Token导航 LogoToken导航

Agent Skill · 研究检索

paw-cra-content-research(Paw cra 内容研究)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

paw-cra-content-research 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 55,679。

总安装 470周安装 19GitHub Stars 25下载 147核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:paw-cra-content-research(Paw cra 内容研究)
来源仓库:https://github.com/pawbytes/skill-suites
仓库路径:skills/paw-cra-content-research
安装命令:
npx skills add https://github.com/pawbytes/skill-suites --skill paw-cra-content-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/pawbytes/skill-suites --skill paw-cra-content-research

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

辅助文档、README 和 Markdown 内容的整理与改写。适合提炼结构、补齐章节、统一术语或检查链接。使用时应保留项目已有事实和路径,不写未确认的信息。涉及对外文案时需控制语气,避免过度营销或夸大能力。保持克制表达,确保内容真实可信。

paw-cra-content-research 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/paw-cra-content-research

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/pawbytes/skill-suites --skill paw-cra-content-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

paw-cra-content-research 怎么安装?

在终端执行 npx skills add https://github.com/pawbytes/skill-suites --skill paw-cra-content-research。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

paw-cra-content-research 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

paw-cra-content-research 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

paw-cra-content-research 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

paw-cra-content-research 用的人多吗?

公开数据是累计安装 470 次,近一周安装 19 次,下载 147 次,GitHub 25 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

paw-cra-content-research 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
paw-cra-content-research

Paw cra 内容研究 · 本页

47025操作浏览器未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Content Research Workflow

Overview

This workflow produces an actionable research bundle — competitor analysis, trend spotting, and content opportunity identification — that feeds directly into visual and video production. It is a service workflow invoked on-demand by any Aria Creative Suite agent (Strategist, Designer, Video Producer, or Aria herself) when research context is needed to inform creative decisions.

The output is not academic research. Every finding translates into a specific production recommendation: a design brief the Designer can act on, a video format the Video Producer can storyboard, a content angle with hook and platform guidance. If a finding does not lead to a "make this" recommendation, it is context, not output.

Args: Accepts --headless or -H for autonomous execution. Supports scoped research via --scope competitor, --scope trend, --scope content, or --scope all (default).

On Activation

Load available config from {project-root}/.pawbytes/config/config.yaml and {project-root}/.pawbytes/config/config.user.yaml (root level and cra section). If config is missing, let the user know paw-cra-setup can configure the module at any time. Resolve:

  • {user_name} (null) — address the user by name
  • {communication_language} (system) — use for all communications
  • {document_output_language} (system) — use for generated document content
  • {default_brand} (null) — default brand to research if none specified

Load shared agency memory from {project-root}/.pawbytes/creative-suites/index.md. If a brand context is active or specified, load {project-root}/.pawbytes/creative-suites/brands/{brand-name}/guidelines.md and any existing research in {project-root}/.pawbytes/creative-suites/brands/{brand-name}/research/.

If --headless, complete the full pipeline without interaction using the active brand and scope from args. If interactive, greet and confirm research parameters before proceeding.

Pipeline

1. Research Brief Intake

Parse the research request:

ParameterSourceFallback
BrandExplicit request or --brand arg{default_brand} or active brand from index.md
Scope--scope arg or explicit requestall (competitor + trend + content)
Focus areasExplicit questions or topicsDerive from brand guidelines (industry, audience, competitors)
Target platformsExplicit or from brand guidelinesInstagram, TikTok, YouTube, LinkedIn

If interactive: confirm parameters and ask if there are specific questions or competitors to prioritize. If headless: proceed with available context.

2. Brand Context Load

Load from {project-root}/.pawbytes/creative-suites/brands/{brand-name}/:

  • guidelines.md — brand identity, voice, visual style, industry, audience
  • research/ — any prior research reports (avoid redundant work, build on existing findings)

If no brand exists at the expected path, abort with a clear message suggesting brand onboarding through Aria.

3. Competitor Scan (scope: competitor or all)

Load ./references/competitor-scan.md for detailed research guidance.

Use Exa MCP tools to analyze 3-5 competitors across:

  • Content strategy and posting patterns
  • Visual style and design language
  • Video formats and production quality
  • Platform presence and engagement signals
  • Messaging and positioning

Production lens: For every competitor insight, note what it means for Designer and Video Producer. "Competitor X uses bold typography overlays on Reels" is more useful than "Competitor X has strong video presence."

