Fetches and analyzes gold fundamental data from FRED, CFTC, SPDR ETF, and Fed RSS. Used when the user requests gold fundamental analysis, phân tích cơ bản và...
编程
Gold News Sentiment
试用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...
它能做什么
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...
技能文档
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:
- gather recent gold-relevant news
- reuse a fresh cached snapshot when available
- separate signal from repeated headlines and noise
- connect the news to macro drivers that usually matter for gold
- output a disciplined conclusion with uncertainty and risk notes
When To Use
Use this skill when the user wants to:
- get a current gold market sentiment snapshot
- understand whether recent news is net bullish or bearish for gold
- classify the environment as
看涨,看跌, or观望 - summarize the main drivers behind gold price moves
- run a recurring workflow that tracks gold-related sentiment over time
Core Rules
- Treat the output as analysis support, not investment advice.
- Prefer high-credibility and recent sources over volume.
- Do not let repeated headlines count as multiple independent signals.
- Separate
news sentimentfromprice trend. They often diverge. - 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.json
If 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:
- interactive use: 6 hours
- slower-moving medium-term questions: up to 24 hours if the user accepts it
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:
- central bank buying
- Fed rate cuts
- geopolitics
- ETF flows
- inflation
The script outputs normalized JSON with:
- title
- source
- published time
- link
- query bucket
- provider
- detected tags
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.md
The automation can then write:
data/latest_sentiment.md
3. Remove weak signals
Before analysis:
- deduplicate near-identical headlines
- down-weight aggregator rewrites
- discard clearly stale items if newer reports supersede them
- flag articles that mention gold only in passing
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_only
Then note the driver category:
- Fed / rates
- US real yields
- USD
- inflation
- labor / growth slowdown
- geopolitics / risk-off
- central bank demand
- ETF / investor flows
- physical demand / supply
Do not force a directional label when the causal chain is weak.
5. Aggregate into a market read
Build the conclusion in this order:
- short-term news balance
- macro driver alignment or conflict
- whether price-sensitive drivers are pointing the same way
- remaining uncertainty
Default horizon:
短线: next few sessions to two weeks中线: next one to three months
If 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
- A
看涨conclusion requires multiple aligned bullish drivers, not one dramatic headline. - A
看跌conclusion requires multiple aligned bearish drivers, not just temporary USD strength. - Use
观望when the main drivers conflict or the incoming news is too noisy. - Prefer
偏多or偏空in the explanation even when the final top-line conclusion is观望.
Validation Checks
Before answering, verify:
- at least one high-credibility source is represented
- the timeframe is explicit
- bullish and bearish evidence were both considered
- the conclusion matches the balance of evidence
- the fetch result was non-empty and did not fail silently
Automation Guidance
For recurring runs, the automation prompt should ask for:
- one fresh gold sentiment update
- explicit
看涨 / 看跌 / 观望conclusion - supporting drivers and risks
- links to the most relevant recent items
When 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.
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