home / skills / cklxx / elephant.ai / research-briefing

research-briefing skill

safe

This skill quickly consolidates scattered research findings into a decision-ready briefing with knowns, uncertainties, and concrete next steps.

npx playbooks add skill cklxx/elephant.ai --skill research-briefing

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: research-briefing
description: 快速梳理调研问题、提炼事实与不确定性、给出后续实验/访谈/数据拉取建议的通用调研简报模板。
---

# 调研简报（问题→证据→结论/空白）

## When to use this skill
- 需要把分散的资料或搜索结果整理成可决策的简报。  
- 需要明确“已知事实、假设、不确定性、下一步验证计划”。

## 必备输入
- 目标与决策场景：要解决什么问题/做什么决定？  
- 具体问题列表：优先级、成功判准、时间约束。  
- 已有资料：链接、数据、专家访谈要点；可信度或偏差。  
- 输出受众：高层/技术/运营？期望篇幅与语言。

## 工作流
1. **聚焦问题**：重写 1–3 句问题陈述 + 成功标准；列出优先级。  
2. **梳理证据**：按问题归档来源（数据/文档/访谈），记录出处与时间；标记可信度或潜在偏差。  
3. **分析与判断**：  
   - 提炼关键发现（事实 + 解释 + 影响）。  
   - 区分“事实 vs. 假设 vs. 未证实风险”。  
   - 发现矛盾或缺口时，写出需要的额外数据/实验。  
4. **输出结构**：  
   - TL;DR（3–5 条结论或洞见，含影响与建议）  
   - 关键发现（按问题分组，带证据引用）  
   - 不确定性与风险（缺失数据、样本偏差、时间敏感信息）  
   - 下一步计划（要验证什么、怎么做、由谁、截止时间）  
   - 附录：来源列表、引文、数据口径说明。  
5. **质量检查**：引用可追溯；数字注明口径/时间；明确“我不知道”或“仍需验证”的部分。

## 输出格式示例
以 Markdown 段落和列表呈现；引用来源时用括号标注 `(来源/时间)`，若为假设则标记 `[假设]`；建议用表格列出“问题 / 关键发现 / 证据 / 风险 / 推荐行动”。

## 最终检查清单
- 每条结论都可对应到具体证据或注明是假设。  
- 已标注缺口与下一步验证方式。  
- 读者无需额外上下文即可理解背景、结论与推荐行动。

Overview

This skill creates concise research briefings that turn scattered information into decision-ready summaries. It focuses on clarifying the decision context, listing evidence, separating facts from assumptions, and proposing concrete next steps. The output is structured for quick consumption by different audiences (executive, technical, operations).

How this skill works

You provide the decision goal, prioritized questions, existing materials, and the intended audience. The skill rewrites focused problem statements, consolidates sources by question, tags credibility and biases, and extracts key findings. It then separates facts vs. assumptions, highlights uncertainties, and produces a TL;DR plus a prioritized validation plan with owners and deadlines.

When to use it

When you need a decision-ready summary from scattered research or search results
When you must distinguish knowns, assumptions, and risks before committing resources
When preparing syntheses for executives, product teams, or operations
When designing experiments, interviews, or data pulls to validate hypotheses
When documenting evidence for audits or cross-team handoffs

Best practices

Supply a clear decision context and success criteria up front
Provide source links, timestamps, and notes on source credibility or bias
Limit scope to 1–3 tightly focused questions for one briefing
Require each conclusion to cite supporting evidence or be labeled as an assumption
Include owners and deadlines for every recommended validation or action

Example use cases

Pre-product decision: summarize customer interviews, analytics, and docs to recommend go/no-go
Operational risk review: consolidate incident notes and data to identify root uncertainties and mitigation tests
Research sprint: convert literature and expert calls into prioritized experiments and data queries
Executive one-pager: translate detailed findings into 3–5 decisive takeaways with impact and ask
User study planning: list unanswered questions and propose interview scripts, metrics, and sample sizes

FAQ

What inputs are essential to produce a usable briefing?

A clear decision goal and success criteria, a prioritized list of 1–3 questions, and the available sources (links, notes, data) with credibility notes.

How does the skill handle missing or contradictory evidence?

It flags contradictions and gaps, classifies items as fact/assumption/uncertainty, and proposes targeted follow-up actions (experiments, interviews, data pulls) with owners and timelines.