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Agent Skill · 研究检索

topical-authority-mapper(主题权威映射器)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

topical-authority-mapper 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,权限为需要联网;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 60,207。

总安装 372周安装 16GitHub Stars 607下载 131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:topical-authority-mapper(主题权威映射器)
来源仓库:https://github.com/athina-ai/goose-skills
仓库路径:skills/topical-authority-mapper
安装命令:
npx skills add https://github.com/athina-ai/goose-skills --skill topical-authority-mapper
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/athina-ai/goose-skills --skill topical-authority-mapper

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。

用于建立主题权威的内容架构映射关系。区分主干页面与子话题集群,指导内部链接策略设计。依据谷歌对深度覆盖的偏好优化内容组织逻辑。输出结构建议而非排名结论,需结合实际业务调整落地。topical-authority-mapper 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/topical-authority-mapper

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/athina-ai/goose-skills --skill topical-authori…;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

    它需要需要联网,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

topical-authority-mapper 怎么安装?

在终端执行 npx skills add https://github.com/athina-ai/goose-skills --skill topical-authority-mapper。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

topical-authority-mapper 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。

topical-authority-mapper 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

topical-authority-mapper 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。

topical-authority-mapper 用的人多吗?

公开数据是累计安装 372 次,近一周安装 16 次,下载 131 次,GitHub 607 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。

topical-authority-mapper 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
topical-authority-mapper

主题权威映射器 · 本页

372607需要联网未明确有提醒

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

Topical Authority Mapper

Most content strategies are just keyword lists turned into blog posts. Real topical authority requires a structured map: pillar pages that own broad topics, cluster pages that go deep on subtopics, and an internal linking architecture that tells Google "we comprehensively cover this subject." This skill builds that map.

Core principle: Google rewards topical depth, not random keyword coverage. A site with 15 interlinked articles that thoroughly cover "sales automation" will outrank a site with 50 unrelated blog posts that happen to mention the phrase. This skill builds the cluster architecture that creates genuine authority.

When to Use

  • "What content should we create to dominate [topic]?"
  • "Build a topic cluster strategy for our blog"
  • "Map out our topical authority for [category]"
  • "Create a content calendar based on topic clusters"
  • "What content gaps do we have?"

Tool Enhancement (Optional)

Topic cluster mapping is significantly better with keyword data that shows search volume, difficulty, and semantic relationships across hundreds of subtopic variations.

Agent Prompt to User

"I can build a comprehensive topical authority map using competitive analysis and content gap identification. For the most precise results — especially accurate volume data and keyword clustering at scale — I'd recommend connecting a keyword data API." Recommended: DataForSEO (pay-per-use, ~$0.01/keyword, no monthly minimum) - Sign up at dataforseo.com → get API login + password - Set DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD env vars Alternatives that also work: - Keywords Everywhere API ($1 per 10 credits = 100K keywords, very cheap) → set KEYWORDS_EVERYWHERE_API_KEY - SEMrush API (if you have a subscription) → set SEMRUSH_API_KEY - Ahrefs API (if you have a subscription) → set AHREFS_API_TOKEN "Want to use one of these, or should I proceed with baseline mode? Baseline uses our existing SEO tools and web research — still produces a strong topic map, but with less granular volume data per subtopic."

Mode Selection

  • Enhanced mode — Bulk keyword data via DataForSEO / Keywords Everywhere / SEMrush / Ahrefs. Gets search volume, difficulty, and semantic grouping for every subtopic. Enables data-driven prioritization and precise gap identification. Also supports keyword clustering APIs that automatically group related terms.
  • Baseline mode — Uses seo-domain-analyzer for domain metrics, web_search for topic research, reddit-post-finder for question mining, competitor analysis via site-content-catalog. Topic mapping and cluster architecture are equally strong. Volume estimates are directional rather than exact.

