3d-deep-research

3d-deep-research is a skill for Codex from jeffy-Peng/jeffy-skills. It costs 121 tokens per session (3,367 once invoked), scanned A, original, MIT.

A research workflow for investigating products, companies, technologies, people, markets, industries, and complex events. It produces a traceable report based on sources, evidence, and analysis of how events developed, what forces shaped them, and how the parts work.

In plain words
What is it for?
Use it for deep research, competitor or market studies, due diligence, history-and-cause analysis, evidence reviews, and formal Markdown reports, with optional HTML or PDF output.
Why use it?
It helps prevent reports from becoming unsupported summaries or opinions. It keeps important claims and numbers tied to sources and separates facts, explanations, predictions, and unresolved questions.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it for deep research, competitor or market studies, due diligence, history-and-cause analysis, evidence reviews, and formal Markdown reports, with optional HTML or PDF output.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jeffy-peng/jeffy-skills/3d-deep-research
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.

Any agent
npx skills add jeffy-Peng/jeffy-skills --skill 3d-deep-research
Clone the repo
git clone --depth 1 https://github.com/jeffy-Peng/jeffy-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for 3d-deep-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeffy-peng/jeffy-skills/3d-deep-research/github.svg)](https://agentmods.dev/skills/jeffy-peng/jeffy-skills/3d-deep-research)
Your own site
<a href="https://agentmods.dev/skills/jeffy-peng/jeffy-skills/3d-deep-research"><img src="https://agentmods.dev/badge/skills/jeffy-peng/jeffy-skills/3d-deep-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for 3d-deep-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/jeffy-peng/jeffy-skills/3d-deep-research"><img src="https://agentmods.dev/badge/skills/jeffy-peng/jeffy-skills/3d-deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,367 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00121 $0.03367
Opus 5.5 $0.00048 $0.01347
Sonnet 5.5 $0.00024 $0.00673
Haiku 4.5 $0.00012 $0.00337

Measured 8d ago against content hash 82b121c8be81, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

3d-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 8d ago.

The scan reads SKILL.md. This mod also ships 11 executable files (scripts/build_report.py, scripts/linkify_sources.py, scripts/preview_report.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

3d-deep-research/SKILL.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

3D Deep Research

先建立研究底图,确认研究对象的边界、运转方式和当前状态;再用 X/Y/Z 逐层解释:X 识别显性与非显性的关键变化及其后续影响,Y 沿具体变化切开并比较成因,Z 拆开尚不清楚的作用连接。分析结果持续返回发展路径和研究底图,用证据校正解释并检查重要遗漏。

本 Skill 为主研究流程时,默认交付完整的 Markdown、HTML 和 PDF 三份报告;用户明确缩小交付范围时按其要求减少。用户点名其他研究 Skill 或选择其他工作模式时,以其作为主流程;仅在需要本方法时辅助使用,不叠加独立默认产物。不要仅因通用的 deep research 字样同时运行两套流程,也不要把普通问答扩写成长报告。

资源读取

按当前阶段读取所需资源;同一任务中已完整读取且未变化的文件直接复用。输出被截断时只补读缺失部分,不反复装载全文。

  1. 读取 references/evidence-protocol.md,建立来源与 Claim 账本并执行事实审计。
  2. 读取 references/xyz-method.md,建立研究底图并执行 X/Y/Z、路径校正和覆盖复核。
  3. 根据研究对象读取 references/object-adapters.md 的对应部分。
  4. 分析时读取 references/visual-guidelines.md,规划有解释价值的图;论点稳定后制作和检查。
  5. 写作时复制 assets/report-template.md,保留元数据与证据附录,按核心问题组织正文。
  6. 首次构建或排错时读取 references/build-runtime.md。运行现有脚本,无需预读实现;仅在明确故障需要时定位相关代码。

