Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add zrtch/awesome-skills --skill daily-ai-news-skillgit clone --depth 1 https://github.com/zrtch/awesome-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zrtch/awesome-skills/daily-ai-news-skill)<a href="https://agentmods.dev/skills/zrtch/awesome-skills/daily-ai-news-skill"><img src="https://agentmods.dev/badge/skills/zrtch/awesome-skills/daily-ai-news-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zrtch/awesome-skills/daily-ai-news-skill"><img src="https://agentmods.dev/badge/skills/zrtch/awesome-skills/daily-ai-news-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.02135 |
| Opus 5 | $0.00032 | $0.01068 |
| Sonnet 5 | $0.00013 | $0.00427 |
| Haiku 4.5 | $0.00006 | $0.00214 |
Grade A, and why
daily-ai-news scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to daily-ai-news — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily AI News Briefing
Aggregates the latest AI news from multiple sources and delivers concise summaries with direct links
When to Use This Skill
Activate this skill when the user:
- Asks for today's AI news or latest AI developments
- Requests a daily AI briefing or updates
- Mentions wanting to know what's happening in AI
- Asks for AI industry news, trends, or breakthroughs
- Wants a summary of recent AI announcements
- Says: "给我今天的AI资讯" (Give me today's AI news)
- Says: "AI有什么新动态" (What's new in AI)
Workflow Overview
This skill uses a 4-phase workflow to gather, filter, categorize, and present AI news:
Phase 1: Information Gathering
├─ Direct website fetching (3-5 major AI news sites)
└─ Web search with date filters
↓
Phase 2: Content Filtering
├─ Keep: Last 24-48 hours, major announcements
└─ Remove: Duplicates, minor updates, old content
↓
Phase 3: Categorization
└─ Organize into 5 categories
↓
Phase 4: Output Formatting
└─ Present with links and structure
Phase 1: Information Gathering
Step 1.1: Fetch from Primary AI News Sources
Use mcp__web_reader__webReader to fetch content from 3-5 major AI news websites:
Recommended Primary Sources (choose 3-5 per session):
- VentureBeat AI: https://venturebeat.com/category/ai/
- TechCrunch AI: https://techcrunch.com/category/artificial-intelligence/
- The Verge AI: https://www.theverge.com/ai-artificial-intelligence
- MIT Technology Review AI: https://www.technologyreview.com/topic/artificial-intelligence/
- AI News: https://artificialintelligence-news.com/
- AI Hub Today: https://ai.hubtoday.app/
Parameters:
return_format: markdownwith_images_summary: false (focus on text content)timeout: 20 seconds per source
Step 1.2: Execute Web Search Queries
Use WebSearch with date-filtered queries to discover additional news:
Query Template (adjust dates dynamically):
General: "AI news today" OR "artificial intelligence breakthrough" after:[2025-12-23]
Research: "AI research paper" OR "machine learning breakthrough" after:[2025-12-23]
Industry: "AI startup funding" OR "AI company news" after:[2025-12-23]
Products: "AI application launch" OR "new AI tool" after:[2025-12-23]
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 328 lines · 64 tokens per session scan A aaa80691167d
daily-ai-news is a skill published in the GitHub repository zrtch/awesome-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 64 tokens to every session and 2,135 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to daily-ai-news, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…
training-check
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.