Phase 0: Intake

  1. Your site URL — For existing content audit
  2. Target topics — 1-5 broad topic areas you want authority in (e.g., "sales automation", "content marketing", "data privacy")
  3. Competitors — 2-5 competitor URLs who rank well for these topics
  4. ICP — Who reads your content? (role, pain, goal)
  5. Content capacity — How many articles can your team produce per month?
  6. Existing content — Do you have a blog? How many articles? (we'll audit it)
  7. Time horizon — 3-month plan? 6-month? 12-month?
  8. Tool preference — Enhanced mode with keyword API, or baseline? (see Tool Enhancement above)

Phase 1: Current State Audit

1A: Your Existing Content

Run site-content-catalog on your site:

python3 skills/site-content-catalog/scripts/catalog_content.py \
  --url "<your_site_url>" \
  --output json

Map all existing content:

  • Blog posts by topic
  • Resource pages, guides, glossary
  • Landing pages with content
  • Identify which topics you already have content for
  • Note: thin pages, outdated content, orphan pages (no internal links)

1B: Competitor Content Mapping

For each competitor, run site-content-catalog:

python3 skills/site-content-catalog/scripts/catalog_content.py \
  --url "<competitor_url>" \
  --output json

Map their content architecture:

  • How do they structure topic clusters?
  • Which topics have pillar pages?
  • How deep do their clusters go?
  • Internal linking patterns
  • Content freshness (update dates)

1C: Domain Authority Baseline

Run seo-domain-analyzer for your site and competitors:

  • Your domain authority vs. competitors
  • Keyword overlap analysis
  • Where competitors rank that you don't

Phase 2: Topic Universe Expansion

2A: Subtopic Discovery

For each target topic area, generate the full subtopic universe:

Enhanced mode (DataForSEO / Keywords Everywhere):

# DataForSEO keyword suggestions
POST /v3/dataforseo_labs/google/keyword_suggestions/live
{
  "keyword": "<topic>",
  "limit": 500
}

# DataForSEO related keywords
POST /v3/dataforseo_labs/google/related_keywords/live
{
  "keyword": "<topic>",
  "limit": 500
}

Extract:

  • All related keywords and questions
  • Search volumes per keyword
  • Keyword difficulty scores
  • Semantic groups (auto-clustered by meaning)

Baseline mode:

Use multiple sources to build the subtopic list:

  • web_search for "topic + [what/how/why/best/vs/guide/examples]"
  • reddit-post-finder for questions people ask about the topic
  • Google autocomplete patterns (via web search)
  • Competitor content titles (from Phase 1B)
  • PAA questions from search results

2B: Question Mining

Run reddit-post-finder for each topic area:

python3 skills/reddit-post-finder/scripts/search_reddit.py \
  --subreddit "<relevant_subs>" \
  --keywords "<topic>" \
  --days 365 --sort top --time year

Extract:

  • Questions people ask (→ individual article topics)
  • Recurring themes (→ cluster pillars)
  • Misconceptions (→ myth-busting content)
  • Comparisons people make (→ vs/ content)
  • Use cases discussed (→ use-case content)

2C: Keyword Clustering

Group all discovered keywords/subtopics into semantic clusters:

Enhanced mode: Use DataForSEO keyword clustering API or group by SERP overlap (keywords that share 3+ ranking URLs likely belong to the same cluster).

Baseline mode: Manual semantic grouping based on:

  • Shared root concepts
  • User intent alignment (informational / commercial / navigational)
  • Topic hierarchy (broad → specific)

Phase 3: Cluster Architecture

3A: Pillar-Cluster Mapping

For each topic area, design the cluster hierarchy:

PILLAR: [Broad Topic] — "The Complete Guide to [Topic]"
│
├── CLUSTER 1: [Subtopic Group A]
│   ├── Article: [Specific subtopic A1]
│   ├── Article: [Specific subtopic A2]
│   └── Article: [Specific subtopic A3]
│
├── CLUSTER 2: [Subtopic Group B]
│   ├── Article: [Specific subtopic B1]
│   ├── Article: [Specific subtopic B2]
│   └── Article: [Specific subtopic B3]
│
├── CLUSTER 3: [Subtopic Group C]
│   ├── Article: [Specific subtopic C1]
│   └── Article: [Specific subtopic C2]
│
└── SUPPORTING: [Glossary terms, FAQs, tools]
    ├── Glossary: [Term 1]
    ├── Glossary: [Term 2]
    └── FAQ: [Common questions]

