AI Tech Insight Compass turns daily AI trend research into source-backed, publication-ready technical articles.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-tech-insight-compass
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-tech-insight-compass using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is AI Tech Insight Compass?
AI Tech Insight Compass is an Openclaw Skills research and content-production workflow for tracking AI, LLM, and machine learning developments. It combines web search, GitHub trend validation, multi-source summarization, technical writing, and article publishing into one repeatable pipeline.
The skill is designed to reduce a typical four-hour research-and-writing process to approximately 30 minutes while producing 3,000–5,000-word technical articles with practical code examples, precise technology tags, and an emphasis on actionable analysis. It is particularly useful for AI newsletters, daily technology reports, developer publications, and public-account content.
AI Tech Insight Compass Use Cases
- Generate a daily AI technology intelligence report from current news, research papers, and open-source activity.
- Track LLM developments such as MoE, long-context models, reasoning, RLHF, SFT, Transformers, and KV Cache optimization.
- Validate emerging technology trends using GitHub repository activity, star counts, and project descriptions.
- Produce in-depth technical articles with at least four substantial code examples.
- Create AI-focused newsletters, technology insight posts, or public-account articles.
- Respond to triggers such as “generate today’s AI technology news,” “write a deep technical article,” “AI daily report,” and “technology insights.”
- Publish completed articles to a configured public-account or document platform through an HTTP API.
How AI Tech Insight Compass Works
- Collect current signals: Use the
brave-searchskill to search for daily AI, LLM, arXiv, and technology developments using topic-specific queries. - Validate open-source momentum: Use the GitHub skill and
ghCLI to identify relevant repositories, inspect star counts, and verify whether an apparent trend has supporting project activity. - Aggregate evidence: Pass collected material to the
summarizeworkflow, which extracts major events, technical principles, related projects, and potential industry impact. - Select a focused angle: Choose one technically meaningful topic rather than producing a broad news roundup.
- Write the article: Invoke
tech-article-proto create a 3,000–5,000-word technical deep dive in a professional technology-publication style. - Apply quality requirements: Include at least four valid code examples of at least 10 lines each, five or more accurate technology tags, and at least 70% technical content.
- Save the artifact: Copy the generated Markdown article into a date-based workspace directory.
- Publish the result: Send the title, content, and category to the configured article API, such as a public-account or Feishu document publishing endpoint.
- Return structured status: Record the date, topic, source counts, article metadata, tags, and publication status.
AI Tech Insight Compass Setup
- Install or enable the collaborating Openclaw Skills:
brave-search,github,summarize, andtech-article-pro. - Confirm that the Brave Search workflow and GitHub CLI are available and authenticated.
- Create the expected workspace and article directories.
- Configure the publishing API URL, authentication, and destination category before enabling production publishing.
- Run the daily workflow with a topic trigger or the supplied script.
cd ~/Projects/agent-scripts/skills/brave-search
./search.js "AI LLM latest progress" -n 8 --content
./search.js "LLM reasoning RLHF" -n 8 --content
./search.js "arXiv AI latest papers" -n 5 --content
gh api graphql -f query='{
search(query: "AI LLM created:>2026-08-01", type: REPOSITORY, first: 10) {
nodes { ... on Repository { nameWithOwner stars: stargazerCount description url } }
}
}'
python3 scripts/summarize.py --input /tmp/tech_intel.md --mode insight
cd /root/skills/ai-tech-insight-compass
python3 scripts/daily_intel.py --topic "Latest AI Agent developments"
For publication, configure the destination endpoint and replace placeholder article fields with the generated title and Markdown content:
curl -X POST http://your-publishing-host:3001/api/articles \
-H "Content-Type: application/json" \
-d '{"title":"...","content":"...","category":"AI Technology"}'
AI Tech Insight Compass Data Schema & Taxonomy
The workflow produces both a Markdown article artifact and a structured execution record.
| Field or artifact | Description |
|---|---|
date |
Execution or publication date, such as 2026-08-10. |
topic |
Focused AI or LLM research topic selected for the article. |
sources.search_results |
Number of web-search results collected. |
sources.github_repos |
Number of relevant GitHub repositories reviewed. |
sources.papers |
Number of research papers included in the evidence set. |
article.title |
Publication-ready technical article title. |
article.word_count |
Target body length of 3,000–5,000 words. |
article.code_examples |
Target count of at least four code examples. |
article.tech_tags |
At least five precise tags such as MoE, LLM, KV Cache, or RLHF. |
status |
Processing result, such as published. |
Generated files are organized by date, for example:
/root/articles/YYYY-MM-DD/tech-insight-daily.md
The metadata taxonomy covers source provenance, technical topic, model or systems concepts, open-source evidence, article quality metrics, and publication state. The expected evidence mix is web-search results plus GitHub Trending or repository data plus arXiv papers. The final article should contain at least 70% technical material and preserve links or references to the underlying sources when available.
AI Tech Insight Compass Advanced Features
- Multi-skill orchestration across search, GitHub analysis, summarization, technical writing, and publishing.
- Evidence triangulation that combines current web results, open-source repository signals, and arXiv research.
- GitHub GraphQL queries for repository discovery, star counts, descriptions, and trend validation.
- Insight-mode summarization that separates major breakthroughs, technical mechanisms, projects, and industry impact.
- Topic-focused editorial selection to turn a broad daily news stream into one deep technical narrative.
- Enforced article quality targets for word count, code-example quantity, code-example size, technology tags, and technical-content ratio.
- Date-based artifact organization for repeatable daily archives and easier content operations.
- Structured publication status and source-count metadata suitable for automation monitoring.
- Configurable HTTP publishing integration for public accounts, document systems, or internal content platforms.
- Trigger-driven execution for daily reports, technology intelligence requests, and AI trend investigations using Openclaw Skills.
SKILL.md
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