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 msdakot/ai-foundary --skill content-curator-researchgit clone --depth 1 https://github.com/msdakot/ai-foundaryWrote 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/msdakot/ai-foundary/content-curator-research)<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.
<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>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 | $0.00041 | $0.00807 |
| Sonnet 5 | $0.00016 | $0.00323 |
| Haiku 4.5 | $0.00008 | $0.00161 |
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 11d 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.
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.
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.
- 11d ago First seen · 158 lines · 82 tokens per session scan A 36d9c991a4dd
content-curator-research is a skill published in the GitHub repository msdakot/ai-foundary (5 stars, last pushed 4mo ago), licensed MIT. It adds 82 tokens to every session and 1,615 once invoked, about $0.0004 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 2026-08-31.
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