Agenda‑Intelligence.md: a protocol that turns AI news summarizers into analysts (github.com)

A new protocol called Agenda-Intelligence.md has been introduced to enhance AI agents' capabilities in analyzing public agendas rather than merely summarizing news. This protocol establishes a structured workflow with an optional reasoning-memory component known as AnalysisBank, helping agents transition from superficial analysis to more substantive insights that support decision-making. The protocol addresses common pitfalls in AI-generated news analysis, requiring agents to classify information into categories such as facts, assessments, assumptions, and key indicators, thus fostering a deeper understanding of the implications surrounding policy, regulation, and geopolitics. The latest version, v0.4.0, adds a Source Acquisition Layer, which instructs agents on the types of sources needed for accurate claims regarding sanctions, regulations, and other critical agendas. By incorporating machine-readable formats and validating outputs against JSON schemas, Agenda-Intelligence.md aims to empower AI systems to ask more insightful questions, identify signal vs. noise, and enable operators to track potential shifts in various domains such as trade and energy. This represents a significant step towards increasing the decision value of AI-generated analyses, ultimately facilitating more informed and strategic responses to evolving public agendas.