oraclaw-graphNetwork intelligence for AI agents. PageRank, community detection (Louvain), critical path, and bottleneck analysis for any graph of connected things.
Install via ClawdBot CLI:
clawdbot install whatsonyourmind/oraclaw-graphGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://oraclaw.dev/graphAudited Apr 16, 2026 · audit v1.0
Generated Oct 7, 2026
A product team models epics, tasks, and blockers as a graph, then runs bottleneck and critical path analysis to find which single task blocks the most downstream work. PageRank surfaces the most influential tasks across the sprint so planning focuses on leverage points rather than loudest requests.
An HR analytics team builds a graph of teams, managers, and cross-functional dependencies to identify informal connectors and single points of failure. Louvain communities reveal siloed sub-organizations while PageRank highlights high-influence individuals who drive information flow.
A fintech risk team treats accounts, devices, and transactions as nodes and edges, using Louvain clustering to surface tightly connected fraud rings. Bottleneck and PageRank scores prioritize the accounts most central to laundering flows for manual review.
A logistics planner models suppliers, warehouses, and routes as a dependency graph, calculating the critical path from source to delivery. Bottleneck detection identifies single-source suppliers or transit nodes whose failure cascades across the network.
An SEO team builds a knowledge graph of topics, entities, and internal links to find high-influence hub pages with PageRank. Community detection groups related topic clusters to guide content pillars and interlinking strategy.
Charge developers $0.05 USDC per graph analysis call via x402 on Base, with a free tier of 500 analyses per month to drive adoption. Usage-based billing scales naturally with customer graph size and query frequency.
License the OraClaw Graph engine as an embedded module inside project management, CRM, or observability platforms, letting those products offer network intelligence as a premium feature. Revenue comes from per-seat or per-workspace subscriptions bundled by the host platform.
Offer enterprise customers higher rate limits, dedicated compute, private graph processing, and SLAs beyond the free tier. This captures larger organizations with compliance and scale requirements that the metered public API cannot serve.
💬 Integration Tip
Set the ORACLAW_API_KEY environment variable before calling analyze_decision_graph, and normalize node confidence/impact/urgency values to 0–1 to get accurate PageRank and bottleneck rankings. Start by modeling 10–20 nodes and their typed edges to validate outputs before scaling to production graphs.
Scored Oct 7, 2026
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