db-ai-github-paper-weekly-news

db-ai-github-paper-weekly-news is a skill for Codex from digoal/blog. It costs 181 tokens per session (2,285 once invoked), scanned A, original, GPL-2.0.

A guide for collecting and summarizing the past week’s news about databases, artificial intelligence, GitHub, and AI research papers.

In plain words
What is it for?
Fetching the latest items from its supported sources and writing a Markdown newsletter with images and Mermaid diagrams.
Why use it?
It gathers updates from multiple named sources into one weekly report instead of requiring separate manual searches.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Fetching the latest items from its supported sources and writing a Markdown newsletter with images and Mermaid diagrams.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/digoal/blog/db-ai-github-paper-weekly-news
View source ↗ digoal/blog
About the project

digoal/blog is a large collection of Chinese-language articles, courses, videos, and practical learning materials about databases, especially PostgreSQL and related systems, along with topics such as AI, open source, business, and finance. It is for database administrators, developers, architects, and others learning database technologies and their applications.

digoal/blog · 8,569 stars · on GitHub

Install

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.

Any agent
npx skills add digoal/blog --skill db-ai-github-paper-weekly-news
Clone the repo
git clone --depth 1 https://github.com/digoal/blog

Made for: Codex.

Wrote 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.

agentmods badge for db-ai-github-paper-weekly-news

README.md
[![agentmods](https://agentmods.dev/badge/skills/digoal/blog/db-ai-github-paper-weekly-news/github.svg)](https://agentmods.dev/skills/digoal/blog/db-ai-github-paper-weekly-news)
Your own site
<a href="https://agentmods.dev/skills/digoal/blog/db-ai-github-paper-weekly-news"><img src="https://agentmods.dev/badge/skills/digoal/blog/db-ai-github-paper-weekly-news/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.

agentmods 80×15 button for db-ai-github-paper-weekly-news

Your own site · 80×15
<a href="https://agentmods.dev/skills/digoal/blog/db-ai-github-paper-weekly-news"><img src="https://agentmods.dev/badge/skills/digoal/blog/db-ai-github-paper-weekly-news.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 181 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,285 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00181 $0.02285
Opus 5 $0.00090 $0.01143
Sonnet 5 $0.00036 $0.00457
Haiku 4.5 $0.00018 $0.00229

Measured 10d ago against content hash fdf0b511e7ad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

db-ai-github-paper-weekly-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 10d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/crawl.py, scripts/parse_postgres_git.py, scripts/parse_postgresweekly.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/db-ai-github-paper-weekly-news/SKILL.md · 129 lines

The source is not reproduced here

Licensed GPL-2.0

The repository is licensed GPL-2.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

7 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.

Changes

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.

  1. 10d ago First seen · 129 lines · 181 tokens per session scan A fdf0b511e7ad

Subscribe to this mod's changes

db-ai-github-paper-weekly-news is a skill published in the GitHub repository digoal/blog (8,569 stars, last pushed yesterday), licensed GPL-2.0. It adds 181 tokens to every session and 2,285 once invoked, about $0.0009 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.