By gprecious
Deep research engine for URLs (YouTube, arXiv, GitHub, blogs) or topic keywords. Produces structured markdown reports with full source attribution via parallel subagent fanout.
research-engine vs baseline mini-bench. Runs N topics × 2 modes × 2 trials, scores via LLM-as-judge, emits report.md with improvement opportunities.
research/<slug>/app/ 를 hetzner LXC 에 배포하고 G3 (prod e2e) 게이트 통과 확인
research/<slug>/README.md + spec/spec.md 를 claude.ai/design 으로 보내 핸드오프 번들 받기
Extract cross-session patterns from past /research sessions. Writes readonly insights to docs/dreams/<run-id>/, or wiki drafts with --target=wiki.
research-engine 어댑터 페르소나의 evolvable 영역을 mutate하거나, wiki schema 후보를 draft로 생성.
Watch-first YouTube analysis — download media once, always extract visual frames and a Whisper transcript, cross-check with captions. Emit findings with timecodes. Return JSON per adapter contract.
Analyze an arXiv paper — abstract, contributions, related work — and surface implementation repos. Return JSON per adapter contract.
Scrape a single blog / docs page, optionally follow connected posts, and return JSON per adapter contract.
Summarize HN / Reddit / Lobsters threads referenced in the session. Tier-2; captures crowd reaction and dissenting views.
Pull current library / framework / SDK documentation via the context7 MCP for libraries referenced in the research session.
Use when the user asks Codex to research a URL, paper, repo, video, blog, documentation page, or topic and produce a structured cited markdown report or follow up on a previous research session using the research-engine workflow.
Use when an agent needs background or prior findings on a topic that may already be researched — look it up in the LLM-Wiki (the Obsidian vault built by research-engine) instead of re-researching. Searches distilled concepts/entities and verbatim reports, returns a cited answer, never edits the vault. Triggers on "위키 찾아봐", "이전 리서치 있어?", "wiki lookup", "what do we already know about X", needing context already captured by /research.
Uses power tools
Uses Bash, Write, or Edit tools
Runs pre-commands
Contains inline bash commands via ! syntax
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Deep research via Claude Code slash commands or the Codex skill. Give it a URL or a topic — it returns a structured markdown report with citations.
From the published marketplace (recommended):
claude plugin marketplace add gprecious/gprecious-marketplace # one-time per machine
claude plugin install research-engine@gprecious-marketplace
Then restart Claude Code or run /plugins reload. Updates via claude plugin update research-engine@gprecious-marketplace once a new version is published.
This repository also contains a Codex-compatible plugin manifest and skill:
.codex-plugin/plugin.json
skills/research-engine/SKILL.md
Install it the same way you install local Codex plugins in your environment, pointing the plugin source at this repository. After the plugin is available, ask Codex for research directly, for example:
Use research-engine to research https://arxiv.org/abs/2402.10171 --yes
Use research-engine to research "MoE LLM routing improvements" --yes
Use research-engine to follow up on the latest session: "저자 한계만 더 정리해줘"
Clone this repo, then register it as a local marketplace:
git clone https://github.com/gprecious/research-engine
# Point a local marketplace at the repo
mkdir -p research-engine-mp/.claude-plugin
cat > research-engine-mp/.claude-plugin/marketplace.json <<JSON
{
"\$schema": "https://anthropic.com/claude-code/marketplace.schema.json",
"name": "research-engine-local", "version": "0.0.0",
"owner": { "name": "local-dev" },
"plugins": [{ "name": "research-engine", "source": "../research-engine", "category": "productivity" }]
}
JSON
claude plugin marketplace add ./research-engine-mp
claude plugin install research-engine@research-engine-local
Tip: once installed, replace the snapshot in ~/.claude/plugins/cache/research-engine-local/research-engine/<ver>/ with a symlink to your working copy so local edits reflect without a version bump.
/research https://youtu.be/xxxxx # analyze a YouTube video
/research https://arxiv.org/abs/2301.xxxx # analyze a paper
/research "MoE LLM trends in 2026" # topic research
/research https://... --yes # skip intent Q&A
/research https://... --fresh # bypass cache
/research-followup "저자 배경 더" # ask follow-up on latest session
/research-followup "..." --slug <name> # target specific session
/research-visualize <slug> # charts + Notion auto-push
/research-visualize <slug> --diagrams # + Mermaid diagrams (preset-themed when --preset set)
/research-visualize <slug> --slides # + Marp slide deck (.pptx/.pdf)
/research-visualize <slug> --slides --judge # + 4-axis rubric auto-refine <75 (2-pass cap)
/research-visualize <slug> --slides --preset dark-neon # force preset (chart + deck + diagram share it)
/research-visualize <slug> --slides --brand-image <url> # watermark chart background via QuickChart plugin
/research-visualize <slug> --no-sync-notion # skip Notion push
/research-visualize # use most recent session
/research-design <slug> # research → claude.ai/design → LXC 배포
/research-design <slug> --no-deploy # 로컬 산출물까지만
/research-design <slug> --login-headful # cloak skip, Tailscale m4 로 1회 로그인
/research-design <slug> --fresh # storageState 캐시 무시
Output lands in research/YYYY-MM-DD-<slug>/README.md. When Notion is configured, a consolidated report is also upserted as a row in a research-engine database under the configured parent page (one row per session, re-runs update in place).
Agents that cannot execute Claude Code slash commands should use skills/research-engine/SKILL.md as the entrypoint and treat the command files as the canonical pipeline reference:
commands/research.md defines the full classify → preview → intent → evidence → synthesize → persist workflow.commands/research-followup.md defines session follow-ups.lib/adapter_contract.md defines the normalized evidence JSON shape.lib/report_sections.md defines the required markdown report sections and citation rules.agents/*-adapter.md defines source-specific collection behavior.For a new research run, create research/YYYY-MM-DD-<slug>/README.md, sources.json, and intent.json. Use the same report structure as lib/report_sections.md; every factual claim in 핵심 포인트, 상세 분석, and 인용 / 원문 must cite a real source id such as [1].
For Codex specifically:
npx claudepluginhub gprecious/gprecious-marketplace --plugin research-engineSisyphus/Ultrawork 패턴 기반 병렬 에이전트 오케스트레이션. oh-my-opencode 영감.
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