← 返回 Skills 市场
draco-kzn

quick research for VC/Consulting/Strategy Intern

作者 draco-kzn · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
310
总下载
0
收藏
4
当前安装
1
版本数
在 OpenClaw 中安装
/install desk-research-skill
功能描述
Structured desk research workflow for market, company, policy, product, and competitor questions. Use when a user asks for secondary research, landscape scan...
使用说明 (SKILL.md)

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
安全使用建议
This skill appears coherent and safe in structure — it is a set of procedures for performing secondary research using public sources. Before installing, consider: (1) confirm you are comfortable with the agent performing web queries on your behalf (it will access and cite external public websites); (2) avoid using it to process or fetch private/credentialed resources since it has no declared access to those; and (3) if you need auditability, request the agent include full source links and dates (the skill already mandates this). If you want additional assurance, ask the publisher for a signed homepage or contact info.
功能分析
Type: OpenClaw Skill Name: desk-research-skill Version: 1.0.0 The desk-research-skill bundle is a well-structured set of instructions designed to guide an AI agent through a rigorous secondary research process. It emphasizes source triangulation, reliability scoring, and structured synthesis without any evidence of malicious intent, data exfiltration, or unauthorized system access. The instructions in SKILL.md and the supporting reference files (methodology.md, deep-writing-patterns.md) are entirely focused on improving research quality and decision-usefulness for the user.
能力评估
Purpose & Capability
Name/description (desk research for market/company/policy/product/competitor questions) matches the content of SKILL.md and supporting reference files. No unexpected binaries, env vars, or external services are required.
Instruction Scope
Runtime instructions are narrowly focused on searching public sources, extracting claims with dates/links, scoring source reliability, and synthesizing findings. The SKILL.md does not instruct reading local files, environment variables, or sending data to unknown endpoints beyond normal web research.
Install Mechanism
No install spec or code files that would write/execute code on disk. Instruction-only approach minimizes install risk.
Credentials
The skill requires no credentials, secrets, or config paths. The data it asks for (public sources, dates, links) is proportionate to the research task.
Persistence & Privilege
always is false and the skill has no mechanism to persist or modify other skills or system-wide settings. Autonomous invocation is allowed by default but is not combined with elevated privileges or secret access.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install desk-research-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /desk-research-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of desk-research-skill, providing a comprehensive structured workflow for secondary research tasks. - Implements a step-by-step methodology covering research scoping, source planning, evidence gathering, source reliability scoring, and insight synthesis. - Enforces quality controls, mandatory validation loops, and clear separation of fact, interpretation, and uncertainty. - Standardizes output in a concise 9-part template, with confidence tags and clear actionables. - Includes special rules for startup and use-case research, ensuring depth, triangulation, and actionable conclusions.
元数据
Slug desk-research-skill
版本 1.0.0
许可证 MIT-0
累计安装 4
当前安装数 4
历史版本数 1
常见问题

quick research for VC/Consulting/Strategy Intern 是什么?

Structured desk research workflow for market, company, policy, product, and competitor questions. Use when a user asks for secondary research, landscape scan... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 310 次。

如何安装 quick research for VC/Consulting/Strategy Intern?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install desk-research-skill」即可一键安装,无需额外配置。

quick research for VC/Consulting/Strategy Intern 是免费的吗?

是的,quick research for VC/Consulting/Strategy Intern 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

quick research for VC/Consulting/Strategy Intern 支持哪些平台?

quick research for VC/Consulting/Strategy Intern 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 quick research for VC/Consulting/Strategy Intern?

由 draco-kzn(@draco-kzn)开发并维护,当前版本 v1.0.0。

💬 留言讨论