enakoneschniy/claude-dev-stack/dev-research

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Use NotebookLM for grounded research — documentation queries, stack comparisons, session log search. Trigger when user needs answers FROM SPECIFIC DOCUMENTATION or FROM PAST SESSIONS: "по документации", "check docs", "как в Payload", "как в Next.js", "что мы решили про", "when did we decide", "по нашим записям", "спроси в нотбуке", "ask notebooklm", "query notebook", "загрузи доки", "load docs", "add to notebook", "найди в сессиях", "search sessions", "когда мы делали". Also for structured comparisons: "сравни X и Y по документации", "compare based on docs". Requires notebooklm-py. For WEB research (current info, trends), use deep-research skill instead.

Install

npx vskill@latest install enakoneschniy/claude-dev-stack/dev-research

SKILL.md

Dev Research Skill

Integrates NotebookLM into development workflow for grounded, citation-backed research. Uses notebooklm-py CLI for all NotebookLM interactions.

Prerequisites

bash
# Check if notebooklm-py is installed
which notebooklm || echo "Install: pip install 'notebooklm-py[browser]'"
# Check auth
notebooklm auth check --test

Notebooks Convention

Each dev notebook follows naming: [Project] — [Purpose]

Examples:

  • "Crypto Portal — Stack Docs" (Payload CMS, Next.js docs)
  • "AI News Portal — CMS Research" (comparing CMS options)
  • "Dev Sessions Archive" (all session logs for cross-project search)

Commands

/research TOPIC

Research a topic using NotebookLM's grounded answers.

bash
# Check if relevant notebook exists
notebooklm list 2>/dev/null | grep -i "TOPIC"
# If not, create one
notebooklm create "Research — TOPIC"
notebooklm use <notebook_id>
# Add sources — user provides URLs, or we search
notebooklm source add "URL1"
notebooklm source add "URL2"
notebooklm source add "./local-doc.md"
# Ask questions
notebooklm ask --json "QUESTION"

Parse JSON response and extract:

  • Answer text
  • Citations with source references
  • Confidence indicators
/docs-query QUESTION

Query project documentation notebook.

bash
# Use the project's docs notebook
notebooklm use <project-docs-notebook-id>
notebooklm ask --json "QUESTION"

This gives grounded answers from actual documentation, not hallucinations.

/compare OPTION1 vs OPTION2

Create a structured comparison using NotebookLM.

bash
notebooklm create "Comparison — OPTION1 vs OPTION2"
# Add documentation for both options
notebooklm source add "URL_OPTION1_DOCS"
notebooklm source add "URL_OPTION2_DOCS"
# Structured comparison questions
notebooklm ask --json "Compare OPTION1 and OPTION2 for: performance, DX, ecosystem, production readiness"
notebooklm ask --json "What are the main trade-offs between OPTION1 and OPTION2?"
notebooklm ask --json "Which is better for: [specific use case]?"
# Generate mind-map for visual comparison
notebooklm generate mind-map
notebooklm download mind-map ./vault/research/COMPARISON.json
/load-docs PROJECT

Load current project documentation into NotebookLM.

bash
PROJECT_NAME=$(basename $(git rev-parse --show-toplevel 2>/dev/null || pwd))
VAULT=${VAULT_PATH:-~/vault}
# Create or reuse notebook
notebooklm create "$PROJECT_NAME — Documentation"
# Add from vault
for f in "$VAULT/projects/$PROJECT_NAME/decisions/"*.md; do
notebooklm source add "$f"
done
# Add architecture docs from project
find . -name "*.md" -maxdepth 2 | head -20 | while read f; do
notebooklm source add "$f"
done
echo "Loaded docs for $PROJECT_NAME into NotebookLM"
/archive-sessions

Upload session logs to NotebookLM for cross-project search.

bash
VAULT=${VAULT_PATH:-~/vault}
# Use or create archive notebook
notebooklm create "Dev Sessions Archive"
# Upload recent sessions from all projects
for project_dir in "$VAULT/projects"/*/sessions/; do
for session in $(ls -t "$project_dir"*.md 2>/dev/null | head -10); do
notebooklm source add "$session"
done
done

Now you can ask: "When did we last deal with caching issues?" across all projects.

Output to Obsidian

All NotebookLM research outputs go to the vault:

bash
VAULT=${VAULT_PATH:-~/vault}
# Mind maps
notebooklm download mind-map "$VAULT/research/TOPIC-mindmap.json"
# Research notes (from JSON answers)
# Parse and format as Obsidian markdown with wikilinks
Formatting NotebookLM answers for Obsidian

When saving answers to vault:

  1. Convert citations to wikilinks: [1] → [[Source Name#passage]]
  2. Add YAML frontmatter: date, notebook, question, sources
  3. Create topic files if they don't exist
  4. Add backlinks from source files

Example output file:

markdown
---
date: 2026-04-06
notebook: "Crypto Portal — Stack Docs"
question: "How does Payload CMS handle field hooks?"
sources: ["Payload CMS Docs", "Next.js Integration Guide"]
---
# How Payload CMS handles field hooks
[answer with wikilinks to sources]
## Sources
-[[Payload CMS Docs]] — field lifecycle
-[[Next.js Integration Guide]] — integration patterns

Audio Briefings

Generate audio briefing for a project:

bash
notebooklm generate audio "Brief project status and key decisions" --wait
notebooklm download audio "$VAULT/projects/$PROJECT/briefing-$(date +%Y-%m-%d).mp3"

Listen on phone via Obsidian Sync while commuting.

Limitations & Notes

  • Rate limit: ~50 queries/day on free Google account
  • NotebookLM uses undocumented Google APIs — may break
  • Browser automation requires local Chromium — won't work in Docker devcontainer
  • Sources max: 300 per notebook
  • Best for: documentation, comparisons, cross-source search
  • NOT for: running code, real-time data, live APIs

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
5
7-day trend score
9

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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