ai-assist-discovery

Discovery reports transform ambiguous research questions into structured, evidence-backed outputs by applying analytical frameworks. The process delivers executive summaries, key findings, detailed sections, and cited sources to guide technology choices and domain explorations.

Framework-driven analysis applies templates like SWOT, ADR, PESTLE, and risk registers to evaluate technologies and investigate codebases. These frameworks are tailored to the target type and depth, producing structured analytical reports for decision-making.

Cited research reports link every claim to explicit sources with clear confidence levels. This evidence-backed approach supports feasibility studies, data-source assessments, and domain explorations by providing structured documentation with tagged source reliability.

Hierarchical templates loaded from frameworks references support domain exploration and data-source assessments. The system applies frontmatter-driven discovery requirements, outputting template-compliant formats with executive summaries, key findings, and cited sources.

Evidence-backed findings are structured into executive summaries, key findings, detailed sections, and appendices. This template-compliant format applies appropriate analytical frameworks to deliver cited sources with confidence tagging for technology decision-making.

The discovery workflow supports codebase analysis without external dependencies. It applies default discovery workflows with analytical frameworks to produce structured, source-backed reports for investigating codebases, technologies, and data sources.