Agent skill

AI News Radar

by LearnPrompt in LearnPrompt/ai-news-radar

A skill your agent uses when working on AI News Radar, 24 小时 AI 更新雷达, AI 更新雷达, 伯乐Skill, or Scout Skill: finding high-signal AI/tech sources, adding RSS/OPML/GitHub feeds, checking source health…

MITAuto-check: notesDevOps & Cloud

Install AI News Radar

skills CLI
$ npx skills add LearnPrompt/ai-news-radar --skill ai-news-radar -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LearnPrompt/ai-news-radar ai-news-radar --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LearnPrompt/ai-news-radar.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-news-radar .claude/skills/ai-news-radar && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ai-news-radar
GitHub stars
1.8k
Token cost
~2.5k tokens
SKILL.md length
1,122 words
Files
5 (incl. references)
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when working on AI News Radar, 24 小时 AI 更新雷达, AI 更新雷达, 伯乐Skill, or Scout Skill: finding high-signal AI/tech sources, adding RSS/OPML/GitHub feeds, checking source health…

  • Works in 5 steps: Context pass: read the current docs,… → Product diagnostic: identify the user,… → Coverage pass: classify each requested… → …
  • Working on AI News Radar
  • SKILL.md covers First Reads, V2 Workflow, Product Direction and Safety Rules, plus 5 more sections
  • Calls python, gh and node; needs AGENTMAIL_API_KEY

What it does

AI News Radar is an agent skill from LearnPrompt/ai-news-radar. Use when working on AI News Radar, 24 小时 AI 更新雷达, AI 更新雷达, 伯乐Skill, or Scout Skill: finding high-signal AI/tech sources, adding RSS/OPML/GitHub feeds, checking source health, updating the web UI, GitHub Actions, or GitHub Pages deployment.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `README.md`, `agents/openai.yaml` and `references/source-intake.md`).

It sits in DevOps & Cloud, covering CI/CD, Frontend development and Deployment. It works with GitHub and GitHub Actions. The repository describes itself as: 24h AI/tech news radar with GitHub Actions, live web UI, and Scout Skill for AI sources. The licence is MIT.

When your agent uses it

  • Working on AI News Radar
  • Scout Skill: finding high-signal AI/tech sources
  • Adding RSS/OPML/GitHub feeds
  • Checking source health

Example prompts

  • “/ai-news-radar”

Requirements

  • Python 3
  • A credential in AGENTMAIL_API_KEY

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Context pass: read the current docs, source status, recent commits, and
  2. Product diagnostic: identify the user, current workaround, signal-density
  3. Coverage pass: classify each requested source as official feed, OPML,
  4. Alternatives pass: when the choice is not obvious, present 2-3 approaches
  5. Implementation pass: make small diffs, reuse existing fetcher/UI patterns,

What it can do on your machine

Read from SKILL.md and the folder at commit cd4d7da. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python
    • gh
    • node
    • git
    • pytest

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh and git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AGENTMAIL_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AI News Radar loads about 2.5k tokens when it runs, and up to ~5.3k if it reads all its reference files. Until then it costs about 63 tokens; SKILL.md has 1,122 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:65
    s, tokens, cookies, browser exports, or `.env` values into code or logs.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LearnPrompt/ai-news-radar at commit cd4d7da, republished under its MIT licence (© LearnPrompt). 1,122 words, ~2,542 tokens.

Download SKILL.mdSave it as .claude/skills/ai-news-radar/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
ai-news-radar
description
Use when working on AI News Radar, 24 小时 AI 更新雷达, AI 更新雷达, 伯乐Skill, or Scout Skill: finding high-signal AI/tech sources, adding RSS/OPML/GitHub feeds, checking source health, updating the web UI, GitHub Actions, or GitHub Pages deployment.

