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narrative-landscape叙事景观

Agent Skill

narrative-landscape 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

588

周安装

25

GitHub Stars

66

下载量

206
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:narrative-landscape(叙事景观)
来源仓库:https://github.com/indranilbanerjee/digital-marketing-pro
仓库路径:skills/narrative-landscape
安装命令:
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill narrative-landscape
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/indranilbanerjee/digital-marketing-pro --skill narrative-landscape

简介

叙事景观用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 它支持基于关键词、任务场景或来源线索进行信息筛选与匹配。
  • 可通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前建议确认权限范围和维护状态,注意是否会触发联网或文件操作。
  • narrative-landscape 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

/dm:narrative-landscape

Purpose

Map the competitive narrative landscape to identify positioning opportunities the brand can own. Analyze how each competitor positions itself across key market dimensions — price-value, innovation-reliability, specialist-generalist, premium-accessible, or custom dimensions relevant to the industry. Find crowded territories where multiple competitors cluster, unoccupied gaps where no brand has staked a claim, and recommend the highest-value positioning territory for the brand to claim based on customer desirability and brand credibility.

Input Required

The user must provide (or will be prompted for):

  • Competitors to map: List of competitor names to include in the landscape analysis — typically 4-8 direct competitors plus any adjacent or aspirational competitors. Each will be analyzed for positioning on every defined dimension
  • Narrative dimensions to analyze: The positioning axes to map competitors against — common dimensions include price-value (premium vs budget), innovation-reliability (cutting-edge vs proven), specialist-generalist (niche expert vs broad platform), premium-accessible (luxury vs mass market), or custom dimensions specific to the industry (e.g., self-serve vs white-glove, enterprise vs SMB, AI-native vs traditional). Recommend 3-5 dimensions for a comprehensive but readable landscape
  • Competitor messaging sources: Where to extract positioning signals for each competitor — company websites (homepage, about, pricing pages), advertising copy (search ads, social ads, display), social media profiles and content themes, press releases and media coverage, analyst reports or review site positioning. Specify URLs or indicate which sources to prioritize

Process

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Pay special attention to the brand's current positioning, value proposition, target audience, and competitive differentiation claims. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load brand voice and positioning guardrails. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/dm:brand-setup)?" — or proceed with defaults.
  2. Define narrative dimensions: Validate and refine the positioning dimensions for the market — confirm each dimension represents a genuine spectrum where competitors can differentiate, ensure dimensions are independent (not redundant), and add any industry-standard dimensions the user may have missed. Define the poles of each dimension with clear labels and examples.
  3. Analyze each competitor's positioning: For every competitor on every dimension, extract positioning signals from the specified messaging sources — homepage headlines and hero copy (what they lead with), pricing page framing (how they present value), ad copy themes (what they emphasize to acquire customers), social content patterns (how they present themselves day-to-day), and PR/media positioning (how they describe themselves to press). Score each competitor's position on each dimension as a value from -5 to +5 representing their placement between the two poles.
  4. Map positions via narrative-mapper.py: Execute narrative-mapper.py map-landscape with the competitor position data to generate the narrative landscape map — plotting all competitors on each dimension pair, calculating cluster density, and identifying open territories. The script produces structured positioning data with gap analysis.
  5. Identify clusters and gaps: Analyze the landscape map for crowded positions where 3+ competitors cluster on similar positioning (high competition, difficult to differentiate), contested positions where 2 competitors overlap (direct rivalry), and unoccupied gaps where no competitor has claimed territory (potential opportunities). Classify gaps by size, strategic value, and defensibility.
  6. Score each gap: Evaluate every identified gap by two factors — customer value (how much do target customers actually want a brand positioned here? Is there demand for this positioning?) and brand credibility (can this brand credibly claim this territory given its product, history, and capabilities?). Multiply these scores to produce an opportunity score for each gap. Rank gaps by opportunity score.
  7. Recommend optimal positioning territory: Select the highest-scoring gap as the recommended positioning territory. Justify the recommendation with evidence — why customers want it, why the brand can credibly own it, why competitors have left it open, and what risks exist (competitors may move to contest it).
  8. Generate positioning strategy: For the recommended territory, produce actionable positioning guidance — key messages, proof points to support the claim, content themes that reinforce the position, channels best suited to establish the positioning, and a timeline for claiming the territory through consistent messaging across all brand touchpoints.

Output

A comprehensive narrative landscape analysis containing:

  • Narrative landscape map: Competitor positions plotted on each dimension pair — showing where each competitor sits on every axis, with clear visualization of clusters, contested zones, and open territories
  • Cluster analysis: Identification of crowded positioning territories where multiple competitors overlap — which positions are contested, how intensely, and what it means for brands trying to differentiate in those areas
  • Gap analysis with opportunity scores: Every unoccupied or underserved positioning territory identified, scored by customer desirability multiplied by brand credibility, ranked from highest to lowest opportunity value
  • Recommended positioning territory: The single highest-value gap the brand should claim — with evidence-based justification covering customer demand, brand credibility, competitive dynamics, and defensibility against future competitor moves
  • Positioning strategy with messaging guidance: Key messages, proof points, supporting themes, and language patterns that establish the brand in the recommended territory — calibrated to brand voice from context
  • Content plan to claim the territory: Specific content types, channels, and cadence to systematically reinforce the positioning over 30, 60, and 90 days — homepage messaging updates, ad copy angles, social content themes, PR narratives, and thought leadership topics

Agents Used

  • competitor-intelligence — Competitive messaging extraction and analysis across websites, advertising, social media, and press coverage, positioning signal scoring on each narrative dimension, cluster and gap identification through landscape pattern analysis, and competitive response prediction for recommended positioning moves
  • marketing-strategist — Positioning strategy development from gap analysis to actionable territory selection, customer desirability and brand credibility scoring for each gap, messaging framework creation with key messages, proof points, and content themes, and territory-claiming content plan with 30/60/90-day milestones across channels

适合场景

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02

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03

需要对比不同来源的安装命令和来源信息时

能力概览

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能力 2

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能力 3

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能力 4

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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

38.3%
按下载量换算79

Claude

29.88%
按下载量换算62

Cursor

19.19%
按下载量换算40

Gemini CLI

9.05%
按下载量换算19

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可疑

Snyk

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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

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来源信息

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