research-deep

research-deep is a command for Claude Code from Galbaz1/video-research-mcp. It costs 9 tokens per session (1,215 once invoked), scanned A, original, MIT.

A command that starts Gemini's web-based research agent after interviewing the user to define a research brief. It also checks stored knowledge and earlier research before beginning.

In plain words
What is it for?
Preparing research briefs, checking existing analyses, and launching longer web-grounded research tasks. The listing says these tasks typically take 10–20 minutes and cost $2–5.
Why use it?
It helps turn a broad research request into a focused question and avoids overlooking relevant previous findings.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; names the AskUserQuestion tool; positional $N argument.

Part of the gr plugin — 12 skills, 17 commands, 7 agents shipped together

Good fit Preparing research briefs, checking existing analyses, and launching longer web-grounded research tasks. The listing says these tasks typically take 10–20 minutes and cost $2–5.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/galbaz1/video-research-mcp/research-deep
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/Galbaz1/video-research-mcp

Made for: Claude Code.

Or install gr, the plugin that ships this one along with the rest of its 12 skills, 17 commands, 7 agents.

Wrote 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.

agentmods badge for research-deep

README.md
[![agentmods](https://agentmods.dev/badge/commands/galbaz1/video-research-mcp/research-deep/github.svg)](https://agentmods.dev/commands/galbaz1/video-research-mcp/research-deep)
Your own site
<a href="https://agentmods.dev/commands/galbaz1/video-research-mcp/research-deep"><img src="https://agentmods.dev/badge/commands/galbaz1/video-research-mcp/research-deep/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.

agentmods 80×15 button for research-deep

Your own site · 80×15
<a href="https://agentmods.dev/commands/galbaz1/video-research-mcp/research-deep"><img src="https://agentmods.dev/badge/commands/galbaz1/video-research-mcp/research-deep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,215 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00009 $0.01215
Opus 5 $0.00005 $0.00607
Sonnet 5 $0.00002 $0.00243
Haiku 4.5 $0.00001 $0.00121

Measured 10d ago against content hash 5dfc17404af9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

research-deep 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 10d 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.

commands/research-deep.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research: $ARGUMENTS

Last updated: 2026-03-05 15:19 CET

Launch the Gemini Deep Research Agent for autonomous web-grounded research ($2-5/task, 10-20 min).

For free, instant offline research, use /gr:research instead.

Phase 0: Load Context

Before interviewing, gather intelligence:

  1. Prior research: Call knowledge_search(query="$ARGUMENTS", limit=5) to find existing findings in Weaviate
  2. Check memory: Read files under <memory-dir>/gr/research/ for previous analyses on related topics

Present to the user:

  • "I found X prior analyses related to this topic: [summaries]"
  • "Here's what we already know: [key findings]"
  • "Let me interview you to build a precise research brief."

If no prior context found, proceed directly to the interview.

Phase 1: Research Brief Interview

This is a CHALLENGE-DRIVEN interview. The quality of the brief determines the quality of $2-5 worth of research.

Interview Protocol (3-5 rounds via AskUserQuestion)

Round 1 -- Question Sharpening Restate topic as a precise question. Challenge HARD:

  • "This is too broad -- which specific aspect matters for your decision?"
  • "What would the ACTIONABLE output look like? A decision memo? Competitive landscape?"
  • "What's the actual decision this research needs to inform?"

Round 2 -- Scope Boundaries

  • Time period (recent vs historical vs both)
  • Domains (academic, industry, regulatory, all)
  • Geographic scope if relevant
  • What to EXCLUDE (common knowledge, things user already knows)
  • Budget confirmation ($2-5 per run)

Round 3 -- Hypotheses & Surprises

  • "What's your current hypothesis? I'll make sure the research tests it"
  • "What finding would CHANGE your mind?"
  • "What finding would be useless to you?"

Round 4 (if needed) -- Format & Audience

  • Who reads this? (affects tone, depth, structure)
  • Required sections? (executive summary, data tables, risk assessment)
  • Compare-and-contrast structure vs narrative vs bullet points?

Compile Brief

Read the full file on GitHub · 142 lines

Changes

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.

  1. 10d ago First seen · 142 lines · 9 tokens per session scan A 5dfc17404af9

Subscribe to this mod's changes

research-deep is a command published in the GitHub repository Galbaz1/video-research-mcp (23 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 1,215 once invoked, about $0.0000 per session on Opus 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 2026-08-30.