What is content-curator-research?

An automated research workflow that checks several technology sources for recent AI and software developments and records the findings in a daily report.

Use it to monitor sources such as Hacker News, GitHub Trending, company AI blogs, research papers, and social posts for selected AI topics.

It collects scattered updates in one dated file, so later writing can use a recent research record instead of starting from scratch.

content-curator-research — Skill for Claude Code and Codex by msdakot

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 msdakot/ai-foundary --skill content-curator-research

Clone the repo

git clone --depth 1 https://github.com/msdakot/ai-foundary

Made for: Claude Code, 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/msdakot/ai-foundary/content-curator-research/github.svg)](https://agentmods.dev/skills/msdakot/ai-foundary/content-curator-research)

Your own site

<a href="https://agentmods.dev/skills/msdakot/ai-foundary/content-curator-research"><img src="https://agentmods.dev/badge/skills/msdakot/ai-foundary/content-curator-research/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/msdakot/ai-foundary/content-curator-research"><img src="https://agentmods.dev/badge/skills/msdakot/ai-foundary/content-curator-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,615 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.

Origin original 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.

Model	Per session	Once invoked
Fable 5.1	$0.00082	$0.01615
Opus 5.5	$0.00033	$0.00646
Sonnet 5.5	$0.00016	$0.00323
Haiku 4.5	$0.00008	$0.00161

Measured 2mo ago against content hash 36d9c991a4dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

content-curator-research 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 2mo 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.

skills/social-media/content-curator-research/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an autonomous AI research agent. Run every step in order. Do not ask questions. If a source fails, log it and continue.

Config:

{
  "email": "<YOUR_EMAIL>",
  "repo_url": "<YOUR_REPO_SSH_URL>",
  "repo_clone_dir": "<YOUR_LOCAL_REPO_DIR>",
  "output_subdir": "content-curator",
  "cadence": "0 6,12,17 * * *",
  "topics": ["LLM", "Claude", "OpenAI", "MCP", "ADK", "agent", "open-source AI", "AI orchestration", "transformer", "fine-tuning", "RAG", "agentic", "multimodal", "reasoning model", "harness", "vibe coding"],
  "star_history_url": "https://star-history.com/compare"
}

Setup: Replace <YOUR_EMAIL>, <YOUR_REPO_SSH_URL>, and <YOUR_LOCAL_REPO_DIR> with your own values before using this skill.

Step 1 — Prepare repo

Expand <YOUR_LOCAL_REPO_DIR> to absolute path. If it doesn't exist:

git clone <YOUR_REPO_SSH_URL> <YOUR_LOCAL_REPO_DIR>

If it exists:

cd <YOUR_LOCAL_REPO_DIR> && git pull --rebase origin main

Ensure <YOUR_LOCAL_REPO_DIR>/content-curator/ exists. Determine today's filename: research-MMDDYY.md (e.g. research-042026.md).

Determine sweep number: if the file doesn't exist → sweep 1. If it exists, count existing ## Sweep headings in it → that count + 1 is this run's sweep number.

Step 2 — HackerNews

WebFetch https://hacker-news.firebaseio.com/v0/topstories.json → first 30 IDs. For each, WebFetch https://hacker-news.firebaseio.com/v0/item/{id}.json. Filter by topic keywords (case-insensitive on title/url). Sort by score. Keep top 5. Extract: title, score, comment count, URL, 2–3 sentence "why it matters" note.

Step 3 — GitHub Trending

WebFetch https://github.com/trending?since=daily and https://github.com/trending/python?since=daily. Filter repos whose name or description matches any topic keyword. Keep top 5 unique. Extract: repo name, description, stars-today, URL, 2–3 sentence summary.

Step 4 — Google AI Blog

WebFetch https://blog.google/technology/ai/rss/. Parse 8 most recent items. Extract: title, pubDate, link, 2–3 sentence editorial summary.

Read the full file on GitHub · 158 lines

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.

2mo ago First seen · 158 lines · 82 tokens per session scan A 36d9c991a4dd

Subscribe to this mod's changes

content-curator-research is a skill published in the GitHub repository msdakot/ai-foundary (5 stars, last pushed 6mo ago), licensed MIT. It adds 82 tokens to every session and 1,615 once invoked, about $0.0003 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 2026-08-31.

Research

content-curator-research next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
content-curator-researchmsdakot/ai-foundary	Skill	5	6mo ago	MIT	A	82	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code