Gold News Sentiment
by @cyecho-io
Use this skill when users want to pull recent global gold-related news, assess short-term or medium-term market sentiment for gold, connect macro drivers lik...
clawhub install gold-news-sentiment📖 About This Skill
name: gold-news-sentiment description: Use this skill when users want to pull recent global gold-related news, assess short-term or medium-term market sentiment for gold, connect macro drivers like Fed policy, US yields, USD, inflation, geopolitics, and ETF flows to gold, and produce a structured conclusion such as 看涨, 看跌, or 观望 with confidence and risks.
gold-news-sentiment
Use this skill to turn recent gold-related news into a structured market sentiment read.
The default job is not to produce a trading call from vibes. The default job is to:
When To Use
Use this skill when the user wants to:
看涨, 看跌, or 观望Core Rules
1. Treat the output as analysis support, not investment advice.
2. Prefer high-credibility and recent sources over volume.
3. Do not let repeated headlines count as multiple independent signals.
4. Separate news sentiment from price trend. They often diverge.
5. Always state uncertainty, key assumptions, and what could invalidate the conclusion.
Workflow
1. Check for a fresh cached snapshot
Before doing a fresh pull, check whether these files already exist:
data/latest_sentiment.mddata/latest_digest.mddata/latest_news.jsonIf data/latest_sentiment.md is fresh enough for the user's need, use it first so the user gets an immediate answer. Default freshness window:
If the cache is stale, missing, or the user explicitly asks for a refresh, continue with a fresh pull.
For the recurring workflow, read references/automation-template.md.
2. Pull recent news
Run the bundled script from the skill directory:
python3 scripts/fetch_news.py --hours 48 --limit 40
Use --query when the user wants a narrower theme such as:
The script outputs normalized JSON with:
For source coverage and caveats, read references/source-list.md.
For cached fast-path updates, prefer:
python3 scripts/update_snapshot.py --hours 48 --limit 50
This refreshes:
data/latest_news.jsondata/latest_digest.mdThe automation can then write:
data/latest_sentiment.md3. Remove weak signals
Before analysis:
If the fetch step returns zero usable items or includes request failures, do not fabricate a sentiment conclusion. Report that retrieval failed or that the evidence is insufficient, then stop or ask for a narrower rerun.
If more detail is needed, read references/scoring-rules.md.
4. Classify each item
Classify each article into one of:
bullish_for_goldbearish_for_goldmixed_or_unclearbackground_onlyThen note the driver category:
Do not force a directional label when the causal chain is weak.
5. Aggregate into a market read
Build the conclusion in this order:
1. short-term news balance 2. macro driver alignment or conflict 3. whether price-sensitive drivers are pointing the same way 4. remaining uncertainty
Default horizon:
短线: next few sessions to two weeks中线: next one to three monthsIf the user does not specify a horizon, provide both.
6. Produce the final output
Use this structure unless the user asks for another format:
结论:观望情绪方向:
短线:偏多
中线:中性 置信度:中
核心驱动:
主要新闻:
1.
2.
3.
为什么不是明确看涨/看跌:
风险提示:
Output Discipline
看涨 conclusion requires multiple aligned bullish drivers, not one dramatic headline.看跌 conclusion requires multiple aligned bearish drivers, not just temporary USD strength.观望 when the main drivers conflict or the incoming news is too noisy.偏多 or 偏空 in the explanation even when the final top-line conclusion is 观望.Validation Checks
Before answering, verify:
Automation Guidance
For recurring runs, the automation prompt should ask for:
看涨 / 看跌 / 观望 conclusionWhen data/latest_sentiment.md exists and is fresh, answer from it first unless the user asks for a real-time refresh.
Avoid claiming certainty. If the signal is mixed, say so.