3B: Content Type Assignment

For each piece in the cluster:

Content TypeWhen to UseTypical Word Count
Pillar pageBroad topic overview, links to all cluster content3,000-5,000+
Cluster articleDeep dive on subtopic1,500-3,000
Comparison postvs/ or alternatives content2,000-3,500
How-to guideStep-by-step instruction1,500-2,500
Glossary entryDefinition + context500-1,000
Tool/CalculatorInteractive resource500 + tool
Case studyProof point1,000-2,000
ListicleCurated collection1,500-3,000

3C: Internal Linking Architecture

Design the linking structure:

  1. Pillar → All cluster articles (every cluster article gets a link from the pillar)
  2. Cluster articles → Pillar (every article links back to the pillar)
  3. Cluster articles ↔ Related cluster articles (cross-links within the cluster)
  4. Cross-cluster links where topics overlap
  5. Supporting content → Relevant cluster articles (glossary terms link to articles that explain them in depth)

Map specific anchor text for each link.

Phase 4: Gap Analysis & Prioritization

4A: Coverage Gap Matrix

SubtopicYour ContentCompetitor ACompetitor BVolumeDifficultyGap?
[subtopic 1]✗ None✓ Pillar page✓ Blog post[vol][diff]✓ High priority
[subtopic 2]✓ Thin post✓ Deep guide✗ None[vol][diff]✓ Update needed
[subtopic 3]✓ Strong guide✓ Similar✓ Similar[vol][diff]✗ Covered
[subtopic 4]✗ None✗ None✗ None[vol][diff]✓ White space

4B: Priority Scoring

Score each content piece to create:

FactorWeightDescription
Search volume25%Monthly search demand
Competitive gap25%How much better can you be than what exists?
Intent alignment20%Does the searcher match your ICP?
Cluster completeness15%Does this fill a critical gap in a cluster?
Effort15%How much work to create high-quality content?

4C: Content Calendar

Based on content capacity and priority scores:

Month 1: Build [N] pillar foundations

  • [Pillar 1] — [rationale]
  • [3-5 highest-priority cluster articles]

Month 2: Deepen Cluster 1, start Cluster 2

  • [5-8 articles] — [rationale]

Month 3: Complete Cluster 2, begin Cluster 3

  • [5-8 articles] — [rationale]

Months 4-6: Expansion

  • [Continue pattern based on capacity]

Phase 5: Output

# Topical Authority Map — [Site/Client] — [DATE]

## Executive Summary
- Topic areas mapped: [N]
- Total content pieces identified: [N] (pillars: [N], clusters: [N], supporting: [N])
- Existing content: [N] pages ([N] strong, [N] need updates, [N] gaps)
- Net new content needed: [N] pages
- Estimated timeline to full coverage: [N] months at [N] articles/month

---

## Topic Map: [Topic Area 1]

### Cluster Architecture
[Visual tree structure per Phase 3A]

### Pillar Page
- **Target keyword:** [keyword] ([volume]/mo, [difficulty])
- **Title:** [recommended title]
- **Content type:** Comprehensive guide
- **Word count target:** [X]-[Y]
- **Links to:** [all cluster articles listed]
- **Status:** [Exists — needs update / New — priority [P0/P1/P2]]

### Cluster: [Subtopic Group A]

#### Article: [Subtopic A1]
- **Target keyword:** [keyword] ([volume]/mo, [difficulty])
- **Content type:** [how-to / comparison / listicle / etc.]
- **Word count target:** [X]-[Y]
- **Links to:** Pillar + [related articles]
- **Links from:** Pillar + [related articles]
- **Priority:** [P0/P1/P2]
- **Anchor text:** "[anchor]" from pillar, "[anchor]" from [related article]

#### Article: [Subtopic A2]
...

### Cluster: [Subtopic Group B]
...

---

## Topic Map: [Topic Area 2]
...

---

## Internal Linking Matrix

| From ↓ / To → | Pillar | Article A1 | Article A2 | Article B1 | ... |
|----------------|--------|-----------|-----------|-----------|-----|
| **Pillar** | — | ✓ "[anchor]" | ✓ "[anchor]" | ✓ "[anchor]" | |
| **Article A1** | ✓ "[anchor]" | — | ✓ "[anchor]" | | |
| **Article A2** | ✓ "[anchor]" | ✓ "[anchor]" | — | | |
| **Article B1** | ✓ "[anchor]" | | | — | |

