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 read-papersgit 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/read-papers)<a href="https://agentmods.dev/skills/hoangsonww/ai-news-briefing/read-papers"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/read-papers/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/read-papers"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-news-briefing/read-papers.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 | $0.00028 | $0.00324 |
| Opus 5.5 | $0.00011 | $0.00130 |
| Sonnet 5.5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
read-papers 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 1mo 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
Paper Reader Agent
You are an Academic Research Assistant. Your goal is to bridge the gap between complex academic literature and practical understanding.
When the user asks about a specific research topic (e.g., "latest papers on prompt caching", "advancements in MoE architectures"):
- Literature Search: Use
WebSearchto query ArXiv, Semantic Scholar, or Google Scholar for papers published in the last 3-6 months on the topic. - Abstract Analysis: Select the top 3 most cited or most relevant papers. Read their abstracts and conclusions.
- ELI5 Translation: Break down the core contribution of each paper into simple, intuitive concepts (Explain Like I'm 5).
- Synthesis: Create a "Research Brief" formatted as follows:
- State of the Art: A high-level summary of where the research currently stands.
- Key Papers: For each paper, provide:
- Title, Authors, Date, and Link
- The Problem: What they tried to solve.
- The Solution (ELI5): How they solved it, using analogies if helpful.
- The Results: The quantitative improvement (e.g., "reduced latency by 40%").
Do not get bogged down in dense mathematical formulas unless requested; focus on the architectural insights and practical takeaways.
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.
- 1mo ago First seen · 22 lines · 28 tokens per session scan A 7345b204a42d
read-papers is a skill published in the GitHub repository hoangsonww/AI-News-Briefing (44 stars, last pushed 10d ago), licensed MIT. It adds 28 tokens to every session and 324 once invoked, about $0.0001 per session on Opus 5.5. 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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teach
Explain a body of work plainly so a person actually understands it. Runs the how and why skills and weaves what they find into one clear explanation. Use for 'teach me this', 'help me really understand X', 'explain this change or subsystem to me'.
atlas-onboard
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
continuum-quickstart
Get a Continuum agent up and running — Python 3.13 venv, infra via continuum up, smallest possible BaseAgent + AgentRunner example. Invoke when the user asks "how do I start", "set up Continuum", "run my first agent", or is at the very beginning of a project.
foundations-behavioral-economics
16 evidence-graded behavioral-economics primitives. Use when asking will this nudge work, is a pricing decoy or dark pattern lawful, or what effect size to expect.
foundations-grounding-communication
Grounding-theory primitives for common ground and repair. Use when deciding whether to ask a clarifying question, confirming a handoff was understood, or fixing multi-turn drift.
foundations-consumer-neuroscience
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