Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Enakoneschniy/claude-dev-stacknpx agentmods add skills/enakoneschniy/claude-dev-stack/dev-researchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/enakoneschniy/claude-dev-stack/dev-research)<a href="https://agentmods.dev/skills/enakoneschniy/claude-dev-stack/dev-research"><img src="https://agentmods.dev/badge/skills/enakoneschniy/claude-dev-stack/dev-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/enakoneschniy/claude-dev-stack/dev-research"><img src="https://agentmods.dev/badge/skills/enakoneschniy/claude-dev-stack/dev-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00177 | $0.01390 |
| Opus 5.5 | $0.00071 | $0.00556 |
| Sonnet 5.5 | $0.00035 | $0.00278 |
| Haiku 4.5 | $0.00018 | $0.00139 |
Grade A, and why
dev-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dev Research Skill
Integrates NotebookLM into development workflow for grounded, citation-backed research. Uses notebooklm-py CLI for all NotebookLM interactions.
Prerequisites
# 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.
# 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.
# 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.
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 195 lines · 177 tokens per session scan A 2f0253e243f3
dev-research is a skill published in the GitHub repository Enakoneschniy/claude-dev-stack (5 stars, last pushed 1mo ago), licensed MIT. It adds 177 tokens to every session and 1,390 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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