需求分析→系统设计→代码执行→质量审计→交付验收，一键完成大型项目全自动开发。 Requirements Analysis → System Design → Code Execution → Quality Audit → Delivery Acceptance. One command to autonomously develop large-scale projects.
This Skill is built on practical expertise in AI agent safety, prompt-injection defense, source-to-sink privacy review, tool and MCP metadata integrity, memory provenance checks, autonomous action scoping, and evidence-based verification. It helps agents separate instructions from evidence before tool calls, uploads, publishing, deletion, code execution, or network output.
This Skill is built on practical expertise in long-running AI workflow control, constraint tracking, handoff reliability, completion evidence, and instruction-change recovery. It helps agents keep the user's first, middle, and latest requirements aligned across multi-step work so older assumptions do not override newer directions and completion is backed by observable evidence.
Based on an MIT-licensed open-source agent skill. Unofficial and not affiliated with ASD or STEMG.
AI Integration — Plans and builds LLM API connections (OpenAI, Anthropic, and more) into real apps. Covers model selection, cost estimation, key safety, error handling, and working code. Adapts to non-engineers and developers alike. Stops the #1 mistake: shipping your API key to the browser.