// Generate a one-page Market Posture summary with net exposure ceiling, growth-vs-value bias, participation breadth, and new-entry-allowed vs cash-priority recommendation by integrating signals from breadth, regime, and flow analysis skills.
| name | exposure-coach |
| description | Generate a one-page Market Posture summary with net exposure ceiling, growth-vs-value bias, participation breadth, and new-entry-allowed vs cash-priority recommendation by integrating signals from breadth, regime, and flow analysis skills. |
Exposure Coach synthesizes outputs from market-breadth-analyzer, uptrend-analyzer, macro-regime-detector, market-top-detector, ftd-detector, theme-detector, sector-analyst, and institutional-flow-tracker into a unified control-plane decision. The skill answers the solo trader's core question: "How much capital should I commit to equities right now?" before any individual stock analysis begins.
FMP_API_KEY environment variable) for institutional-flow-tracker dataargparse, json, datetimeCollect the most recent JSON outputs from integrated skills. Each file provides a specific signal dimension:
| Skill | Output File Pattern | Signal Provided |
|---|---|---|
| market-breadth-analyzer | breadth_*.json | Advance/decline ratios, new highs/lows |
| uptrend-analyzer | uptrend_*.json | Uptrend participation percentage |
| macro-regime-detector | regime_*.json | Current regime (Concentration, Broadening, etc.) |
| market-top-detector | top_risk_*.json | Distribution day count, top probability score |
| ftd-detector | ftd_*.json | Follow-Through Day quality (market bottom confirmation) |
| theme-detector | theme_*.json | Active investment themes and rotation |
| sector-analyst | sector_*.json | Sector performance rankings |
| institutional-flow-tracker | institutional_*.json | Net institutional buying/selling |
Execute the exposure scoring script with paths to upstream outputs:
python3 skills/exposure-coach/scripts/calculate_exposure.py \
--breadth reports/breadth_latest.json \
--uptrend reports/uptrend_latest.json \
--regime reports/regime_latest.json \
--top-risk reports/top_risk_latest.json \
--ftd reports/ftd_latest.json \
--theme reports/theme_latest.json \
--sector reports/sector_latest.json \
--institutional reports/institutional_latest.json \
--output-dir reports/
The script accepts partial inputs; missing files reduce confidence but do not block execution.
Review the generated posture report containing:
Map the posture recommendation to portfolio actions:
| Recommendation | Action |
|---|---|
| NEW_ENTRY_ALLOWED | Proceed with stock-level analysis and new positions |
| REDUCE_ONLY | No new entries; trim existing positions on strength |
| CASH_PRIORITY | Raise cash aggressively; avoid all new commitments |
{
"schema_version": "1.0",
"generated_at": "2026-03-16T07:00:00Z",
"exposure_ceiling_pct": 70,
"bias": "GROWTH",
"participation": "BROAD",
"recommendation": "NEW_ENTRY_ALLOWED",
"confidence": "HIGH",
"component_scores": {
"breadth_score": 65,
"uptrend_score": 72,
"regime_score": 80,
"top_risk_score": 25,
"ftd_score": 10,
"theme_score": 68,
"sector_score": 70,
"institutional_score": 75
},
"inputs_provided": ["breadth", "uptrend", "regime", "top_risk"],
"inputs_missing": ["ftd", "theme", "sector", "institutional"],
"rationale": "Broad participation with low top risk supports elevated exposure."
}
The markdown report provides a one-page summary suitable for quick review:
# Market Posture Summary
**Date:** 2026-03-16 | **Confidence:** HIGH
## Exposure Ceiling: 70%
| Dimension | Score | Status |
|-----------|-------|--------|
| Breadth | 65 | Healthy |
| Uptrend Participation | 72% | Broad |
| Regime | Broadening | Favorable |
| Top Risk | 25 | Low |
## Recommendation: NEW_ENTRY_ALLOWED
**Bias:** Growth > Value
**Participation:** Broad (healthy internals)
### Rationale
Broad participation with low distribution day count supports elevated equity exposure.
New positions allowed within the 70% ceiling.
Reports are saved to reports/ with filenames exposure_posture_YYYY-MM-DD_HHMMSS.{json,md}.
scripts/calculate_exposure.py -- Main orchestrator that scores and synthesizes inputsreferences/exposure_framework.md -- Scoring rules and threshold definitionsreferences/regime_exposure_map.md -- Regime-to-exposure ceiling mappingsRecommend the right trading workflow, skillset, API profile, and setup path from a natural-language goal. Use this as the on-ramp when a user expresses a trading or investing goal and needs to know which skill/workflow to use, where to start, or whether something works without paid API keys — e.g. "where do I start", "which skill should I use", "I want to swing trade only when the market is favorable", "what works without API keys", "どれを使えばいい", "API キー無しで 使えるものは". Routes and explains only; it never executes trades or auto-runs other skills, and it is honest when no workflow has shipped yet.
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