laborany
基于 Claude Code 的桌面 AI 工作力平台 — 支持飞书/QQ 远程调度、技能创建、定时任务。OpenClaw 的桌面实现,零代码养好你的 AI 🦞 Desktop AI workforce platform built on Claude Code. Feishu/QQ bot integration, skill c...
Auto-analyze URLs/info for OpenClaw strategic value, classify, create Obsidian notes, update memory. Use when user shares a URL, article, tweet, or any external info source.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install 2233admin/openclaw-skill-intelligence-ingestionInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
When the user shares a URL, article, tweet, thread, or any piece of external information, execute this pipeline automatically. Do NOT ask for permission — just process it.
USE this skill when:
DO NOT USE when:
read_url_content or browser)Assign one primary category and up to 2 secondary tags:
| Category | Description | Examples |
|---|---|---|
infra |
Infrastructure / protocols / networking | Pilot Protocol, MCP, networking stacks |
strategy |
Routing / cost / architecture decisions | Model routing, multi-account, fallback chains |
skill |
Agent skills / tools / capabilities | OpenAI Skills, Skill design patterns |
theory |
Conceptual frameworks / mental models | Bayes, decision theory, learning loops |
tutorial |
How-to guides / learning material | Claude Code, OpenClaw tutorials |
product |
Tools / apps / services | LM Studio, new AI models, apps |
community |
OpenClaw ecosystem / discussions | Community posts, feature requests |
threat |
Risks / security / deprecation | API changes, breaking updates, security alerts |
For each piece of information, evaluate:
## Strategic Asses...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
Auto-analyze URLs and external information for strategic value.
Pipeline: READ -> CLASSIFY -> ANALYZE -> MAP -> STORE -> REMEMBER -> RESPOND
Most users do not need more content. They need better filtering. This skill turns noisy external information into structured, actionable intelligence.
# 1) Install
openclaw skills install github:sarahmirrand001-oss/openclaw-skill-intelligence-ingestion
# 2) Trigger
Analyze this: https://example.com/article
# 3) Verify
# - Obsidian note created
# - memory/YYYY-MM-DD.md updated
# - response includes category + strategic value
SKILL.md: skill behavior and 7-step pipelineindex.html: public landing page for sharingvercel.json: static deployment configThis repo is static-site ready for Vercel.
vercel --prod
# Intelligence Ingestion Skill When the user shares a URL, article, tweet, thread, or any piece of external information, execute this pipeline automatically. Do NOT ask for permission — just process it. ## Trigger Conditions **USE this skill when:** - User sends a URL (x.com, github.com, any domain) - User pastes article text or tweet content - User says "analyze this", "evaluate this", "what do you think about this" - User forwards content from Telegram or any messaging surface - User shares something and asks about strategic value **DO NOT USE when:** - User is asking a general question unrelated to external content - User is asking about internal workspace files - User explicitly says they don't want analysis ## Pipeline Steps ### Step 1: READ — Extract Content 1. If a URL is provided, read the full content (use `read_url_content` or browser) 2. If text is pasted, use it directly 3. If X/Twitter link fails to parse (common), search web for the tweet content ### Step 2: CLASSIFY — What Is This? Assign **one primary category** and up to 2 secondary tags: | Category | Description | Examples | |----------|------------|---------| | `infra` | Infrastructure / protocols / networking | Pilot Protocol, MCP, networking stacks | | `strategy` | Routing / cost / architecture decisions | Model routing, multi-account, fallback chains | | `skill` | Agent skills / tools / capabilities | OpenAI Skills, Skill design patterns | | `theory` | Conceptual frameworks / mental models | Bayes, decision theory, learning loops | | `tutorial` | How-to guides / learning material | Claude Code, OpenClaw tutorials | | `product` | Tools / apps / services | LM Studio, new AI models, apps | | `community` | OpenClaw ecosystem / discussions | Community posts, feature requests | | `threat` | Risks / security / deprecation | API changes, breaking updates, security alerts | ### Step 3: ANALYZE — Strategic Value Assessment For each piece of information, evaluate: ```markdown ## Strategic Asses...
# OpenClaw Skill: Intelligence Ingestion Auto-analyze URLs and external information for strategic value. Pipeline: **READ -> CLASSIFY -> ANALYZE -> MAP -> STORE -> REMEMBER -> RESPOND** ## Why Most users do not need more content. They need better filtering. This skill turns noisy external information into structured, actionable intelligence. ## Quick Start ```bash # 1) Install openclaw skills install github:sarahmirrand001-oss/openclaw-skill-intelligence-ingestion # 2) Trigger Analyze this: https://example.com/article # 3) Verify # - Obsidian note created # - memory/YYYY-MM-DD.md updated # - response includes category + strategic value ``` ## What It Produces - Structured Obsidian note - Daily memory log update - Strategic value score (Critical/High/Medium/Low) - Next action recommendation ## Main Files - `SKILL.md`: skill behavior and 7-step pipeline - `index.html`: public landing page for sharing - `vercel.json`: static deployment config ## Deploy This repo is static-site ready for Vercel. ```bash vercel --prod ```
基于 Claude Code 的桌面 AI 工作力平台 — 支持飞书/QQ 远程调度、技能创建、定时任务。OpenClaw 的桌面实现,零代码养好你的 AI 🦞 Desktop AI workforce platform built on Claude Code. Feishu/QQ bot integration, skill c...
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