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research-synthesis研究综合

Agent Skill

research-synthesis 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

661

周安装

27

GitHub Stars

33

下载量

212
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:research-synthesis(研究综合)
来源仓库:https://github.com/assimovt/productskills
仓库路径:skills/research-synthesis
安装命令:
npx skills add https://github.com/assimovt/productskills --skill research-synthesis
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/assimovt/productskills --skill research-synthesis

简介

research-synthesis 将原始研究材料转化为原子级洞察,支撑决策而非编故事。

  • 适用于用户调研、竞品分析等定性资料整理场景。
  • 采用四层结构:原石(nuggets)、模式、缺口、行动项。
  • 每个 nugget 为一个独立观察,附带来源标签。
  • 避免 cherry-picking,保持证据完整性。

SKILL.md

Turn raw research into atomic insights that drive decisions. Good synthesis surfaces patterns, bad synthesis creates narrative fiction. The goal is structured evidence, not a compelling story that cherry-picks quotes.

Atomic Research Method

Break research into four levels, bottom-up:

1. Nuggets (Raw Evidence)

Individual observations from a single source. Each nugget is:

  • One observation per nugget (not a paragraph)
  • Tagged with source (participant ID, date, method)
  • Direct quotes preferred over your interpretation

Example: "[P3, Jan 12] 'I spend 30 minutes after every customer call just trying to remember what they said.'"

2. Patterns (Recurring Themes)

Group nuggets that point to the same phenomenon. A pattern requires evidence from 3+ independent sources.

Example: "5 of 7 PMs report spending 20-45 minutes on post-call documentation. All describe it as tedious and low-value."

3. Insights (Implications)

What the pattern means for the product. An insight connects a pattern to a product opportunity or risk.

Example: "Post-call documentation is a high-frequency pain point (daily for active PMs) with no satisfying solution. Current workarounds (voice memos, bullet lists) lose context and emotional nuance."

4. Recommendations (Actions)

Specific product actions justified by insights. Each recommendation traces back through the chain: recommendation ← insight ← pattern ← nuggets.

Evidence Strength

Rate every pattern and insight:

StrengthCriteria
Strong5+ sources, consistent behavior observed, corroborated by data
Moderate3-4 sources, mostly consistent, some data support
Emerging2 sources, needs more evidence before acting
WeakSingle source or contradictory evidence

NEVER make product recommendations based on Weak or Emerging evidence. Flag them for further research.

Synthesis Process

  1. Extract all nuggets from raw notes — one per line, tagged with source
  2. Affinity map: group nuggets by theme (not by interview)
  3. Name each group as a pattern with a count ("5/7 participants...")
  4. Derive insights from strong and moderate patterns only
  5. Write recommendations that trace back to specific insights
  6. Flag contradictions explicitly — don't smooth them over

Guidelines

  • CRITICAL: NEVER synthesize from fewer than 3 data points. Two people saying the same thing is a coincidence, not a pattern.
  • ALWAYS cite specific evidence. "Users struggle with X" is worthless. "5 of 7 participants spent 20+ minutes on X, with P2 calling it 'the worst part of my week'" is evidence.
  • ALWAYS weight actions over opinions. What people DO matters more than what they SAY.
  • NEVER cherry-pick quotes to support a narrative. Include contradictory evidence.
  • ALWAYS flag your confidence level. Distinguish "we know" from "we think."
  • NEVER present synthesis without the evidence chain. Anyone reading should be able to trace a recommendation back to raw nuggets.

*Built on the Atomic Research method (Daniel Pidcock) and Continuous Discovery Habits (Teresa Torres). Skills from productskills.*

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

32.58%
按下载量换算69

Claude

30.28%
按下载量换算64

Cursor

18.87%
按下载量换算40

Gemini CLI

9.72%
按下载量换算21

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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