agentleFS
dannotedannote/dot-pi/skills/ai-news/SKILL.md

ai-news

Skill57 starsChanged 5 months agoMITView on GitHub

Fetch and curate AI news from X/Twitter list. Use when user asks for AI news, AI digest, what's happening in AI, or wants a summary of AI announcements, papers, and releases.

6 other projects use a version of this, 1 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Check oldest tweet's createdAt — if < 24h ago, fetch next page with --cursor

    line 98

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

AI News Digest

Fetch and curate important AI news from the user's X/Twitter AI list.

Prerequisites

  • @dannote/bird-premium package (official X API v2)
  • AI list ID: 1894700501725229467

Workflow

  1. Fetch tweets from the last 24 hours (use pagination to get all)
  2. Filter out noise (marketing, challenges, hiring, retweets, emojis-only)
  3. Categorize into: Releases, Papers, Insights, Tools
  4. Extract actual announcement links from tweet text (t.co URLs to blogs, GitHub, arxiv)
  5. 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

Example Usage

User: "What's happening in AI today?"

  1. Fetch first page:
    bunx --bun @dannote/bird-premium list-timeline 1894700501725229467 -n 100 --json
  2. Check oldest tweet's createdAt — if < 24h ago, fetch next page with --cursor
  3. Repeat until oldest tweet is > 24h old
  4. Merge all tweets, filter to last 24h by createdAt
  5. Parse JSON, extract: author.username, text, id
  6. Build source link: https://x.com/{username}/status/{id}
  7. Extract t.co links from text, resolve to actual URLs when relevant
  8. Filter noise, categorize, output curated digest

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.