---

## Content Calendar

### Month 1: Foundation
| Week | Content Piece | Type | Cluster | Keywords | Priority |
|------|--------------|------|---------|----------|----------|
| W1 | [Pillar: Topic 1] | Pillar page | — | [kw] ([vol]) | P0 |
| W1 | [Article A1] | Cluster article | A | [kw] ([vol]) | P0 |
| W2 | [Article A2] | Cluster article | A | [kw] ([vol]) | P0 |
| W2 | [Article B1] | Cluster article | B | [kw] ([vol]) | P0 |

### Month 2: Depth
...

### Month 3: Expansion
...

---

## Coverage Gap Report

### High Priority (Competitors rank, you don't)
| Topic | Competitor Coverage | Your Status | Volume | Recommended Action |
|-------|-------------------|-------------|--------|--------------------|
| [topic] | A: Pillar, B: Blog post | None | [vol] | Create [content type] |

### Medium Priority (Weak coverage)
| Topic | Your Current Page | Issue | Volume | Recommended Action |
|-------|------------------|-------|--------|--------------------|
| [topic] | [URL] | Thin (400 words) | [vol] | Expand to [X] words, add [sections] |

### Existing Content Updates Needed
| URL | Issue | Action Required | Effort |
|-----|-------|----------------|--------|
| [url] | Outdated (2023 data) | Update stats, refresh examples | 2 hours |
| [url] | No internal links | Add [N] links to cluster articles | 30 min |
| [url] | Missing from pillar | Add link from pillar with "[anchor]" | 15 min |

---

## Metrics to Track
- **Topical coverage %** — Articles created vs. total identified
- **Internal link density** — Avg links per article within cluster
- **Cluster ranking velocity** — Time from publish to page 1 per cluster
- **Pillar page rankings** — Position for head terms
- **Organic traffic by cluster** — Traffic attributed to each topic cluster

Save to the current working directory or wherever the user prefers.

For large topic maps (3+ topic areas), also export a summary CSV: content-calendar-[YYYY-MM-DD].csv

Cost

ComponentCost
Site catalog (your site, once)~$0.05-0.10
Site catalog per competitor~$0.05-0.10
SEO domain analyzer~$0.10-0.20
Reddit scraper (per topic area)~$0.05-0.10
DataForSEO keyword data (enhanced)~$0.50-3.00 (depending on keyword count)
Keywords Everywhere (enhanced alt)~$0.01-0.10
Page fetches (competitor content analysis)~$0.01-0.05
AnalysisFree (LLM reasoning)
Total per topic area (baseline)~$0.25-0.50
Total per topic area (enhanced)~$0.75-3.50
3 topic areas (baseline)~$0.75-1.50
3 topic areas (enhanced)~$2.25-10.50

Tools Required

  • Apify API token — APIFY_API_TOKEN env var
  • Upstream skills: site-content-catalog, seo-domain-analyzer, reddit-post-finder, fetch_webpage
  • Optional (enhanced): DataForSEO (DATAFORSEO_LOGIN + DATAFORSEO_PASSWORD), Keywords Everywhere (KEYWORDS_EVERYWHERE_API_KEY), SEMrush (SEMRUSH_API_KEY), or Ahrefs (AHREFS_API_TOKEN)

Scheduling

For ongoing topical authority tracking:

  • Run quarterly to reassess coverage gaps
  • Monthly: check for new subtopics emerging in the space
  • After each content batch: update the map with published URLs and internal links

Trigger Phrases

  • "Map our topical authority for [topic]"
  • "Build a topic cluster strategy"
  • "What content gaps do we have?"
  • "Create a content calendar for SEO"
  • "How do we build authority in [topic area]?"
  • "Plan our content architecture"

平台分布

Codex

37.26%
按下载量换算49

Claude

30.14%
按下载量换算39

Cursor

16.56%
按下载量换算22

Gemini CLI

8.67%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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