research-podcast
Turn papers, PDFs, reports, lecture notes, datasets, or research material into an evidence-aware AI podcast for deep dives, exam review, defense rehearsal, or multi-source briefings.
SKILL.mdSKILL.md
GitHubResearch Podcast
Create a traceable chain from research evidence to spoken dialogue.
Paths
SKILL_DIR: directory containing this file.DATA_DIR:~/.research-podcast.
Read QUALITY_RULES.md before drafting and PROMPT.md for dialogue style.
Workflow
- Read all supplied research material.
- Build
DATA_DIR/runs/<run-id>/source_map.jsonwith stable source IDs, source labels, locations when known, factual summaries, and supporting evidence. - Use the requested mode:
deep-dive,exam-review,defense, orbriefing; default todeep-dive. - Follow
PROMPT.mdand saveDATA_DIR/runs/<run-id>/script.json. Facts and interpretations require supportingsource_ids. - Validate before audio:
python SKILL_DIR/scripts/validate_script.py --script DATA_DIR/runs/<run-id>/script.json --sources DATA_DIR/runs/<run-id>/source_map.json
- For audio, create
DATA_DIR/venv, installscripts/requirements.txt, copyconfig/config.example.yamltoDATA_DIR/config.yaml, set both voice IDs, and ensureffmpegis installed. - Generate:
DATA_DIR/venv/bin/python SKILL_DIR/scripts/speak.py --script DATA_DIR/runs/<run-id>/script.json
The audio tool requests the provider credential interactively and writes an MP3 under DATA_DIR/episodes/.
Completion checks
Confirm the source map exists, the script validates, factual claims are traceable, and requested audio is non-empty.