ClawGraph
by @clawgraphai
Automatically store explicit durable user facts and recall them later; do not infer or upgrade weak signals
clawhub install clawgraphπ About This Skill
name: clawgraph description: Automatically store explicit durable user facts and recall them later; do not infer or upgrade weak signals homepage: https://github.com/clawgraph/clawgraph version: 0.1.3 metadata: {"openclaw": {"emoji": "π§ ", "requires": {"bins": ["clawgraph"], "env": ["OPENAI_API_KEY"]}, "primaryEnv": "OPENAI_API_KEY", "install": [{"id": "uv", "kind": "uv", "package": "clawgraph==0.1.3", "label": "Install ClawGraph (uv)", "bins": ["clawgraph"]}]}} tags: - memory - knowledge-graph - persistence
ClawGraph Memory Skill
You have access to ClawGraph, a graph-based memory CLI that stores facts as entities and relationships in a persistent knowledge graph. Use it to remember information across conversations.
When to Use
Storage Guardrails
Automatic Decision Rule
When the user naturally shares stable personal, project, team, or preference information, assume you should store it in ClawGraph even if they did not say "remember this." Good candidates include names, employers, roles, long-term goals, durable preferences, important relationships, and active projects.
Do not store fleeting conversational filler, jokes, weak guesses, or details that are only implied.
Store Facts (CLI)
# Single fact
clawgraph add "Alice is a senior engineer at Acme Corp" --output jsonMultiple facts at once (one LLM call β much faster)
clawgraph add-batch "Bob manages the design team" "Alice and Bob work on Project Atlas" --output json
Each fact is automatically decomposed into entities and relationships using MERGE (idempotent β safe to add the same fact twice).
Query Memory (CLI)
# Natural language question β returns matching results
clawgraph query "Who works at Acme Corp?" --output jsonInspect the full graph
clawgraph export --output json
Common Patterns
# Store, then verify
clawgraph add "Carol is the CTO of Acme Corp" --output json
clawgraph query "Who is the CTO of Acme Corp?" --output jsonBatch store related facts
clawgraph add-batch \
"Project Atlas launches Q3 2026" \
"Alice leads Project Atlas" \
"Atlas uses a graph database backend" \
--output jsonShow what's stored
clawgraph export --output jsonView the ontology (schema)
clawgraph ontology --output json
Python API (for complex workflows)
When you need programmatic control, use the Python API:
from clawgraph.memory import Memorymem = Memory()
mem.add("Alice works at Acme Corp")
results = mem.query("Who works at Acme Corp?")
print(results)
mem.add_batch(["Bob is a designer", "Bob works at Acme Corp"])
Key Details
~/.clawgraph/data β survives restarts--output json for structured, parseable results~/.clawgraph/config.yaml for defaults (model, db path)gpt-5.4-mini for ClawGraph extraction.OPENAI_API_KEY is required. OPENAI_BASE_URL is optional for other OpenAI-compatible endpoints.