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tapestrytapestry 搜索

Agent Skill

tapestry 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

250

周安装

10

GitHub Stars

54

下载量

81
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:tapestry(tapestry 搜索)
来源仓库:https://github.com/natsufox/tapestry
仓库路径:skills/tapestry
安装命令:
npx skills add https://github.com/natsufox/tapestry --skill tapestry
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/natsufox/tapestry --skill tapestry

简介

用于查找、检索和筛选相关信息,支持基于关键词或任务场景的内容定位。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中快速获取候选结果,提升研究效率。
  • 通过 npx 安装,需确认权限范围和维护状态,注意潜在的联网或文件访问行为。
  • 建议结合来源仓库和原始 README 核验具体功能与使用限制。
  • tapestry 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

🧵 Tapestry

AI-Native Web Intelligence Workflow

Tapestry is a complete workflow for turning scattered web content into organized, searchable knowledge. It handles everything from crawling to synthesis across multiple platforms.

When to Use Tapestry

Use this skill when the user:

  • Shares URLs to ingest (from Zhihu, Reddit, HN, X/Twitter, Xiaohongshu, Weibo, or any webpage)
  • Wants to archive or capture web content
  • Asks to organize content into a knowledge base
  • Wants structured feeds or analysis of web content
  • Needs to visualize their knowledge base
  • Wants to manage RSS/Atom feed subscriptions (list, add, remove sources)
  • Wants to refresh or fetch the latest content from subscribed sources

Workflow Overview

Tapestry has eight internal sub-skills that work together:

  1. Init Deps Install (init-deps-install/SKILL.md) - Auto-triggered dependency installation (Phase 0: setup)
  2. Ingest (ingest/SKILL.md) - Crawl and capture URLs (Phase 1: deterministic)
  3. Synthesis (synthesis/SKILL.md) - Analyze and organize into knowledge base (Phase 2: AI-driven)
  4. Feed (feed/SKILL.md) - Generate structured, source-aware feeds
  5. Display (display/SKILL.md) - Visualize the knowledge base as a website
  6. Visual Card (visual-card/SKILL.md) - Generate visual note cards from KB content
  7. Subscriptions (subscriptions/SKILL.md) - Manage RSS/Atom sources and refresh them into the knowledge base
  8. Export (export/SKILL.md) - Export KB content to PDF, Markdown, or HTML files saved under _data/exports/

Two-Phase Architecture

Tapestry uses a two-phase design with automatic dependency setup:

Phase 0 (Init): Auto-triggered dependency installation when first launched or dependencies missing Phase 1 (Ingest): Deterministic extraction → _data/notes/YYYY/MM/ (date-organized) Phase 2 (Synthesis): AI-driven analysis → _data/books/{topic}/{chapter}/ (book-organized)

By default, synthesis runs automatically after each ingest (synthesis.mode: "auto" in tapestry.config.json). You can configure this to "manual" or "batch" mode.

How to Use This Skill

Step 1: Understand the User's Intent

Analyze what the user wants:

  • Just capture? → Use ingest only (set synthesis mode to "manual" if needed)
  • Structured feed? → Use ingest + feed
  • Analysis/organization? → Use ingest + synthesis (default with "auto" mode)
  • Browse knowledge base? → Use display
  • Visual summary? → Use visual-card to generate infographic cards
  • Complete workflow? → Ingest automatically triggers synthesis in "auto" mode
  • Manage subscriptions? → Use subscriptions (list/add/remove sources)
  • Refresh subscribed feeds? → Use subscriptions fetch → ingest → synthesis pipeline

Step 2: Execute the Appropriate Sub-Skill(s)

Read and follow the instructions in the relevant sub-skill SKILL.md files:

For Dependency Installation (Auto-Triggered)

Read the file init-deps-install/SKILL.md to understand the detection and installation workflow. All installation steps require explicit user confirmation before execution.

For URL Ingestion

Read the file ingest/SKILL.md, then follow the workflow described there.

For Structured Feeds

Read the file feed/SKILL.md, then follow the workflow described there.

For Synthesis & Knowledge Base

Read the file synthesis/SKILL.md, then follow the workflow described there.

For Visualization

Read the file display/SKILL.md, then follow the workflow described there.

For Visual Cards

Read the file visual-card/SKILL.md, then follow the workflow described there.

For Subscription Management & Feed Refresh

Read the file subscriptions/SKILL.md, then follow the workflow described there.

