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

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.md
• data/latest_digest.md
• data/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.json
• data/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_gold
• bearish_for_gold
• mixed_or_unclear
• background_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:

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 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：
- <driver 1>
- <driver 2>
- <driver 3>

主要新闻：
1. <headline summary + why it matters>
2. <headline summary + why it matters>
3. <headline summary + why it matters>

为什么不是明确看涨/看跌：
- <reason>

风险提示：
- <risk 1>
- <risk 2>

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.