deep-research
Multi-agent deep research pipelines for Claude Code. Runs internet research, repository analysis, schema-driven structured research, and med
Open source Repository Open in the app JSON README (API)
About
Multi-agent deep research pipelines for Claude Code. Runs internet research, repository analysis, schema-driven structured research, and media research (via NotebookLM) using coordinated Agent Teams --- Haiku scouts build source corpora, Sonnet specialists verify and cross-challenge findings, and an Opus synthesizer produces the final output. Drop-in plugin, no code dependencies.
Details
- Kind
- Plugins
- Topic
- AI, RAG & memory
- Publisher
- oduffy-delphi
- Origin
- marketplace
- Category
- ferramentas
- Last push
- 2026-05-24T23:05:42Z
- Repository state
- ativo
- Language
- JavaScript
- License
- MIT
- Added
- 2026-08-30 01:48:58
- Updated
- 2026-08-30 01:48:58
- Origin id
oduffy-delphi/deep-research-claude/deep-research
README
# PoC -- John Stawinski # deep-research Multi-agent research pipelines for Claude Code — stop leaving your session to go research elsewhere. ## Who This Is For You're mid-session, you need real research, and you don't want to break flow to Perplexity or ChatGPT and paste results back. Or you want to deeply understand an open-source repo before building on it. Or you need structured data on 20 competitors in a consistent schema. These pipelines delegate research to agent teams so your top-level Claude stays free. Results come back as committed markdown in `docs/research/` — artifacts, not chat messages. ## Install This is a Claude Code plugin. The first-class install path is to hand the job to your agent — paste the prompt below into a Claude Code session and let it follow the playbook in [`docs/install.md`](docs/install.md). > Please install the deep-research-claude plugin from https://github.com/dbc-oduffy/deep-research-claude. The repo's `docs/install.md` is the install playbook — read it and follow the steps. Verify by running `/deep-research setup` at the end and report the result. After the agent finishes, restart Claude Code (so the Agent Teams env var takes effect) and try: ``` /deep-research web "agent orchestration patterns in LLM frameworks" ``` ## Pipelines ### Pipeline A — Internet Research Haiku scout builds a source corpus via web search. 3-5 Sonnet specialists deep-read sources, verify claims, and challenge each other adversarially. Opus sweep agent checks coverage, fills gaps, and writes the final document. An optional iterative deepening pass targets high-severity gaps identified in the first sweep. ``` /deep-research web "topic" ``` ### Pipeline B — Repository Research 2 Haiku scouts inventory every file in assigned chunks. 4 Sonnet specialists deep-read, analyze architecture, and optionally compare against a second project. Opus synthesizer writes the final assessment. ``` /deep-research repo /path/to/repo [--compare /path/to/mine] [--deeper] [--deepest] ``` - `--compare` — gap-analysis artifact comparing target repo to your project - `--deeper` — dependency-weighted repomap during scoping; specialists prioritize structurally central files - `--deepest` — adds a Sonnet atlas agent producing architecture artifacts (file index, system map, connectivity matrix) ### Pipeline C — Structured Research Schema-conforming batch research across N entities. Haiku scout maps findings to schema fields. 1-5 Sonnet verifiers challenge each other's values (CONFIRMED / UPDATED / REFUTED / CONTESTED). Opus synthesizer resolves contested fields and outputs validated YAML/JSON. ``` /deep-research structured tasks/research/spec.yaml subject-key ``` ### Pipeline D — NotebookLM Research Research YouTube videos, podcasts, and media Claude can't access directly, via NotebookLM. Haiku scout ingests sources. Sonnet workers query on focused sub-questions. Opus sweep writes the synthesis. Requires the [notebooklm-mcp-cli](https://github.com/jacob-bd/notebooklm-mcp-cli) MCP server and a Google account with NotebookLM access. ``` /notebooklm-research "topic" ``` ## Commands | Command | Pipeline | |---------|----------| | `/deep-research web <topic>` | Internet research with iterative deepening | | `/deep-research repo <path>` | Repository analysis (with optional `--compare`, `--deeper`, `--deepest`) | | `/deep-research structured <spec> <key>` | Schema-conforming batch research | | `/notebooklm-research <topic>` | NotebookLM media research | All pipelines are fire-and-forget — the EM spawns the team and is freed. Results are committed to `docs/research/` automatically. ## Agents | Agent | Model | Role | |-------|-------|------| | **research-scout** | Haiku | Web search, source vetting, shared corpus | | **research-specialist** | Sonnet | Source verification, adversarial peer challenges, structured claims | | **research-synthesizer** | Opus | Coverage check, gap-filling, final document | | **repo-scout** | Haiku | File inventory with signatures, constants, data flow | | **repo-specialist** | Sonnet | Architecture analysis, optional project comparison | | **structured-synthesizer** | Opus | Schema validation, contested field resolution, final YAML/JSON | ## Integration with coordinator This plugin works standalone. When used alongside the [coordinator plugin](https://github.com/dbc-oduffy/coordinator-claude), the EM automatically suggests research pipelines via a `PreToolUse` hook when Claude reaches for ad-hoc web search — nudging toward these structured pipelines instead of one-off `WebFetch` calls that consume the coordinator's context window. ### Optional dependency: `coordinator-safe-commit` Pipeline commands (`/web`, `/repo`, `/structured`) invoke `~/.claude/plugins/coordinator-claude/coordinator/bin/coordinator-safe-commit` for phase-end commits. The helper provides scoped staging (per-session audit-trail integrity) for users running multiple concurrent agent sessions on the same branch. **If you have the coordinator plugin installed,** no action needed — the helper is on the expected path. **If running deep-research standalone,** substitute either form when you encounter the command: - `git add <explicit-paths> && git commit -m "<subject>"` — manual scoped staging - `git add -A && git commit -m "<subject>"` — blanket staging (acceptable for solo single-session use) ## Research Backing Pipeline design derives from published guidance (OpenAI, Perplexity, Google, Anthropic, Stanford STORM) and is validated through [controlled experiments](docs/research/2026-03-31-deep-research-pipeline-evidence.md). Anthropic independently built a [production multi-agent research system](https://www.anthropic.com/engineering/multi-agent-research-system) using the same core pattern — their eval showed 90.2% improvement over single-agent. We converged on the same architecture independently; this system extends it with Haiku scouts for cost efficiency, adversarial peer dynamics between specialists, and asynchronous orchestrator dispatch. ## Source of Truth This is the canonical home of the deep-research plugin. Originally developed as part of [coordinator-claude](https://github.com/dbc-oduffy/coordinator-claude) and extracted for independent distribution. ## Acknowledgements Pipeline D is built on [notebooklm-mcp-cli](https://github.com/jacob-bd/notebooklm-mcp-cli) by [jacob-bd](https://github.com/jacob-bd) — an MCP server that provides programmatic access to Google NotebookLM. --- [Dónal O'Duffy](https://github.com/dbc-oduffy) & Claude