deep-research

A method for organising research that uses several sources and needs fact checking. It breaks a broad question into smaller investigations, checks important claims and combines the results into a cited report.

In plain words
What is it for?
Use it for literature reviews, industry or competitor research, technology comparisons and other reports that require multiple sources, verification and citations.
Why use it?
It reduces scattered research, unsupported claims and missed contradictions. It also makes the evidence and gaps behind a conclusion easier to trace.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/xerrors/yuxi/deep-research
Any agent
npx skills add xerrors/Yuxi --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/xerrors/Yuxi

Made for: Claude Code, Codex.

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,060 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00069 $0.01060
Opus 5 $0.00034 $0.00530
Sonnet 5 $0.00014 $0.00212
Haiku 4.5 $0.00007 $0.00106

Measured yesterday against content hash 72842a1054e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deep-research 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 yesterday.

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.

backend/package/yuxi/agents/skills/buildin/deep-research/SKILL.md · 51 lines

What it actually says

深度研究技能

当任务目标是产出多来源、可追溯、经过核验的深度研究结论(科研综述、行业/竞品调研、技术选型、专题分析等)时,使用此技能组织整个研究过程。本技能的核心是编排:你负责整体把控与子智能体调度,把繁重的检索与核验工作派发出去,自己专注规划与综合。

可用子智能体

通过 task 工具调度(可并行多开,互不依赖的子任务同时派发):

  • research-explorer(调研探索员):围绕一个明确子问题做多轮网页/知识库检索,返回按要点组织、带 <cite> 引用的结构化发现。这是主力,按子问题并行多开。
  • fact-verifier(事实核查员):对给定的关键论断做对抗式核验,逐条给出 支持 / 存疑 / 反驳 + 依据来源 + 置信度,并标注冲突。

编排流程

1. 澄清范围

问题不明确时,先用 ask_user_question 补充 2-3 个关键问题(研究目标、受众、范围边界、地域/时效、输出语言与形式),对齐验收标准后再开工。已经清晰的任务不要反复追问。

2. 规划拆解

write_todos 把研究目标拆成可独立调研的子问题,每个子问题写明产出标准(要回答什么、需要哪类证据)。子问题应正交、覆盖完整,避免重叠或遗漏关键角度。

3. 并行派发调研

  • 把互不依赖的子问题用多个 task 调用并行派发给 research-explorer
  • 每次派发在 description 中写清:子问题目标、已知上下文、期望输出格式(要点 + <cite source="$URL" type="url">$INDEX</cite> 引用 + 参考来源列表)。
  • 何时派发 vs 自己直检:子问题复杂、需多轮检索、可隔离上下文、可并行时一律派发子智能体;仅在澄清范围、补一两个零散事实、或快速校正方向时才自己少量直接检索。
  • 子问题之间有依赖时,先派发前置子问题,拿到结果后再派发后续。

4. 核验关键结论

影响最终结论的关键论断、数字、以及子智能体之间相互冲突的发现,派发 fact-verifier 做对抗式核验。要求其默认倾向「证据不足即标注存疑」。核验未通过的结论不要写进正文,或必须明确降级标注。

5. 综合成稿

证据充分后,由你统一综合为结构化报告,不要简单拼接子智能体返回的原文。组织顺序:问题定义 → 证据整理 → 分析比较 → 结论与建议 → 来源。围绕「论证」而非「资料堆砌」,每个结论都要有证据支撑。

6. 停止准则

信息饱和、或确认无法获取更多有效信息即停。明确标注证据缺口与不确定性,不臆断、不编造来源。

引用规范

  • 报告中关键结论、数据、观点必须绑定来源。
  • 沿用 <cite source="$URL" type="url">$INDEX</cite> 标注,$INDEX 从 1 起递增,引用紧跟结论后、不单独成行。
  • 文末单列「来源」章节,逐条列出标题与 URL;引用用户附件/知识库时标明文件名或路径。

输出约束

  • 最终交付的是一份可直接使用的报告,而不是「我打算怎么研究」。
  • 不要外泄中间推理过程、原始检索日志,也不要把待办清单原样输出成正文。
  • 报告语言与用户提问语言一致,使用正式、克制、可复核的书面表达。
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. yesterday First seen · 51 lines · 69 tokens per session scan A 72842a1054e0

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository xerrors/Yuxi (6,591 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 1,060 once invoked, about $0.0003 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.

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