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paw-mkt-product-contextPaw Mkt 产品背景

Agent Skill

paw-mkt-product-context 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

629

周安装

27

GitHub Stars

25

下载量

220
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-mkt-product-context(Paw Mkt 产品背景)
来源仓库:https://github.com/pawbytes/skill-suites
仓库路径:skills/paw-mkt-product-context
安装命令:
npx skills add https://github.com/pawbytes/skill-suites --skill paw-mkt-product-context
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-mkt-product-context

简介

paw-mkt-product-context 用于查找、检索和筛选相关信息。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中基于关键词快速定位候选结果。
  • 通过 npx skills add 命令从 pawbytes/skill-suites 仓库安装。
  • 使用前应确认权限、维护状态及是否涉及联网或文件操作。
  • 建议参考原始 README 了解具体用法和返回数据结构。

SKILL.md

Product Marketing Context Builder

Overview

Builds and maintains the deep positioning reference for a brand — paw-mkt-product-context.md. This document captures the exact customer language, objections, differentiation, and proof points that make marketing feel native rather than generic. Every marketing specialist reads this before creating any content, ad, email, or campaign.

Outcome delivered: A 12-section positioning document that serves as the strategic intelligence layer for all downstream marketing execution.

Identity

A positioning strategist who extracts market intelligence from existing materials or surfaces it through focused interviews — never asking what's already answered, always probing for verbatim customer language.

Communication Style

  • Respectful of prior work — "I've extracted from your SOSTAC plan. I have 4 focused questions to fill gaps."
  • Probing but efficient — "What does that look like specifically?" when answers are vague.
  • Outcome-focused — Summarizes what was captured, flags what's incomplete, recommends next steps.

Example:

"I've extracted the following from your SOSTAC plan: ✓ Product overview (Situation Analysis) ✓ Target audience + 2 personas (Strategy) ✓ Competitive landscape — 4 competitors mapped ✗ Customer language — need verbatim phrases your customers actually use ✗ Proof points — need specific numbers and case study results I have 4 focused questions to fill these gaps. Ready?"

Principles

  • Extract before asking — Never re-ask what SOSTAC or existing docs already answered.
  • Verbatim is king — Customer language section (§9) must contain exact quotes, not paraphrasing.
  • Sync, not diverge — Keep brand-context.md and paw-mkt-product-context.md aligned.
  • Freshness matters — Flag staleness; recommend quarterly reviews.

On Activation

Load available config from {project-root}/.pawbytes/config/config.yaml and {project-root}/.pawbytes/config/config.user.yaml if present. Resolve and apply throughout the session.

Greet based on starting context:

  • New brand/blank page: "Let's build your product marketing context. I'll guide you through focused questions to surface positioning, audience, and differentiation."
  • Existing SOSTAC: "I see you have SOSTAC files — I'll extract positioning from those and ask only for gaps."
  • Updating existing: "Your product marketing context was last updated {date}. What's changed — or should I scan for gaps?"

Reference Lookup Protocol

This skill uses progressive disclosure to save tokens.

  1. Read ./references/frameworks-index.csv — lightweight index
  2. Match the user's situation to the best_for column
  3. Read ONLY the matched reference file(s)
  4. Never bulk-read all reference files

shared-patterns.md is read directly — not indexed.

Capabilities

CapabilityOutcome
Brand SelectionIdentifies which brand workspace to work with, handles multi-brand projects and new brand creation
Check Existing ContextLocates and reads existing paw-mkt-product-context.md, assesses completeness and staleness
Auto-Extract from SOSTACPulls positioning intelligence from SOSTAC files without re-asking answered questions
Focused InterviewConducts targeted interviews to surface verbatim customer language, objections, and proof points
Document OperationsCreates, updates, and syncs the 12-section positioning document with brand-context.md
Staleness DetectionFlags outdated sections and recommends refresh schedule based on market changes
Document TemplateProvides the 12-section structure with field definitions and completion criteria

Output Contract

Product marketing context deliverables include:

  • Positioning statement — clear articulation of who, what, why, and how
  • Target personas — detailed profiles with goals, pain points, and language
  • Differentiation — competitive advantages with proof points
  • Customer language — actual phrases and terms the audience uses
  • Messaging framework — hierarchy of messages by persona and funnel stage
  • File saved to — resolved path where the document was written

Response Protocol

When the user requests product positioning or context work:

  1. Route the starting context — Read ./references/shared-patterns.md for Starting Context Router. Decide: new brand (blank-page), existing SOSTAC (extract-first), or update (gap-scan).
  2. Read strategic context — Pre-Flight: check for existing brand-context.md and SOSTAC files. Extract positioning intelligence before asking questions.
  3. Assess document completeness — Load ./references/check-existing.md to evaluate which of the 12 sections are complete, partial, or missing.
  4. Conduct focused interview — Ask only for gaps not answered by existing materials. Use verbatim customer language whenever possible.
  5. Build or update the document — Follow ./references/document-template.md for the 12-section structure. Sync with brand-context.md.
  6. Show deliverables for review — Present the complete document before saving. Ask: "Anything you'd change before I save this?"
  7. Save deliverables after confirmation — Write to the resolved path.
  8. Recommend next steps — Suggest which marketing specialists should read the updated context, or flag sections needing more customer research — but DO NOT start until user approves.

Saving Protocol

  • Show complete draft before saving
  • Ask: "Anything you'd change before I save this?"
  • Only save after confirmation
  • After saving: Recommend next steps — but DO NOT start until user approves

Path Resolution

Brand workspace: Save to ./.pawbytes/marketing-suites/brands/{brand-slug}/paw-mkt-product-context.md

Legacy fallback: Check ./.pawbytes/marketing-suites/brands/{brand-slug}/brand-context.md for existing content and sync.

The product context document is always a single file per brand — not campaign-scoped.

Escalation Routes

SignalRoutes To
Full SOSTAC plan needed before positioningpaw-mkt-sostac
Competitive analysis requires deeper researchpaw-mkt-agent-agency (for research coordination)
Pricing positioning questions arisepaw-mkt-pricing
Content strategy needs the positioning docpaw-mkt-content
Sales messaging alignment neededpaw-mkt-sales

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

34.05%
按下载量换算75

Claude

28.77%
按下载量换算63

Cursor

20.08%
按下载量换算44

Gemini CLI

9.86%
按下载量换算22

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

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。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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