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paw-cra-content-researchPaw cra 内容研究

Agent Skill

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。

总安装

470

周安装

19

GitHub Stars

25

下载量

147
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: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

简介

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。

SKILL.md

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

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

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

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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 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。

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