Skill: draco-kzn/desk-research-skill (version 1.0.0)

--- name: desk-research description: Structured desk research workflow for market, company, policy, product, and competitor questions. Use when a user asks for secondary research, landscape scans, evidence-based summaries, source triangulation, or insight synthesis from public information. --- # Desk Research Execute this workflow for any desk-research request. ## 0) Load methodology checklist (first) Read `references/methodology.md`, `references/deep-writing-patterns.md`, and `references/quality-checklist.md` and apply all as guardrails. ## 1) Define the research brief Write 4 lines before searching: - Research question (1 sentence) - Scope (time, geography, industry) - Must-answer sub-questions (3-6 bullets) - Output format needed by user If the question is vague, propose assumptions explicitly and continue. ## 2) Build a source plan Collect evidence in this priority order: 1. Primary/official sources (government, regulator, company filings, product docs) 2. Reputable secondary analysis (major research firms, established media) 3. Community signals (forums/social) only as supporting evidence Require at least 2 independent sources for every key claim. ## 3) Gather evidence fast For each sub-question: - Find 3-8 candidate sources - Keep the highest-signal sources - Extract only claim + evidence + date + link Reject sources that are undated, anonymous, or purely opinionated unless the user asked for sentiment. ## 4) Score source reliability Tag each source: - A = official primary source - B = credible secondary source - C = weak/indicative source When claims conflict, prefer newer A/B sources and explicitly note uncertainty. ## 5) Synthesize insights Convert notes into: - Facts (well-supported) - Interpretations (reasoned but inferential) - Unknowns (gaps needing validation) Never present interpretation as fact. ## 5.5) Deepening loop (mandatory) Before final delivery, run at least 2 rounds of self-questioning: Round A — Coverage challenge - What did I miss by source type, time window, or geography? - Which category/conclusion is over-dependent on one source? - What contradicts my current conclusion? Round B — Decision challenge - If this conclusion is wrong, what evidence would prove it wrong? - Which part is descriptive but not decision-useful? - What next data pull would most change the recommendation? After each round, update findings and confidence. ## 6) Deliver in concise structure Use this exact section order: 1. Core Questions (2 questions) 2. One-sentence Verdict 3. Executive Summary (5-8 bullets) 4. Key Findings by sub-question (with metric anchors) 5. Evidence Table (claim | source | date | reliability) 6. Confidence tags (High/Medium/Low per major claim) 7. Risks / Uncertainty 8. What would falsify this conclusion 9. Next Verification Steps / Todo For output shape and compact template, use `references/output-template.md`. ## 7) Quality bar before sending Check all items: - Every major claim has source/date - No single-source critical claim - Time/geography scope matches user ask - Clear separation of fact vs interpretation - Actionable takeaway included - Each promising case uses the full 9-part deep case framework - Each promising case includes one final case-summary paragraph: what it does / who pays / business model / why pay - Each key section ends with decision implication (so-what) ## 8) Case-depth hard rule (for startup/case research) When the task is startup/use-case research, apply these hard requirements: - For each promising case, collect at least 3 website evidence snippets (feature/pricing/use-flow) - Add at least 1 metric anchor from trusted dataset (revenue/MRR/growth) - Include at least 1 risk point and 1 falsification condition - Do not submit if any case is only descriptive without judgment

path: references/deep-writing-patterns.md
content: # Deep Desk Research Writing Patterns（提炼版）

本文件基于高质量研究文档写法抽象而成，目标是把“资料整理”升级为“可用于决策与写文章的研究”。

## A. 问题定义层：先定“要回答什么”

1. 先写 2 个核心问题（不是10个零散问题）
2. 用一句话给出当前阶段结论（One-sentence Verdict）
3. 明确结论成立的前提条件（边界条件）

> 原则：先定问题，再找证据；不要边搜边改题。

---

## B. 结构层：观点树 + 证据树双层并行

### 1) 观点树（Hypothesis Tree）
建议拆成 4-6 个维度：
- 商业模式与盈利结构
- 产品独特性与复利机制
- 市场空间与渗透路径
- GTM 与交付效率
- 组织/治理与执行能力
- 主要风险与反证

### 2) 证据树（Evidence Tree）
每个维度至少给：
- 1条定量证据（增速/收入/留存/客单等）
- 1条机制证据（为什么会这样）
- 1条反证或不确定性

> 原则：观点必须有证据锚点，证据必须服务于观点。

---

## C. 案例层：统一深挖框架（用于横向对比）

每个重点案例必须按同一结构写：
1. Basic Profile（是什么、面向谁、收入表现）
2. What They Actually Sell（表层卖点 vs 实际卖点）
3. User Problem（用户原始痛点与付费触发点）
4. Product & UX（功能、路径、上手门槛、体验）
5. Business Model（定价、收费逻辑、扩张方式）
6. Why Promising（为什么比同类更值得写）
7. Moat & Risk（护城河、脆弱点、依赖）
8. Key Insight（对主问题的贡献）
9. Case Summary（一段话：做什么/用户是谁/商业模式/为什么付费）

