research-doc

research-doc is a command for Claude Code from Galbaz1/video-research-mcp. It costs 10 tokens per session (1,074 once invoked), scanned A, original, MIT.

A command for researching one or more documents with source evidence and cross-checking. It can work with local files, folders and web URLs.

In plain words
What is it for?
Use it to extract findings, assess research methods, compare documents and review supporting evidence.
Why use it?
It organizes document analysis and helps separate stronger evidence from weaker claims while identifying agreements and contradictions.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; reads .claude/ paths.

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

Good fit Use it to extract findings, assess research methods, compare documents and review supporting evidence.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/commands/galbaz1/video-research-mcp/research-doc"><img src="https://agentmods.dev/badge/commands/galbaz1/video-research-mcp/research-doc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 10 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,074 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 $0.00010 $0.01074
Opus 5 $0.00005 $0.00537
Sonnet 5 $0.00002 $0.00215
Haiku 4.5 $0.00001 $0.00107

Measured 10d ago against content hash d7fefc996be0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

research-doc 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-doc.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Document Research: $ARGUMENTS

Run multi-phase evidence-tiered research grounded in source documents, with progressive memory saving.

Phase 1: Identify Documents

  1. Determine the input from "$ARGUMENTS":

    • If it's a single file path: use research_document with file_paths=["<path>"]
    • If it's multiple paths (comma or space separated): split and pass as file_paths list
    • If it's a directory: use Glob to find all PDFs/text files, then pass as file_paths
    • If it starts with http:// or https://: pass as urls list
    • If arguments include both local files and URLs: pass both file_paths and urls
  2. Determine scope from context:

    • Single document, quick question → scope="quick"
    • 1-2 documents, standard analysis → scope="moderate" (default)
    • 2+ documents, comparative analysis → scope="deep"
    • Comprehensive review with methodology critique → scope="comprehensive"
  3. Call research_document with:

    • instruction: Use $ARGUMENTS context or default to "Analyze these documents comprehensively — extract key findings, assess methodology, identify agreements and contradictions."
    • scope: As determined above
    • thinking_level: "high"

Phase 2: Present & Save Results

  1. Present findings organized by evidence tier:

    • CONFIRMED — Directly stated with data in the document
    • STRONG INDICATOR — Strongly implied by document evidence
    • INFERENCE — Reasonable conclusion from document context
    • SPECULATION — Extrapolation beyond what documents support
    • UNKNOWN — Documents do not address this
  2. For multi-document results, highlight:

    • Cross-references: Where documents agree or contradict
    • Evidence chains: How findings flow across documents
    • Methodology critique: Per-document reliability assessment
  3. Save results to memory: a. Find memory directory via Glob on ~/.claude/projects/*/memory/ b. Generate slug from instruction or first document name (lowercase, hyphens, max 50 chars) c. Use Write to save at <memory-dir>/gr/doc-research/<slug>/analysis.md:

Read the full file on GitHub · 123 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 · 123 lines · 10 tokens per session scan A d7fefc996be0

Subscribe to this mod's changes

research-doc is a command published in the GitHub repository Galbaz1/video-research-mcp (23 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 1,074 once invoked, about $0.0001 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.