Macro Dashboard

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Macro Dashboard

A skill that makes macro monitoring structured, weekly-refreshable and reproducible. It does not forecast price levels — it tracks the four variables that drive the pricing of risk assets and outputs an attack/defend switch. This is the top-down switch layer above valuation-comps and dcf-quick: those two answer "what to buy and what it's worth", this one answers "should you be buying at full size right now".

Run scripts/score_snapshot.py for the regime call: the agent fetches the latest values and the status of each variable, while the script computes the aggregate and applies the hard rules — so nobody "optimistically adjusts" the stance.

The four variables (the transmission chain)

1. Rates: the direction of real rates (nominal rate − inflation expectations). Rising compresses long-duration assets; falling repairs risk appetite. Watch real rates, not what the Fed says.
2. Credit: whether the system suddenly runs short of money. High-yield spreads, commercial paper spreads, offshore dollar liquidity — any of them widening quickly is the pre-symptom of a margin call.
3. Earnings expectations: whether the story can be cashed in. The breadth of revisions (number upgraded versus downgraded) leads EPS growth rates.
4. Liquidity: whether the pool is filling or draining. Central bank balance sheets, reverse repos, broad money growth.

Five steps (same slot every week)

1. Fetch at a fixed slot: pull the latest value of each variable at the same time each week (e.g. Sunday). Sources below.
2. Three-state call: rate each variable friendly / neutral / alert, with the signal and the number (the script can classify automatically against thresholds — see references/indicators.md).
3. Aggregate: green-light count maps to the attack stance. The script applies the rules (see references/regime_rules.md).
4. Output the panel: a table plus a one-line conclusion (attack or defend, with the reason). No price forecasts.
5. Keep a trace: append to the macro-dashboard.md snapshot so you can look back at where signals turned.

Data sources (in priority order; never fabricate)

• westock-data / macro-monitor skill: rates, spreads, liquidity indicators.
• WebSearch / WebFetch: Federal Reserve, central banks, consensus sources.
• Fallback: quote pages / financial terminals. Mark missing items N/A with a note.

Output format

macro-dashboard.md: a four-variable table (variable / latest value / status light / signal) plus the attack-or-defend conclusion plus the triggers to watch next week. Structure in examples/sample-dashboard.md. Append the scripts/score_snapshot.py output as a trace.

Checks and red lines (reliability floor)

• Credit or liquidity at alert = forced defence, overriding the green-light count (a hard rule — "I think it can hold" is not permitted).
• When any variable is N/A, it doesn't count toward the green lights, but the conclusion must state explicitly that "X is unknown, confidence is reduced".
• The stance gives directional guidance only, never price levels; pair it with the dcf-quick downside floor to get "how much to buy".

Boundaries and disclaimer

• The four variables are a switch, not a scorecard. Credit and liquidity both alerting means defend, without hesitation.
• Consistent with sizing from the worst case: confirm the environment permits attack, then use dcf-quick to decide what and how much, then valuation-comps to check whether it's cheap or dear.
• Conclusions support judgement; decisions belong to a human.

Layout

macro-dashboard/
  SKILL.md                  # this file (English)
  SKILL_CN.md               # 简体中文版
  README.md
  references/
    indicators.md           # concrete indicators, sources and thresholds for the four variables
    regime_rules.md         # attack/defend rules, credit & liquidity hard override
  scripts/
    score_snapshot.py       # regime call (hard rules included)
    score_snapshot_test.py
  examples/
    sample-dashboard.md