Source Boundaries
Each source has a manifest record with title, type, license, path, checksum, and processing status.
Project Brief
A generalized pipeline for converting unstructured content into source-bounded information objects, searchable corpora, transcript enrichment packets, and targeted source-grounded analytical reports.
Implemented Pipeline
Ingest synthetic source notes, staged video transcripts, and OCR cleanup examples; build checksum-backed manifests; normalize and segment the corpus; preserve citations; and generate method packs for source-grounded analysis.
Evidence
Each source has a manifest record with title, type, license, path, checksum, and processing status.
Twenty corpus segments carry source IDs and citation labels, so report claims can be traced back to supporting passages.
The staged media demo emits three enrichment packets that simulate an OpenAI-style cleanup pass without making a network request.
The demo uses synthetic notes only and excludes private transcripts, course identifiers, student records, and credentials.
Next Build Direction
The current status report identifies the next strategic tool: a unified converter for cleaned transcripts, OCR outputs, and public-safe documents. That converter should produce stable manifest, normalized artifact, corpus, index, and safety-review objects before a general agent context packet generator is added.
reports/artifact-conversion-and-agent-context-status.mddocs/transcript-enrichment-workflow.mdsample_outputs/information-object-map.jsonsample_outputs/cloud_video_transcription/transcript_enrichment_brief.mdsample_outputs/analysis-method-pack.jsonSafety Boundary
Public examples must use synthetic, sanitized, public-domain, or clearly licensed source material. Do not publish professor names, university course identifiers, private LMS links, copyrighted transcripts, raw lecture text, private video URLs, private lecture manifests, or coursework-specific prompts.