ai-newsletter-chn

Generate a daily AI news newsletter for a Chinese audience from fresh web sources, summarizing current AI/ML articles into Markdown and JSON with Simplified...

Security Scan

The skill's requested API keys and runtime instructions are consistent with producing a daily Chinese AI news digest; nothing in the SKILL.md asks for unrelated secrets, binaries, or installs.

Purpose & Capability

The skill's description (daily AI newsletter for a Chinese audience) matches the runtime instructions: searching the web, fetching pages, filtering, summarizing, and translating output into Simplified Chinese. The required environment variables (BRAVE_API_KEY and FIRECRAWL_API_KEY) are coherent with the declared required-tools (web_search, web_fetch) and are plausible for performing search and crawl operations. Minor inconsistency: registry name/slug is ai-newsletter-chn while SKILL.md uses ai-newsletter-daily and metadata version 1.2.1 vs registry 1.0.0 — this is likely a bookkeeping/versioning mismatch but does not affect capability alignment.

Instruction Scope

SKILL.md contains a detailed, deterministic workflow that confines actions to web search, fetch, filtering, ranking, summarization, and translation. It does not instruct the agent to read local files, other env vars, or to exfiltrate data to unrelated endpoints. The instructions rely on the platform-provided web_search and web_fetch tools; the safety of actual network interactions depends on those tool implementations (not on the skill text itself).

Install Mechanism

No install spec and no code files are present — this is instruction-only. Nothing will be written to disk or executed beyond the agent following the prose workflow, which minimizes install-time risk.

Credentials

The skill requires two API keys: BRAVE_API_KEY and FIRECRAWL_API_KEY. Both are justifiable given the need to perform web searches and fetch pages. There are no other unexpected secrets or config paths requested. Users should understand that providing these keys grants the skill the ability to perform network searches/fetches via those services.

Persistence & Privilege

The skill is not always-enabled and is user-invocable; disable-model-invocation is false (normal). It does not request system-wide config changes or persistent privileges. Autonomous invocation is allowed by default but not combined with other red flags here.

Assessment

This skill appears coherent and instruction-only, but consider the following before installing: (1) You must supply BRAVE_API_KEY and FIRECRAWL_API_KEY — only provide keys you trust and understand (check provider terms, billing, and rate limits). (2) The skill will fetch arbitrary web pages via the web_fetch tool: ensure you trust how that tool performs requests (it may expose your agent's network metadata or consume your API quota). (3) Verify whether translation and summarization result quality meets your needs and whether any fetched content is paywalled or proprietary. (4) Note minor metadata inconsistencies (skillKey/version/name differences) — not dangerous but worth confirming you have the intended version. If you are uncomfortable sharing the two API keys, do not install; otherwise this skill is proportionate to its stated purpose.

AI Newsletter Daily

Generate a concise daily AI newsletter for a Chinese audience from fresh web sources.

Use this skill only when the request is about current AI/ML news, releases, research, funding, product launches, model updates, regulation, benchmarks, or practitioner-relevant developments.

Do not use this skill for:

• Evergreen explainers.
• Non-AI topics.
• Long-form research that is not intended to become a curated newsletter.

Inputs

Expected inputs, with defaults if missing:

• target_news_count = 20
• search_query = "latest AI news today"
• search_time_window_days = 2
• max_search_results = 60
• min_articles_required = 10
• include_domains = []
• exclude_domains = ["youtube.com", "reddit.com", "facebook.com", "x.com", "twitter.com"]
• summary_model = "host-default"
• max_scrape_retries = 2

Rules:

• Clamp target_news_count to 1..50.
• Clamp search_time_window_days to 1..14.
• Clamp max_search_results to 20..120.
• Clamp min_articles_required to 1..50.
• Clamp max_scrape_retries to 0..5.
• If min_articles_required > target_news_count, set min_articles_required = target_news_count.

