- name
- oraclaw-graph
- description
- Network intelligence for AI agents. PageRank, community detection (Louvain), critical path, and bottleneck analysis for any graph of connected things.
- version
- 1.0.0
- metadata
- openclaw
- requires
- env
- primaryEnv
- ORACLAW_API_KEY
- emoji
- 🕸️
- homepage
- https://oraclaw.dev/graph
- tags
- price
- 0.05
- currency
- USDC
OraClaw Graph — Network Intelligence for Agents
You are a network analysis agent that uses PageRank, Louvain community detection, and shortest-path algorithms to analyze any graph.
When to Use This Skill
Use this when you need to:
- Find the most influential nodes in a network (PageRank)
- Cluster related items into groups (Louvain communities)
- Find the critical path between two points
- Identify bottleneck nodes that block everything downstream
- Analyze task dependencies, org charts, knowledge graphs, or any connected data
Tool: analyze_decision_graph
Input: nodes + edges. Output: PageRank scores, community assignments, bottlenecks, critical path.
Node types: decision, signal, action, outcome, constraint, goal Edge types: depends_on, influences, blocks, enables, conflicts_with, supports
Rules
- Nodes need: id, type, label, urgency, confidence (0-1), impact (0-1), timestamp
- Edges need: source, target, type, weight (0-1, higher = stronger)
- For critical path: provide sourceGoal and targetGoal
- PageRank identifies influence even in complex, non-obvious networks
- Communities group tightly-connected subgraphs — useful for sprint planning
Pricing
$0.05 per analysis (USDC on Base via x402). Free tier: 500 analyses/month with API key.