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Webthinker Deep Research

Deep web research for VCO: multi-hop search+browse+extract with an auditable action trace and a structured report (WebThinker-style).

Data, AI & Research|v1|Updated 7/2/2026|GitHub source
MCP get_skill({ skillId: "webthinker-deep-research-2d0e583e" })

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# WebThinker Deep Research (VCO)

## When to use

Use this skill when the task requires **deep web research** (not just one-shot search), for example:

- Multi-hop questions (“find → open → follow links → verify”)
- “Deep research report” / “调研报告” / “竞品调研” / “技术调研”
- Need an **auditable trace** of web actions and sources
- Need to merge findings into a structured deliverable (report / brief / spec)

## Non-goals (avoid redundancy)

- For **quick citations** or “give me 3 sources”, prefer `research-lookup`.
- For **interactive UI flows** (login / forms / downloads), prefer `playwright` or `turix-cua` overlays.
- For **codebase structure / call chains**, prefer GitNexus overlays (not web research).

## Output contract (must)

Produce a folder with:

- `report.md` — structured report (problem → findings → implications → next steps)
- `sources.json` — all sources (URL/title/access time/snippet)
- `trace.jsonl` — append-only action trace (search/open/extract/decision)
- `notes.md` — working notes with per-source anchors

Use `scripts/init_webthinker_run.py` to scaffold the folder.

## Runtime (Upstream vendoring)

This VCO skill supports a **stable Lite mode** by default, and keeps the upstream WebThinker repo **vendored** for optional advanced use.

- Vendored upstream paths:
  - `C:\Users\羽裳\.codex\_external\ruc-nlpir\WebThinker\`
- Runtime config (no secrets stored):
  - `C:\Users\羽裳\.codex\skills\vibe\config\ruc-nlpir-runtime.json`
- Preflight / install (no secrets echoed):
  - `pwsh C:\Users\羽裳\.codex\skills\vibe\scripts\ruc-nlpir\preflight.ps1`
  - Manually create an isolated venv for the vendored runtime and install only the minimal packages you need. The old `install-upstreams.ps1` auto-install path has been removed on purpose.

LLM endpoint conventions (recommended):

- Base URL: `OPENAI_BASE_URL` (or runtime default)
- API key: `OPENAI_API_KEY` (**env var only; never write into files or CLI args**)

## Modes

### Mode A (Recommended): Lite — tool-orchestrated deep research

Use existing tools (no heavy model hosting):

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#broad-capability#creative#deep#researchplaywrightpythonweb-search