Step 3: Chain Sub-Skills When Needed

The sub-skills reference each other. When one sub-skill says to "route to" another, read that sub-skill's SKILL.md and follow its instructions.

Supported Platforms

  • 🇨🇳 Zhihu: Questions, answers, articles, profiles
  • 🐦 X/Twitter: Posts, threads
  • 📱 Xiaohongshu: Notes, profiles
  • 🇨🇳 Weibo: Posts
  • 🔶 Hacker News: Discussions with full comment trees
  • 🤖 Reddit: Threads
  • 🌐 Generic HTML: Any webpage (fallback)

Key Principles

  1. Read sub-skill instructions first: Each sub-skill's SKILL.md contains detailed workflow steps
  2. Follow the deterministic pipeline: Ingest → Feed → Synthesis → Display
  3. Respect user intent: Don't over-process if they just want capture
  4. Chain appropriately: Let sub-skills hand off to each other as described in their instructions
  5. Report clearly: Tell the user what was done and where artifacts are stored

Directory Structure

tapestry/
├── SKILL.md (this file)          # Main orchestrator
├── init-deps-install/SKILL.md     # Dependency installation sub-skill
├── ingest/SKILL.md                # URL crawling sub-skill
├── feed/SKILL.md                  # Feed generation sub-skill
├── synthesis/SKILL.md             # Analysis & KB sub-skill
├── display/SKILL.md               # Visualization sub-skill
├── visual-card/SKILL.md           # Visual card generation sub-skill
├── subscriptions/SKILL.md         # RSS/Atom subscription management sub-skill
├── _src/                          # Shared code (crawlers, parsers, storage)
└── _tests/                        # Unit tests

Example Usage Patterns

Pattern 1: Simple Capture

User: "Ingest this Zhihu answer: https://www.zhihu.com/question/123/answer/456"

Action:
1. Read ingest/SKILL.md
2. Follow its workflow to capture the URL
3. Report the created artifacts

Pattern 2: Structured Feed

User: "Give me a structured feed of this Reddit thread"

Action:
1. Read ingest/SKILL.md and capture the URL
2. Read feed/SKILL.md and generate the structured feed
3. Present the feed to the user

Pattern 3: Full Analysis (Default)

User: "Analyze this HN discussion and add it to my knowledge base"

Action:
1. Read ingest/SKILL.md and capture the URL
2. Synthesis runs automatically (default "auto" mode)
3. Report where the content was organized in the KB

Pattern 4: Manual Synthesis

User: "Just capture these URLs for now, I'll organize them later"

Action:
1. Set synthesis mode to "manual" in tapestry.config.json
2. Read ingest/SKILL.md and capture the URLs
3. User can later run synthesis on selected URLs

Pattern 4: Batch Processing

User: "Ingest these 5 URLs and organize them"

Action:
1. Read ingest/SKILL.md and batch process all URLs
2. With "auto" mode, synthesis runs for each URL automatically
3. Summarize the results

Pattern 5: Subscription Refresh

User: "Refresh all my subscribed feeds"

Action:
1. Read subscriptions/SKILL.md
2. Run: python subscriptions/_scripts/run.py fetch
3. Collect the printed URLs
4. Pass them to $tapestry-ingest for ingestion
5. Let the synthesis pipeline run per config

Pattern 6: Export KB Content

User: "Export the entire knowledge base as PDF"

Action:
1. Read export/SKILL.md
2. Run: python export/_scripts/export.py --format pdf --scope kb
3. Report the output paths from _data/exports/pdf/

Important Notes

  • Always read the sub-skill SKILL.md files: They contain the actual implementation details
  • Don't invent workflows: Follow what's written in the sub-skill instructions
  • Preserve artifacts: The pipeline creates _data/captures/, _data/feeds/, _data/notes/, _data/books/, and _data/exports/
  • Respect the architecture: Ingest is deterministic, synthesis is interpretive
  • Check for errors: Sub-skills may fail; handle gracefully and report to user

Resources

  • _src/: Shared Python code for crawlers, parsers, and storage
  • _tests/: Unit tests for the shared code
  • Each sub-skill has its own _scripts/, _specs/, or _kb_rules/ directories

Remember: This main skill is an orchestrator. The real work happens in the sub-skills. Read their SKILL.md files and follow their instructions.

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

38.19%
按下载量换算31

Claude

28.2%
按下载量换算23

Cursor

18.71%
按下载量换算15

Gemini CLI

10.19%
按下载量换算8

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

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 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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