AI News Radar

First Reads

When this skill triggers inside the repo, read these files first:

  • skills/ai-news-radar/README.md for the public-facing 伯乐Skill / Scout Skill positioning, source-intake prompt, and install-after-first-message guidance.
  • README.md for project usage and current commands.
  • docs/GPT_HANDOFF.md before release-readiness checks or handing the project to another agent.
  • docs/SOURCE_COVERAGE.md before changing source strategy.
  • docs/ROADMAP.md before changing Source Overlap Check, story merge, or version planning.
  • docs/V2_PRODUCT_BRIEF.md before changing product positioning or first-screen UX.
  • scripts/update_news.py before changing data generation.
  • assets/app.js, assets/styles.css, and index.html before changing the UI.
  • references/source-intake.md when the user provides a new site, GitHub repo, RSS feed, newsletter, X source, or asks whether a source can be ingested.
  • references/v2-method.md when the user asks for product optimization, source coverage strategy, Skill packaging, or "v2" direction.

V2 Workflow

Use this order for non-trivial product or source-strategy work:

  1. Context pass: read the current docs, source status, recent commits, and the smallest relevant code surface before proposing changes.
  2. Product diagnostic: identify the user, current workaround, signal-density problem, narrowest useful default, and what must stay in the advanced layer.
  3. Coverage pass: classify each requested source as official feed, OPML, public GitHub-generated feed, public archive, static page, X bridge, optional API adapter, or private inbox/bridge.
  4. Alternatives pass: when the choice is not obvious, present 2-3 approaches: minimal viable, durable architecture, and optional creative/packaged variant.
  5. Implementation pass: make small diffs, reuse existing fetcher/UI patterns, add tests for behavior changes, and run the fastest relevant validation.

For detailed prompts and decision criteria, read references/v2-method.md.

Product Direction

Maintain a two-layer product:

  • Default layer: a simple curated Signal view for ordinary AI enthusiasts.
  • Advanced layer: custom OPML, source health, GitHub Actions, AgentMail email intelligence, and maintainer controls.

Avoid adding many reader-facing choices. Prefer better defaults, source quality, and clearer status output.

The v2 packaging goal is a forkable public site plus a reusable agent Skill. The public-facing Skill name is 伯乐Skill in Chinese and Scout Skill in English. It should feel concrete and easy to use: a scout that helps choose high-signal sources worth tracking, instead of implying that the system knows everything or blindly adding every noisy feed. Ordinary users should be able to browse the hosted page. Maintainers should be able to add their own sources with OPML, public generated feeds, or secret-backed optional adapters without changing the public default.

Safety Rules

  • Never commit private feeds/follow.opml.
  • Never paste secrets, tokens, cookies, browser exports, or .env values into code or logs.
  • Keep the public repo runnable without API keys.
  • Prefer official RSS/Atom/OPML sources over fragile scraping.
  • Avoid account-bound social timelines as defaults.
  • Prefer reading public generated feeds over reimplementing another project's API or scraping pipeline.
  • Treat X API, email, WeChat, private newsletters, and cookies as optional advanced integrations. Store credentials only in environment variables or GitHub Secrets.
  • Treat AgentMail as a private advanced source, not a public default source. Never commit AGENTMAIL_API_KEY, AGENTMAIL_INBOX_ID, inbox addresses, full email bodies, raw emails, or private newsletter contents.
  • Keep AgentMail disabled unless EMAIL_DIGEST_ENABLED=1 is explicit. For QQ Agent Mail, use AGENTMAIL_PROVIDER=agently_cli after agently-cli auth login; default to agently-cli message +list. Only an explicitly authorized private run may set AGENTMAIL_RESOLVE_PUBLIC_URLS=1 to read allowed senders’ messages in memory for archive URLs; never persist bodies. Keep this disabled in the public workflow. The legacy API path may use AGENTMAIL_PROVIDER=api with AGENTMAIL_API_KEY and AGENTMAIL_INBOX_ID, but it must only call the list-messages endpoint; do not call /raw or read text/html bodies.
  • Do not publish data/email-digest.json to public Pages by default. Only allow publication when the maintainer explicitly sets EMAIL_DIGEST_PUBLISH=1 and understands the site/repo privacy implications.

