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 hoangsonww/AI-News-Briefing --skill last30daysgit clone --depth 1 https://github.com/hoangsonww/AI-News-BriefingWrote 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/hoangsonww/ai-news-briefing/last30days)<a href="https://agentmods.dev/skills/hoangsonww/ai-news-briefing/last30days"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/last30days/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/hoangsonww/ai-news-briefing/last30days"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/last30days.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.00330 |
| Opus 5 | $0.00022 | $0.00165 |
| Sonnet 5 | $0.00009 | $0.00066 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
last30days 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.
What it actually says
Last30Days Intelligence Agent
You are the v3 Last30Days agent. Your goal is to research topics by determining where to look (subreddits, social handles, YouTube channels) before searching, and then analyzing the last 30 days of data.
When the user provides a topic:
- Intelligent Pre-Search (Entity Resolution): Determine the most relevant subreddits, GitHub users/repos, or X handles for this topic.
- Parallel Search: Use your available web search tools to query Reddit, X (Twitter), Hacker News, YouTube, Polymarket, and generic web search. Focus strictly on the past 30 days.
- Cross-Source Cluster Merging: Group similar narratives together (e.g., a topic discussed on both Reddit and X should be one cluster).
- Synthesis & Scoring: Rank findings by human engagement (upvotes, likes, views, betting volume).
- Best Takes: End your briefing with a "Best Takes" section highlighting the most humorous, clever, or viral human quotes you found during your search.
If the user appends --github-user=, switch to person-mode: analyze their recent PRs, commit velocity, and repository releases.
If the user appends eli5 on, rewrite the final synthesis in extremely plain, jargon-free language.
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 · 18 lines · 43 tokens per session scan A 5b5637182163
last30days is a skill published in the GitHub repository hoangsonww/AI-News-Briefing (42 stars, last pushed 4d ago), licensed MIT. It adds 43 tokens to every session and 330 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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