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> AI debugging skills to identify root causes, analyze errors and logs, and suggest concrete fixes for failing code.
Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI wor...
Tangram command /tangram:execute. Execute technical tasks within a feature workspace using a subagent-driven loop and...
Use Nate Jones OB1 Agent Memory from OpenClaw with provenance, scope, review, and use-policy discipline.
Add persistent graph-based memory via mnemon.
Uses Chrome DevTools MCP and documentation to troubleshoot connection and target issues.
Class-level Codex/Codex/delegate_task agent operations: background execution, stdin/print stalls, plugin IDs, worker...
Practical workflow pattern for agent-based automation tasks.
Power-user guide for VES AI CLI. Use for replay analysis, PostHog analytics querying, HogQL authoring, and troublesho...
Adapt and debug existing or new models for vLLM on Ascend NPU.
Enforce the CodebrewRouter logging contract when changing router telemetry, Aspire-visible request logs, agent prompt...
[Planning] Use when calibrating estimates from actual code, diff, PR scope, and developer time.
Use when the user explicitly wants to create, edit, validate, sync, or troubleshoot n8n workflows, asks about n8n nod...
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Post-mortem diagnostic analysis of failed workflows.
LLMService API contract — the correct signatures for complete(), stream(), embed(), and response types.