OraClaw Pathfind
Skill Verified ActiveA* pathfinding and task sequencing for AI agents. Find the optimal path through workflows, dependencies, and decision trees. K-shortest paths via Yen's algorithm. Cost/time/risk breakdown.
To equip AI agents with deterministic mathematical tools for finding optimal paths and sequencing tasks, overcoming LLM limitations in algorithmic reasoning.
Features
- A* pathfinding for optimal routes
- K-shortest paths via Yen's algorithm
- Cost, time, and risk breakdown
- Configurable heuristics (cost, time, risk, weighted, zero)
- Task sequencing and workflow navigation
Use Cases
- Finding the fastest/cheapest/safest path through a task dependency graph
- Sequencing tasks optimally considering time, cost, and risk
- Navigating complex workflows with multiple routes to completion
- Planning project execution order with dependency constraints
Non-Goals
- LLM-based reasoning or hallucination
- Real-time execution of tasks
- Complex simulation beyond path analysis
Practices
- Algorithm selection
- Optimization
- Task planning
Prerequisites
- ORACLAW_API_KEY environment variable (for premium features/higher rate limits)
- Access to the OraClaw API or MCP Server
Installation
npx skills add Whatsonyourmind/oraclawRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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