running server with PostgreSQL + pgvector:

# Install Valence
pip install ourochronos-valence

# Start PostgreSQL with pgvector (Docker is easiest)
docker run -d --name valence-db \
  -e POSTGRES_DB=valence \
  -e POSTGRES_USER=valence \
  -e POSTGRES_PASSWORD=valence \
  -p 5432:5432 \
  pgvector/pgvector:pg17

# Run migrations
valence migrate up

# Start the server
valence serve

The server runs at http://127.0.0.1:8420 by default.

Install the Plugin

openclaw plugins install @ourochronos/memory-valence

Configure

Add to your OpenClaw config (~/.openclaw/openclaw.json):

{
  "plugins": {
    "slots": {
      "memory": "memory-valence"
    },
    "entries": {
      "memory-valence": {
        "enabled": true,
        "config": {
          "serverUrl": "http://127.0.0.1:8420",
          "autoRecall": true,
          "autoCapture": true,
          "memoryMdSync": true
        }
      }
    }
  }
}

Or use the OpenClaw Control UI to configure via the web interface.

Configuration Options

Agent Tools

The plugin exposes 13 v2 tools organized by category:

Memory Management (most commonly used)

• memory_store — Store a memory for later recall
• memory_recall — Search and recall memories (used by auto-recall)
• memory_status — Get memory system statistics
• memory_forget — Mark a memory as forgotten (soft delete)

Knowledge Search

• knowledge_search — Unified search across articles and sources (ranked by relevance, confidence, freshness)

Source Management

• source_ingest — Ingest a new source (document, conversation, web, code, observation, tool output, user input)
• source_search — Full-text search over sources

Article Management

• article_get — Get an article by ID, optionally with provenance
• article_compile — Compile sources into a new article via LLM
• article_update — Update an article's content

Contention Resolution

• contention_list — List active contradictions between sources and articles
• contention_resolve — Resolve a contention (supersede_a, supersede_b, accept_both, dismiss)

System Administration

• admin_stats — Health and capacity statistics

File-based Fallback

• memory_search / memory_get — Search and read MEMORY.md (DR fallback when server is unreachable)

How It Works

1. On each agent turn, auto-recall searches Valence for memories relevant to the current conversation and injects them as context
2. During conversations, the agent uses memory_store to capture decisions, preferences, and insights
3. After conversations, auto-capture extracts any uncaptured insights
4. Sources compile into articles automatically based on usage patterns and semantic clustering
5. Over time, the knowledge base self-organizes through usage-based scoring and organic forgetting
6. MEMORY.md is kept in sync as a human-readable snapshot and safety net

Architecture

OpenClaw Agent
    ↕ (plugin tools + hooks)
memory-valence plugin
    ↕ (HTTP MCP)
Valence Server (http://127.0.0.1:8420)
    ↕ (SQL + pgvector)
PostgreSQL + pgvector

The plugin is a thin HTTP client. All intelligence lives in the Valence server — embeddings, article compilation, usage scoring, contention detection, and organic forgetting.

Links

• Valence: github.com/ourochronos/valence | PyPI
• Plugin: github.com/ourochronos/valence-openclaw | npm
• Issues: github.com/ourochronos/valence/issues