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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.

Install Skill

Shared

Installs to .agents/skills, used by Codex, Amp, Warp, Cursor, OpenCode, and more.

CodexAmp
Warp
CursorOpenCode
Cline
Gemini CLI
GitHub Copilot
Personal

Available across projects.

$npx skills-installer add @LearnPrompt/ai-news-radar/ai-news-radar --client shared
Project

Writes to .agents/skills.

$npx skills-installer add @LearnPrompt/ai-news-radar/ai-news-radar -p --client shared
Note: Review the skill instructions before using it.

SKILL.md

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 and both required credentials are present. 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:

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:

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, AGENTMAIL_API_KEY, and AGENTMAIL_INBOX_ID only in environment variables or GitHub Secrets. Keep EMAIL_DIGEST_PUBLISH unset unless the maintainer explicitly wants a private Pages/repo to publish the metadata-only email digest.

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:

    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:

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:

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:

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

For an end-to-end local run:

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:

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