报告措辞

以下规则适用于正文、标题和图注;证据附录以准确、可追溯为先。

  • 先直接回答研究问题,再解释依据、原因及其对用户问题的含义;用户未要求行动方案时,不自行扩成路线图。
  • 先具体,后抽象。 优先说清谁做了什么、发生什么变化,再解释背后的概念。能直接说明的,不用抽象名词代替。
  • 先判断,后解释。 一句话先说清主要意思,原因和必要限制随后展开,避免把多层意思挤进一句话。
  • 面向目标读者使用准确、克制的专业书面语。 保留必要概念,用具体对象、关系和口径解释;不用口语化比喻替代分析,也不用抽象术语增加专业感。
  • 每个核心论点说明目前支持什么判断、为什么重要、依据及作用过程是什么。每段推进一个判断;删除不增加事实、解释或决策价值的句子。
  • 明确区分事实、解释和预测。证据只能支持“可能”时,不写成“证明”或“必然”。
  • 不把 Claim 类型、证据门槛、X/Y/Z 等内部方法术语写进正文;它们只用于组织研究和附录说明。
  • 数字首次出现时说明时间、单位、统计口径和比较对象。
  • 不使用宣传式形容词、无依据的最高级,以及“值得注意的是”“不容忽视”等空洞过渡语。
  • 影响判断方向、适用范围或幅度的限制紧邻相关结论;共性研究限制放入 A3,不逐段重复。同一论证只完整展开一次。
  • 证据不足时,明确可支持的暂定判断和仍未解决的部分。不用反复强调“不能证明”“不等于”代替分析;证据无法区分因素重要性时不强排主次、不编造贡献比例。

表达示例(只示范论证方式,变量须按具体研究取舍):

只有提醒的表达 增加分析的表达
高售价不等于高利润 增量利润取决于售价差、增量制造与售后成本,以及对既有机型的替代。
看得更多,未必做得更好 大屏的使用收益取决于任务布局与输入成本。
兼容不等于适配好 应分别检查布局利用、状态连续性和关键操作完成情况。

执行流程

0. 明确研究设定

根据用户问题和上下文明确目标读者、需要作出的判断、研究对象及类型、时间基准、范围和交付要求。无法从上下文解决且会显著改变目标或正确性的问题才追问;其余情况直接开始。形成暂定问题结构,指出最可能改变判断的未知项,再根据对象适配器建立研究底图、检查遗漏;证据可以推翻暂定结构。

必须检查的维度不等于必须写入正文的章节。篇幅按对核心问题的解释价值分配,不按类别平均分配;重要性判断须有依据,无关侧面省略,证据不足但可能改变结论的侧面进入 A3。

Read the full file on GitHub · 142 lines

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. 8d ago Changed · +7 lines 82b121c8be81
  2. 1mo ago Changed · +4 lines 7e79bff3b504
  3. 1mo ago Changed · +9 lines 5c9a577b3f37
  4. 2mo ago Changed · +2 lines 21cf0304aeb2
  5. 2mo ago Changed · +6 lines c2faa769d31b
  6. 2mo ago First seen · 114 lines · 121 tokens per session scan A bbaa4f5ca823

Subscribe to this mod's changes

3d-deep-research is a skill published in the GitHub repository jeffy-Peng/jeffy-skills (21 stars, last pushed 8d ago), licensed MIT. It adds 121 tokens to every session and 3,367 once invoked, about $0.0005 per session on Opus 5.5. 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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3d-deep-research compared with skills from other repositories

3d-deep-research next to 6 skills from other repositories
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3d-deep-researchjeffy-Peng/jeffy-skillsSkill218d agoMITA121Codex
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mk:researchngocsangyem/MeowKitSkill156d agoMITA165Claude Code
idea-bib-reviewbahayonghang/my-ai-cli-toolkitSkill179d agoMITA126Claude Code, Codex
link-evidencekdcube/kdcubeSkill27yesterdayMITA25Claude Code
net-deep-researchh4444433333/net-deep-researchSkill722mo agoMIT-0A73Claude Code, Codex
ftdericrisco/rsc-harnessSkill5032d agoMITA128Claude Code, Codex