1. A method performed by a computer-implemented content suggestion engine for determining suggested content from a human activity recommendation information system, comprising: obtaining context-sensitive content relevant to attainment of an overall selected goal that is attempted by a human subject, the context-sensitive content produced from content data stored in the human activity recommendation information system, wherein the overall selected goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities; determining a set of conditions relevant to the attainment of the overall selected goal to establish a filter and a weight for restricting and prioritizing the context-sensitive content, the set of conditions including one or more conditions obtained from a profile of the human subject, wherein the profile tracks one or more behavior characteristics affecting the attainment of the overall selected goal by the human subject; matching the context-sensitive content to the human subject according to the set of conditions, the matching including applying the filter to exclude content from the context-sensitive content that does not match the set of conditions; prioritizing the context-sensitive content to the human subject according to the set of conditions, the prioritizing including applying the weight to prioritize content in the context-sensitive content that provides a greater match to the profile of the human subject; and selecting suggested content from the filtered and prioritized context-sensitive content for presentation to the human subject.