Add Personal Sources

When the user has installed or forked the project but does not know how to start, ask them for a source list first. A good kickoff prompt is:

text
请使用伯乐Skill,先问我要信息源清单,然后帮我判断每个信源该用 RSS、OPML、公开 feed、静态页面、Jina 兜底、AgentMail 邮箱还是跳过。目标是部署一个不需要服务器、能用 GitHub Actions 自动更新的 AI 日报网站。不要把任何 API Key、cookies、token、真实 OPML、邮箱正文或私有邮件内容写入仓库。

Use OPML for private customization:

bash
cp feeds/follow.example.opml feeds/follow.opml
python scripts/update_news.py --output-dir data --window-hours 24 --rss-opml feeds/follow.opml

For GitHub Actions deployment, base64 encode feeds/follow.opml and save it as the repository secret FOLLOW_OPML_B64 to override the public demo OPML. If the secret is not configured, the workflow uses feeds/follow.example.opml as a small public RSS/OPML demo so the hosted page shows the OPML path working. Do not commit the private OPML file. For AgentMail, use EMAIL_DIGEST_ENABLED=1 plus either AGENTMAIL_PROVIDER=agently_cli for a locally authorized QQ Agent Mail CLI, or AGENTMAIL_PROVIDER=api with AGENTMAIL_API_KEY and AGENTMAIL_INBOX_ID in environment variables or GitHub Secrets. Keep EMAIL_DIGEST_INCLUDE_IN_RADAR and EMAIL_DIGEST_PUBLISH unset unless the maintainer explicitly wants a private Pages/repo to publish the metadata-only email digest.

Show full SKILL.md (412 more words)Show less

Evaluate A New Source

When a user gives a source URL, first classify it:

  • RSS/Atom/OPML: add privately through feeds/follow.opml unless it should help every public visitor.
  • GitHub project with generated feeds: inspect README, workflows, output files, and raw JSON/RSS URLs; prefer consuming its public feed files.
  • Official changelog or static page: add a focused fetcher only if stable.
  • Newsletter: prefer public archive RSS or archive pages. Use AgentMail only for private newsletter/product-update inboxes; keep it disabled by default and do not expose full bodies, raw emails, inbox ids, or private mailbox addresses.
  • X/Twitter: prefer curated central feeds that already use official X API; direct X API should be optional and secret-backed.

For detailed intake checks and implementation patterns, read references/source-intake.md.

Add A Built-In Source

Only add a built-in source when it is useful to most public visitors.

  1. Run Source Overlap Check for candidate RSS/Atom sources before promoting them into the public default layer:

    bash
    python scripts/evaluate_source_overlap.py \
      --source-url https://example.com/feed.xml \
      --source-name "Example Source" \
      --site-id example_candidate \
      --baseline data/archive.json \
      --lookback-days 7 \
      --output reports/source-intake/example-overlap.json

    Treat the report as advisory: low duplication supports accept_default, high duplication supports skip_duplicate, and small samples or medium duplication should stay watchlist / OPML advanced first.

  2. Inspect existing fetchers in scripts/update_news.py.

  3. Add fetch_<source>(session, now) returning list[RawItem].

  4. Use existing helpers for URL normalization, date parsing, and sessions.

  5. Register the fetcher in the built-in task list.

  6. Update docs/SOURCE_COVERAGE.md when coverage changes.

  7. Add or update tests when behavior changes.

  8. Run a local source-only probe before the full end-to-end generation.

GitHub Project Feed Pattern

For repos like follow-builders, look for public files such as:

  • feed.json, feed-x.json, feed-blogs.json, latest.json
  • state*.json for dedupe behavior
  • .github/workflows/*.yml for schedules, secrets, and output commit paths
  • config/*.json for source lists

If the generated feed is public, stable, timestamped, and low-noise, add a built-in fetcher that reads the raw GitHub URL. Do not copy its private tokens or rebuild its crawler unless the user explicitly wants a self-hosted variant.

Validate

Run the fastest relevant checks:

bash
python -m py_compile scripts/update_news.py
python -m pytest -q
node --check assets/app.js
git diff --check
python "${CODEX_HOME:-$HOME/.codex}/skills/.system/skill-creator/scripts/quick_validate.py" skills/ai-news-radar

For AgentMail changes, also verify default-off safety:

bash
pytest -q tests/test_topic_filter.py -k agentmail

Confirm the checks cover: disabled AgentMail makes no network request, enabled but missing credentials makes no network request, the adapter only uses the list-messages endpoint, and email body/raw fields are not emitted.

