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Agent Skill · 研究检索

narrative-landscape(叙事景观)

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。

narrative-landscape 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,权限为只读;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 51,212。

总安装 588周安装 25GitHub Stars 66下载 206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: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

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。

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。

来源仓库内路径:skills/narrative-landscape

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/indranilbanerjee/digital-marketing-pro --skill…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

narrative-landscape 怎么安装?

在终端执行 npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill narrative…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

narrative-landscape 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。

narrative-landscape 需要什么权限?

权限级别是只读。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。

narrative-landscape 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。

narrative-landscape 用的人多吗?

公开数据是累计安装 588 次,近一周安装 25 次,下载 206 次,GitHub 66 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。

narrative-landscape 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
narrative-landscape

叙事景观 · 本页

58866只读未明确有提醒

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

/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

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

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

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。

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