customer-problems
Identify and document Customer Problems (CP) from business context. Use when starting requirements engineering or when stakeholders describe solutions instead of problems. Step 1 of Problem-Based SRS methodology.
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344 skills found
Identify and document Customer Problems (CP) from business context. Use when starting requirements engineering or when stakeholders describe solutions instead of problems. Step 1 of Problem-Based SRS methodology.
A specialized code review agent that performs multi-dimensional analysis covering security vulnerabilities, performance optimization, code quality, and maintainability standards.
Unified CLI tool to read, query, discover, and write AI agent conversations using the agents:// URI scheme across multiple coding agents and providers.
Plan, implement, and execute user acceptance tests (UAT) and end-to-end scenarios to validate requirements against user-visible behavior.
Expert skill for Next.js Server Actions, covering form handling, data mutations, revalidation, and optimistic UI updates in the App Router.
Maintains a detailed, step-by-step implementation diary for coding sessions with docmgr integration to track changes, rationale, commands, and failures.
Automated quality assurance system that validates markdown deliverables against defined checklists for PB-000 market research workflows.
Monitor Runwall security posture, enabled guardrails, and recent audit logs for Claude Code, Codex, and MCP-based development environments.
Autonomous multi-agent LinkedIn system using LangGraph and Claude Opus 4.5 for trend research, content creation, voice profiling, and analytics-driven optimization.
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Generate scaffolding for custom Minecraft Bedrock packet analyzers. Includes template code, registration guides, and packet capture workflows.
Captures session learnings into Reusable Intelligence Infrastructure (RII). Converts one-time bug fixes and pattern discoveries into permanent agent-executable knowledge to prevent recurrence and accelerate future development.