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研究检索external-servicegithub未标认证来源可访问许可证需确认审计提醒

research研究

Agent Skill

research 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

380

周安装

16

GitHub Stars

141

下载量

133
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(研究)
来源仓库:https://github.com/romiluz13/cc10x
仓库路径:skills/research
安装命令:
npx skills add https://github.com/romiluz13/cc10x --skill research
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/romiluz13/cc10x --skill research

简介

research 用于查找、检索和筛选相关信息。

  • 适合在各类任务中快速定位技术资料或解决方案。
  • 安装命令:npx skills add https://github.com/romiluz13/cc10x --skill research
  • 适用于 Codex、Claude、Cursor、Gemini CLI,通过 GitHub 安装,建议确认网络访问权限。
  • 可能触发外部搜索或文件读取,使用前请检查仓库维护状态。

SKILL.md

Research Synthesis Guidance

Overview

This skill is loaded via SKILL_HINTS by cc10x:planner and cc10x:bug-investigator when the router passes research files in the prompt. It provides instructions for synthesizing web and GitHub research findings.

This skill does NOT execute research. Research execution is done by:

  • cc10x:web-researcher — prefers Bright Data, falls back to WebSearch/WebFetch
  • cc10x:github-researcher — prefers Octocode MCP, falls back to package/docs/GitHub web research

Synthesis Goal

After the router passes research file paths in your prompt, read the available files and produce a synthesis that:

  1. Answers the knowledge gap (the Reason field from your prompt)
  2. Identifies the top 2-3 actionable patterns
  3. Lists gotchas with solutions
  4. Provides specific references for debugging
  5. Reflects evidence quality honestly
  6. States the single finding that most changed the recommendation

What Makes Good Synthesis

Include:

  • Cross-source confirmation (when web + GitHub agree on a pattern, it's reliable)
  • Conflict resolution (when sources disagree, prefer GitHub real code over docs)
  • Confidence calibration from the router-provided ## Research Quality block
  • Gotchas the user probably hasn't considered
  • Specific code snippets only when they materially change the recommendation

Exclude:

  • Raw dump of all findings (summarize)
  • Obvious things the AI already knows
  • Findings not relevant to the specific Reason for research

Synthesis Format

## Evidence Quality
- Web: [high / medium / low / none]
- GitHub: [high / medium / low / none]
- Overall confidence: [high / medium / low]

## Web Findings
[3-5 bullets from web research. Focus on patterns and gotchas.]

## GitHub Findings
[3-5 bullets from GitHub. Focus on real implementation patterns.]

## Synthesis

**Knowledge Gap answered:** [One sentence: what we now know that we didn't before]

**Recommended approach:** [1-3 sentences: what to do]

**What changed the recommendation most:** [single sentence]

**Top patterns to apply:**
1. [Specific, actionable pattern]
2. [Specific, actionable pattern]

**Gotchas to avoid:**
- [Gotcha]: [Solution]

**References for debugging:**
- [URL or GitHub repo path]

Handling Partial Research

If web researcher returned [Web phase unavailable]:

  • Note it in the synthesis header: "Web research unavailable — GitHub only"
  • Do not fabricate web findings
  • Reduce confidence in synthesis accordingly

If GitHub researcher returned [GitHub phase unavailable]:

  • Note it in the synthesis header: "GitHub research unavailable — Web only"
  • Use web findings only for synthesis

If BOTH unavailable:

  • State clearly: "Research unavailable — all sources down. Proceeding with AI knowledge only."
  • Lower confidence and rely on repo-local evidence first.

Quality weighting:

  • high: multiple concrete sources or code-backed findings
  • medium: one strong source or partial cross-confirmation
  • low: indirect, sparse, or web-only/package-only signals
  • none: no usable external findings

Memory Output

Do not edit .claude/cc10x/*.md directly from this skill or from the host agent.

Instead, surface the most durable takeaway through the host agent's MEMORY_NOTES, for example:

  • one research-backed gotcha worth preserving
  • one reference path worth indexing
  • one confidence caveat if research quality was degraded

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

32.16%
按下载量换算43

Claude

29.85%
按下载量换算40

Cursor

20.02%
按下载量换算27

Gemini CLI

8.56%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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