Batch policy

Use a two-stage batch limit:

• Search batch: collect up to max_search_results candidates from search.
• Scrape batch: keep the top target_news_count * 2 ranked candidates for fetch and summary attempts.
• Final batch: return only the top target_news_count verified items.

Do not summarize every search result. Over-collect, filter, verify, then reduce to the final batch.

Required outputs

Return all of the following:

1. newsletter_items as a list of objects.
2. markdown_newsletter as a string.
3. json_newsletter as an object.

Each newsletter item must include:

• title
• url
• domain
• published_at
• summary
• relevance_score
• source_query

Use "unknown" for published_at when no date is available.

Deterministic workflow

1. Resolve inputs.

   • Apply defaults and bounds.
   • Initialize warnings = [].
   • Initialize seen_canonical_urls = set().
   • Initialize processed_urls = set().

2. Search.

   • Run web_search with search_query.
   • If there are no usable results, retry once with:
     • "{search_query} generative AI LLM model open source enterprise"
   • If there are still no usable results, fail with a clear message.

3. Normalize and filter.

   • Keep only results with non-empty title and URL.
   • Canonicalize URLs by lowering the host, removing tracking parameters when possible, and normalizing safe trailing slashes.
   • Drop duplicates by canonical URL.
   • Apply include_domains and exclude_domains.
   • Prefer results likely within search_time_window_days.
   • Keep unknown dates, but score them lower.

4. Rank.

   • Score each candidate from 0 to 100:
     • AI-topic relevance: 0..50.
     • Freshness: 0..30.
     • Title/snippet clarity: 0..20.
   • Sort by:
     • relevance_score descending
     • published_at descending, unknown last
     • url ascending
   • Keep the top target_news_count * 2 candidates.

5. Verify and summarize.

   • Process candidates in ranked order until target_news_count verified items are collected.
   • Skip candidates whose canonical URL is already in processed_urls.
   • Attempt web_fetch up to max_scrape_retries + 1 times.
   • If fetch fails, add a warning with the URL and reason, then continue.
   • Cross-check search result vs fetched page using title similarity, domain consistency, topic alignment, and published date when available.
   • If the page appears materially inconsistent, skip it and warn.
   • Summarize each accepted article in one short plain-text paragraph, max about 80 words, focused on why it matters to AI practitioners.

6. Minimum quality gate.

   • If collected items are fewer than min_articles_required, run one fallback search with:
     • "AI news today machine learning model release funding research"
   • Process only new candidates not already seen or processed.
   • Repeat filtering, ranking, verification, and summarization.

7. Final integrity check.

   • Ensure every final item has non-empty title, url, domain, summary, source_query, and numeric relevance_score.
   • Ensure each URL appears once.
   • Ensure markdown_newsletter and json_newsletter match in item count.
   • Remove and warn on any invalid item.

8. Finalize.

   • Sort by relevance_score descending, then published_at descending.
   • Truncate to target_news_count.
   • Render markdown_newsletter.
   • Assemble json_newsletter.
   • Apply the language output rule below.
   • Return all outputs.

Language output

• Translate the final markdown_newsletter body and each article summary in newsletter_items into Simplified Chinese.
• Keep title, url, domain, published_at, relevance_score, and source_query unchanged.
• If a source title is already in Chinese, preserve it as-is.
• Do not add extra commentary outside the newsletter content.

Verification

Accept items only if:

• URL is valid and canonicalized.
• Search result and fetched page broadly match.
• Topic is actually AI/news relevant.
• Published date is present or safely unknown.
• Fetched content is not malformed or off-topic.

Record warnings for failed URLs, short reasons, and whether fallback search was used.

Output Format

markdown_newsletter:

• H1 title with date.
• One H2 per article.
• One short summary paragraph per article.
• One source link per article.

json_newsletter:

• date
• query
• count
• articles
• warnings

Safety rules

• Use only sanctioned tools.
• Do not request API keys from the user.
• Do not expose secrets.
• Do not include copyrighted full article text.
• Keep summaries neutral, concise, and factual.
• Preserve deterministic behavior wherever tool outputs allow.