> 原则：所有案例可横向比较，避免“每个案例写法都不一样”。

---

## D. 深化层：两轮强制自我拷问

### Round A（覆盖挑战）
- 我遗漏了哪些关键样本/来源？
- 哪个结论过度依赖单一来源？
- 有什么与结论冲突的证据？

### Round B（决策挑战）
- 如果结论错了，最可能错在哪？
- 哪个变量变化会推翻结论？
- 现在这版内容对“下一步行动”是否足够有用？

> 原则：先反驳自己，再交付给别人。

---

## E. 写作层：像分析师，不像搬运工

1. 结论先行，证据跟随
2. 少形容词，多变量、机制和边界条件
3. 区分：事实 / 推断 / 假设
4. 每节最后写“这对决策意味着什么”
5. 允许不确定性，但必须标出验证路径

---

## F. 常见错误清单（必须避免）

- 只罗列项目，不回答核心问题
- 只看收入，不看可复制性
- 只写亮点，不写风险
- 只写结论，不写证据来源
- 只讲框架，不做案例深挖
- 语言空泛，缺乏可执行含义


path: references/methodology.md
content: # Desk Research Methodology Notes

This file captures practical methodology used to improve research quality.

## Source-backed principles

1. **Secondary research first, then primary validation**
   - Start with existing evidence before running interviews/surveys.
   - Practical reference: GOV.UK service manual (user research guidance emphasizes finding existing research first).

2. **Define question and scope before collecting data**
   - Clarify audience, geography, time window, and decision use-case.
   - Practical reference: market research frameworks (e.g., IBM topic overviews stress objective-first process).

3. **Triangulation over single-source claims**
   - Require at least 2 independent sources for important claims.
   - If conflict exists, prioritize newer and more primary sources.

4. **Separate facts, interpretations, and unknowns**
   - Facts = directly evidenced.
   - Interpretation = reasoned inference.
   - Unknown = unresolved evidence gap.

5. **Document uncertainty explicitly**
   - List assumptions and confidence level.
   - Avoid absolute conclusions when evidence quality is mixed.

## Optional analysis lenses

Use only when relevant to the user question:
- Market structure: TAM/SAM/SOM, value chain, buyer segments
- Competition: direct vs substitute products, differentiation map
- Economics: pricing model, gross margin signals, CAC payback assumptions
- Risk: dependency risk, policy risk, concentration risk

## Suggested confidence tags

- **High**: primary/official + corroborated
- **Medium**: credible secondary + partial corroboration
- **Low**: sparse evidence or weak-source-only

## Useful public references to consult

- https://www.gov.uk/service-manual/user-research
- https://en.wikipedia.org/wiki/Desk_research
- https://www.ibm.com/think/topics/market-research


path: references/output-template.md
content: # Desk Research Output Template (Deep)

## Core Questions
1. 
2. 

## One-sentence Verdict

## Executive Summary
- 
- 
- 

## Key Findings
### Q1:
- Fact (with metric/time):
- Why it matters:
- Decision implication:

### Q2:
- Fact (with metric/time):
- Why it matters:
- Decision implication:

### Q3:
- Fact (with metric/time):
- Why it matters:
- Decision implication:

## Evidence Table
| Claim | Source | Date | Reliability (A/B/C) |
|---|---|---|---|
|  |  |  |  |

## Confidence
- Claim A: High / Medium / Low
- Claim B: High / Medium / Low

## Risks / Uncertainty
- 
- 

## What would falsify this conclusion
- 
- 

## Next Verification Steps / Todo
- 
- 


path: references/quality-checklist.md
content: # Desk Research Quality Checklist (Submission Gate)

Before final delivery, verify all boxes:

## 1) Problem-fit
- [ ] Research answers the 2 core questions clearly
- [ ] Scope is explicit (time, geography, sample boundary)
- [ ] No major section is off-topic

## 2) Evidence quality
- [ ] Each major claim has source + date
- [ ] No critical conclusion depends on one weak source
- [ ] Conflicting evidence is acknowledged and reconciled

## 3) Case depth
- [ ] Each promising case uses the full 9-part framework
- [ ] Each case has >=3 website evidence snippets
- [ ] Each case has metric anchors (MRR/revenue/etc.)
- [ ] Each case includes risk + falsification condition
- [ ] Each case has final summary paragraph (做什么/用户是谁/商业模式/为什么付费)

## 4) Decision usefulness
- [ ] Every major section ends with “so-what” implication
- [ ] Cross-category comparison leads to explicit prioritization
- [ ] Final takeaways can be pasted into an article conclusion

## 5) Writing quality
- [ ] Conclusion-first, evidence-following
- [ ] Facts vs interpretations clearly separated
- [ ] Language is concise and non-generic
- [ ] Uncertainty and next verification steps are explicit


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