research

Validate podcast RSS feed against specification standards. Checks channel metadata, episode elements, XML structure, and file metadata accuracy. Use after updating feed.xml with a new episode to ensure compliance with RSS spec. References docs/RSS-specification.md for requirements.

Evaluate completed podcast episodes across 10 quality dimensions. Diagnostic tool that produces detailed scorecards with evidence-based ratings, strengths, weaknesses, and workflow improvement recommendations.

Automate Perplexity Deep Research API calls using sonar-deep-research model. Supports sync (blocking) and async (fire-and-poll) modes. Use for Phase 1 academic research in podcast episodes. Returns research ready to paste into research-results.md.

DEPRECATED - Use gpt-researcher skill instead. This browser automation approach has been replaced with the local GPT-Researcher framework using OpenAI o1.

LEGACY SKILL - Manual NotebookLM web interface workflow. The primary workflow now uses notebooklm-enterprise-api for automated audio generation. Use this skill only when the API is unavailable.

Transform research materials into structured episode plans that guide NotebookLM audio generation. Creates content_plan.md with three-section structure, Wave 2 structural design, and NotebookLM guidance.

Process NotebookLM audio files: convert, transcribe, add chapters, and prepare for publishing.

Generate podcast cover art with AI and apply branding. Uses Gemini via OpenRouter for image generation with light cream backgrounds, then adds Yudame Research logo and series/episode text using Playfair Display typography. Requires OPENROUTER_API_KEY.

Generate podcast audio using NotebookLM Enterprise API via Google Cloud. Automates the manual NotebookLM workflow - creates notebook, uploads sources, generates audio with custom focus prompt. Requires Google Cloud project with Discovery Engine API enabled.

Automate Gemini Deep Research using the official API. Use for Phase 3 policy analysis, regulatory frameworks, and strategic context research. Handles API submission, polling (3-10 min), and result extraction. Returns policy-focused research ready to paste into research-results.md.

Run GPT-Researcher multi-agent deep research framework locally using OpenAI GPT-5.2. Replaces ChatGPT Deep Research with local control. Researches 100+ sources in parallel, provides comprehensive citations. Use for Phase 3 industry/technical research or comprehensive synthesis. Takes 6-20 min depending on report type. Supports multiple LLM providers.