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 dannote/dot-pi --skill ai-newsgit clone --depth 1 https://github.com/dannote/dot-piWrote 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/dannote/dot-pi/ai-news)<a href="https://agentmods.dev/skills/dannote/dot-pi/ai-news"><img src="https://agentmods.dev/badge/skills/dannote/dot-pi/ai-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.
<a href="https://agentmods.dev/skills/dannote/dot-pi/ai-news"><img src="https://agentmods.dev/badge/skills/dannote/dot-pi/ai-news.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 | $0.00830 |
| Opus 5 | $0.00022 | $0.00415 |
| Sonnet 5 | $0.00009 | $0.00166 |
| Haiku 4.5 | $0.00004 | $0.00083 |
Grade A, and why
ai-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.
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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI News Digest
Fetch and curate important AI news from the user's X/Twitter AI list.
Prerequisites
@dannote/bird-premiumpackage (official X API v2)- AI list ID:
1894700501725229467
Workflow
- Fetch tweets from the last 24 hours (use pagination to get all)
- Filter out noise (marketing, challenges, hiring, retweets, emojis-only)
- Categorize into: Releases, Papers, Insights, Tools
- Extract actual announcement links from tweet text (t.co URLs to blogs, GitHub, arxiv)
- Include tweet link as source
Fetching Last 24 Hours
The list produces ~250-300 tweets per day. Use pagination to fetch all:
# First request (100 tweets max per request)
bunx --bun @dannote/bird-premium list-timeline 1894700501725229467 -n 100 --json
# Continue with cursor from previous response until createdAt < 24h ago
bunx --bun @dannote/bird-premium list-timeline 1894700501725229467 -n 100 --cursor <nextCursor> --json
Stop fetching when the oldest tweet's createdAt is older than 24 hours.
Merge all tweets from paginated responses, then filter by createdAt >= (now - 24h).
Filtering Criteria
Include (important)
- Model releases and announcements
- Research papers (arxiv links, paper titles)
- Tool/library releases with technical details
- Benchmark results
- Technical insights and analysis
- Infrastructure updates (vLLM, ComfyUI, MLX, etc.)
- API launches
Exclude (noise)
- Marketing fluff ("excited to announce", "join us")
- Challenges and contests
- Hiring posts
- Retweets (text starting with "RT @")
- Single emoji or short reaction posts
- Partnership announcements without technical substance
- Repetitive product links spam
Output Format
Organize into sections. Extract actual links from tweet text when available (GitHub, arxiv, blog posts). Include tweet as source.
## Releases
**ProductName** (Company) — Brief description
Link: https://github.com/org/repo (or blog/arxiv link from tweet)
Source: https://x.com/username/status/ID
## Papers
**Paper Title** — One-line summary (Institution)
Link: https://arxiv.org/abs/XXXX
Source: https://x.com/username/status/ID
## Insights
**Topic** — Key finding or leak
Source: https://x.com/username/status/ID
## Tools
**Tool** — What it does
Link: https://example.com
Source: https://x.com/username/status/ID
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.
- 10d ago First seen · 105 lines · 43 tokens per session scan A 9752c20f934e
ai-news is a skill published in the GitHub repository dannote/dot-pi (51 stars, last pushed 5d ago), licensed MIT. It adds 43 tokens to every session and 830 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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