When the Skill itself changes, validate the Skill package too:

bash
python "${CODEX_HOME:-$HOME/.codex}/skills/.system/skill-creator/scripts/quick_validate.py" skills/ai-news-radar

For an end-to-end local run:

bash
python scripts/update_news.py --output-dir data --window-hours 24 --rss-opml feeds/follow.opml
python -m http.server 8080

Open http://localhost:8080 and confirm the Signal view, all-source view, WaytoAGI block, search, site filter, and source counts still work.

After pushing source changes, trigger and watch the workflow:

bash
gh workflow run update-news.yml --repo LearnPrompt/ai-news-radar --ref master
gh run list --repo LearnPrompt/ai-news-radar --limit 5

© LearnPrompt, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/ai-news-radar of LearnPrompt/ai-news-radar.

  • SKILL.md
  • README.md
  • agents/openai.yaml
  • references/source-intake.md
  • references/v2-method.md

Open the folder on GitHubat commit cd4d7da

Compare with similar skills

AI News Radar next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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GitHub Actions Docsdevantler-tech/ksail1652 repos~1.3kAutomated safety check: PassCustom licence
CI CDEliasOulkadi/shokunin114—~3.4kAutomated safety check: NotesMIT
Desktop Release PreflightEynzof/Hermes-CN-Desktop1.8k—~1.6kAutomated safety check: NotesCustom licence

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Categories

Questions about AI News Radar

What does AI News Radar do?

A skill your agent uses when working on AI News Radar, 24 小时 AI 更新雷达, AI 更新雷达, 伯乐Skill, or Scout Skill: finding high-signal AI/tech sources, adding RSS/OPML/GitHub feeds, checking source health…. AI News Radar is an agent skill from LearnPrompt/ai-news-radar. Use when working on AI News Radar, 24 小时 AI 更新雷达, AI 更新雷达, 伯乐Skill, or Scout Skill: finding high-signal AI/tech sources, adding RSS/OPML/GitHub feeds, checking source health, updating the web UI, GitHub Actions, or GitHub Pages deployment.

When should I use AI News Radar?

AI News Radar fits situations like: working on AI News Radar; scout Skill: finding high-signal AI/tech sources; adding RSS/OPML/GitHub feeds; checking source health.

How do I install AI News Radar in Claude Code?

Run `npx skills add LearnPrompt/ai-news-radar --skill ai-news-radar -a claude-code`. Or copy the skill folder (skills/ai-news-radar in LearnPrompt/ai-news-radar) into .claude/skills/ai-news-radar in your project. Claude Code loads it when a task matches its description.

How do I install AI News Radar in Codex?

Run `npx skills add LearnPrompt/ai-news-radar --skill ai-news-radar -a codex`. Or copy the skill folder (skills/ai-news-radar in LearnPrompt/ai-news-radar) into .agents/skills/ai-news-radar in your project. Codex loads it when a task matches its description.

Can I use AI News Radar in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LearnPrompt/ai-news-radar --skill ai-news-radar -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-news-radar, .gemini/skills/ai-news-radar, .github/skills/ai-news-radar and .opencode/skills/ai-news-radar in your project.

What does AI News Radar need to run?

Going by SKILL.md and its folder, AI News Radar needs the command-line tools its instructions call (python, gh, node, git and pytest) and credentials named AGENTMAIL_API_KEY. Our summary lists: Python 3; A credential in AGENTMAIL_API_KEY.

Does AI News Radar access the network?

SKILL.md contains no URLs. Its commands use gh and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is AI News Radar safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does AI News Radar use?

AI News Radar is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does AI News Radar use?

About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.7k tokens, read only when the agent opens those files.

What are the alternatives to AI News Radar?

Skills that share tags, products or a category with AI News Radar: Use Vercel Action (amondnet/vercel-action, 764 stars), Prepare Cloudflare Production Deployment (LubomirGeorgiev/cloudflare-workers-nextjs-saas-template, 786 stars), GitHub Actions Docs (devantler-tech/ksail, 165 stars) and CI CD (EliasOulkadi/shokunin, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AI News Radar?

LearnPrompt (a GitHub user) maintains it in LearnPrompt/ai-news-radar, which has 1,768 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 11, 2026.

Source: LearnPrompt/ai-news-radar on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.