deep-research

deep-research is a skill for Codex from Zhangs-11/zs-skills. It costs 147 tokens per session (1,399 once invoked), scanned A, original, MIT.

A structured research method for helping readers understand how a subject developed, how it compares with alternatives, and what may happen next. It emphasizes traceable evidence and clearly separates facts from conclusions.

In plain words
What is it for?
Use it for quick overviews, standard research, or deeper reports involving history, comparisons, current constraints, future possibilities, and source checking.
Why use it?
It prevents research from becoming an unstructured pile of information and makes important claims easier to check.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it for quick overviews, standard research, or deeper reports involving history, comparisons, current constraints, future possibilities, and source checking.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zhangs-11/zs-skills/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 Zhangs-11/zs-skills --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/Zhangs-11/zs-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 deep-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhangs-11/zs-skills/deep-research/github.svg)](https://agentmods.dev/skills/zhangs-11/zs-skills/deep-research)
Your own site
<a href="https://agentmods.dev/skills/zhangs-11/zs-skills/deep-research"><img src="https://agentmods.dev/badge/skills/zhangs-11/zs-skills/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 deep-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/zhangs-11/zs-skills/deep-research"><img src="https://agentmods.dev/badge/skills/zhangs-11/zs-skills/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 147 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,399 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.
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 $0.00147 $0.01399
Opus 5 $0.00073 $0.00700
Sonnet 5 $0.00029 $0.00280
Haiku 4.5 $0.00015 $0.00140

Measured 11d ago against content hash cdbed67f1388, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 11d ago.

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.

deep-research/SKILL.md · 75 lines

What it actually says

可追溯深度研究

目标不是堆满资料,而是让读者在有限时间内形成一个可检查的判断框架:研究对象为什么成为今天这样、它与真正可比对象差在哪里、这些历史能力和约束将怎样影响未来。

先固定研究问题

从用户真正要做的判断反推研究范围。明确研究对象、截止日期、读者、用途、时间跨度和需要比较的维度。能从上下文确定时直接开始;只有选择会实质改变研究对象或结论时,才一次询问一个关键变量。

按需要选择深度:

  • 快速框架:帮助陌生读者建立基本地图,保留核心结论、关键时间线、最小对比表和未知项。
  • 标准研究:完整走通纵向、横向、合并判断和事实核查。
  • 深入报告:用户明确要求长报告、重大决策或全面研究时,扩大来源、时间跨度、对照样本和反证覆盖;不以固定字数冒充深度。

建立证据底座

优先使用离主张最近的一手来源:官方文档、原始数据、源代码或规范、论文、财报、监管文件、正式公告和当事人完整访谈。二手资料适合发现线索与补充争议背景,不能替代它声称引用的一手来源。

为重要结论就近记录来源与日期。遇到来源冲突时并列呈现口径、时间和样本差异,不按数量投票;找不到足够证据时明确写“暂未核实”。研究对象、竞争格局、价格、人员、法规和产品状态可能变化时,以执行当天为截止时间重新核验。

纵向:解释它怎样走到今天

围绕会改变当前能力与约束的节点研究:

  1. 它在什么背景、需求和约束下出现,关键推动者是谁;
  2. 哪些成功、失败、产品转向、技术选择或外部变化构成真正转折;
  3. 哪些早期选择沉淀为今天的能力、路径依赖、组织惯性或包袱;
  4. 哪些常见历史叙事只是事后归因,缺少当时证据。

时间线只保留改变因果链的节点,不把所有发布日期排成流水账。

横向:用统一维度比较真实替代品

比较对象由用户或市场实际会在其中选择的替代方案决定,不只选名字相似者。先说明为什么选择这些对象,再用同一组维度比较目标用户、核心机制、能力边界、成本、分发或采用路径、主要优势与短板。

继续追问两件事:用户、客户或市场为什么选择它;又在什么条件下放弃它。市场份额、融资、声量或单项跑分不能单独代表产品质量或长期胜负。

合并两条轴

把历史形成的能力、路径依赖和现实约束映射到当前竞争差异,再推导未来。除非用户明确要求更多,最多给出三条真正不同的可能路径,并为每条写清:成立前提、最早可观察信号、主要反证和失效条件。相近趋势合并到同一路径下,不用增加条目制造全面感。

未来部分属于推断,不得写成已经发生的事实。若不同路径取决于用户的价值排序,说明实际取舍;若取决于尚未取得但可观察的数据,给出最短验证路径。

逐条核查关键主张

将会影响结论的说法拆成三类:

  • 事实:可由外部证据核验,例如日期、数字、功能、事件和公开表态;
  • 推断:从事实推出的原因、影响、趋势或未来判断;
  • 价值判断:取决于谁的目标、成本与偏好,例如“更好”“值得”“应该”。

只给事实使用证据等级:已证实基本成立但需要收窄存在争议证据不足明显错误。事实成立后仍要单独检查推断是否混淆相关性与因果、遗漏其他解释或越过适用范围。价值判断说明它服务谁、牺牲什么以及什么目标改变时结论会反转。

输出

按研究深度裁剪,默认顺序是:

  1. 核心结论;
  2. 关键时间线;
  3. 横向对比表;
  4. 纵横合并后的详细分析;
  5. 未来路径、前提与预警信号;
  6. 关键事实核查与仍待确认的问题。

先给结论,再给能支撑结论的证据。事实、推断和观点在语言上可区分;引用靠近对应主张。用户没有要求文件时直接在当前对话交付;要求沉淀、交接或仓库研究记录时,再写入符合目标项目惯例的 Markdown 文件。

完成标准

完成前确认:研究问题和截止时间明确;关键结论可追溯到足够新的事实源;纵向节点解释了当前能力或约束;横向对象是真实替代品且维度统一;主要反证和冲突信息没有被隐藏;事实、推断和价值判断没有混写;未来路径不超过用户要求的数量并带有前提、信号与失效条件;篇幅由问题需要决定而非固定字数。

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 75 lines · 147 tokens per session scan A cdbed67f1388

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository Zhangs-11/zs-skills (2 stars, last pushed 4d ago), licensed MIT. It adds 147 tokens to every session and 1,399 once invoked, about $0.0007 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 2026-08-31.

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