4. Trend Analysis (scope: trend or all)

Load ./references/trend-analysis.md for detailed research guidance.

Search for trends relevant to the brand's industry and audience:

  • Trending content formats (carousel styles, video templates, interactive formats)
  • Visual and aesthetic trends (color palettes, typography, layout patterns)
  • Platform-specific trends (TikTok sounds, Instagram features, YouTube formats)
  • Topical trends and hashtag movements

Classify each trend: Fad (<3 months), Trend (6-18 months), Movement (2+ years), Declining (avoid).

5. Content Opportunity Identification (scope: content or all)

Cross-reference competitor gaps with trending topics to find exploitable angles:

  • What are competitors NOT doing that audiences want?
  • Which trends align with the brand's strengths but competitors have not adopted?
  • What content formats are under-served in this niche?
  • Where is engagement high but content quality low (opportunity to dominate)?

Produce an angle shortlist — 5-10 specific content angles, each with:

  • The angle (one sentence)
  • Why it works (gap + trend alignment)
  • Suggested format (carousel, reel, long-form video, etc.)
  • Target platform

6. Production Recommendations

This is the most critical output section. Translate every research finding into briefs that Designer and Video Producer can act on directly.

Load ./references/production-recommendations.md for recommendation templates.

For each recommended angle, produce:

Design briefs (for Designer):

  • Visual concept description
  • Reference style (e.g., "minimalist with bold type overlay," "before/after split")
  • Platform and dimensions
  • Suggested copy direction

Video briefs (for Video Producer):

  • Format and duration
  • Hook concept (first 3 seconds)
  • Scene structure outline
  • Audio/music direction
  • Subtitle style

Platform-specific notes:

  • Optimal posting context (time, hashtags, caption strategy)
  • Platform feature usage (Instagram collab, TikTok stitch, YouTube Shorts)

7. Report Generation

Produce research-report.md following the structure in ./references/report-template.md.

The report consolidates all findings into a scannable document with:

  • Executive summary (key findings in 3-5 bullets)
  • Competitor landscape
  • Trend landscape
  • Angle shortlist (the actionable core)
  • Production recommendations (the handoff to Designer/Video Producer)
  • Platform-specific playbooks
  • Sources with URLs

8. Save to Memory

Write the report to {project-root}/.pawbytes/creative-suites/brands/{brand-name}/research/research-report.md with frontmatter:

---
created: YYYY-MM-DDTHH:MM:SSZ
brand: {brand-name}
scope: {scope}
type: research
---

If scope-specific reports were generated, also save:

  • competitor-analysis.md (scope: competitor or all)
  • trend-analysis.md (scope: trend or all)
  • content-opportunities.md (scope: content or all)

Append to {project-root}/.pawbytes/creative-suites/daily/YYYY-MM-DD.md:

## [Strategist] HH:MM - Content Research Complete
- Brand: {brand-name}
- Scope: {scope}
- Key findings: {2-3 bullet summary}
- Angles identified: {count}
- Report: .pawbytes/creative-suites/brands/{brand-name}/research/research-report.md

9. Handoff

If interactive: present the angle shortlist and ask which angles to prioritize for production. Suggest routing to Designer or Video Producer with the relevant briefs.

If headless: report completion and file locations. The calling agent reads the report from memory.

Research Tools

Primary: Exa MCP

ToolUse
web_search_exaCompetitor discovery, trend scanning, industry analysis
crawling_exaDeep page content extraction from competitor sites
get_code_context_exaTechnical/platform documentation lookup

Fallback: Web Search

If Exa MCP is unavailable, use the Web Search tool for the same research queries.

Optional: Agent-Browser CLI

For social media content behind login gates (Instagram feeds, TikTok For You, LinkedIn). Only use if agent-browser is available and auth sessions exist at {project-root}/.pawbytes/creative-suites/.auth/.

Quality Standards

  • Every finding must cite a source URL
  • Every insight must connect to a production recommendation
  • Competitor analysis focuses on content strategy, not corporate profiles
  • Trend classification distinguishes fads from movements
  • The angle shortlist is the most important output — it must be specific and actionable
  • Production recommendations must be detailed enough for Designer/Video Producer to start work without further research

平台分布

Codex

34.5%
按下载量换算51

Claude

29.42%
按下载量换算43

Cursor

18.29%
按下载量换算27

Gemini CLI

9.53%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills