Webthinker Deep ResearchSAFE
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
Overview
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
5ff3ca429e5bOBSERVED · 2026-10-08Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| codex | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: webthinker-deep-research
description: "Deep web research for VCO: multi-hop search+browse+extract with an auditable action trace and a structured report (WebThinker-style)."
---
# 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):
1. Scaffold outputs:
- `python C:\Users\羽裳\.codex\skills\webthinker-deep-research\scripts\init_webthinker_run.py --topic "..." --out outputs/webthinker`
2. Search (broad → narrow):
- Use `web.run` search queries or `mcp__tavily__tavily_search` if available.
3. Browse/extract:
- Use `web.run open/click/find` for structured pages
- Use `playwright` when pages require dynamic rendering / interactions
4. Draft + iterate:
- Update `notes.md` and `sources.json` continuously
- Write `report.md` as you go (think-search-and-draft), not only at the end
5. Verification:
- Triangulate key claims across ≥2 sources when possible
- Flag uncertainties explicitly
### Mode B (Optional): Full WebThinker stack
Only choose this if you want to run the upstream system end-to-end and you have the environment:
- Requires heavy deps (`torch`, `transformers`, `vllm`) + a served reasoning model
- Requires a search API (Serper recommended by upstream)
- Optional: Crawl4AI parser client for JS-heavy pages
This mode is for **high-throughput** deep research runs; for most VCO tasks, Lite mode is enough and cheaper.
## Action trace format (trace.jsonl)
Each line is one JSON object, e.g.:
- `{"ts":"...","type":"search","query":"...","provider":"web.run"}`
- `{"ts":"...","type":"open","url":"..."}`
- `{"ts":"...","type":"extract","url":"...","highlights":["...","..."]}`
- `{"ts":"...","type":"decision","reason":"why this source matters","next":"..."}`
## Quality gates
- Every major claim in `report.md` links back to at least one entry in `sources.json`.
- `sources.json` contains the exact URLs you used (no “I saw somewhere...”).
- Keep the report actionable: add “Next steps” with concrete verification tasks.Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
5ff3ca429e5bfull audit observations/trust-audit/skill/foryourhealth111-pixel__webthinker-deep-research.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-08 | 5ff3ca429e5b | SAFE | B | 89 | first audit |
Questions
What does the Webthinker Deep Research skill do?
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
Is Webthinker Deep Research safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Webthinker Deep Research access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
What do I need installed to use Webthinker Deep Research?
Its own instructions reference torch, transformers and vllm. Dependencies are pinned to exact versions.
Which assistants does Webthinker Deep Research work with?
Its documentation mentions codex. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (5ff3ca429e5b), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.