sector-macro-insights

name	sector-macro-insights
description	Researches and synthesizes sector-level macro insights for DSE — Bangladesh and global analysis, sector news context, cross-sector spending themes (e.g. real estate slowdown, FMCG pressure). Use for macro tab sector refresh, "pharma outlook Bangladesh", global cement demand, or qualitative themes spanning sectors. Persists memos via stock-buddy-data MCP.
license	Apache-2.0
compatibility	Prompt-first Agent Skill. Host LLM performs web research; optional TS helper returns context and instructions.
metadata	{"author":"stock-buddy","version":"0.1.0","mode":["momentum","investment"]}

Sector Macro Insights

Prompt-first skill. The host LLM researches qualitative drivers and saves structured memos. Call sector_macro_insights for instructions, or get_sector_macro_context for data.

When to use

• Macro tab sector analysis (Bangladesh + global sections)
• "What's happening in pharma / banking / FMCG in Bangladesh?"
• Global commodity or rates impact on a DSE sector
• Cross-sector themes: "people aren't spending on real estate", regulatory shifts

Workflow

1. stock-buddy-data.get_sector_macro_context({ sector?, scope: "bangladesh"|"global"|"both", days: 14 })
2. Web research for qualitative drivers (BD + global as requested)
3. stock-buddy-data.upsert_research_sources({ sources: [...] })
4. stock-buddy-data.upsert_research_memo({ title, body_md, summary_json, as_of })

summary_json convention

{
  "sector": "Pharmaceuticals",
  "sector_slug": "pharmaceuticals",
  "scope": "bangladesh|global|cross_sector",
  "insight_type": "sector_macro|spending_trend|regulatory",
  "bullets": ["...", "..."]
}

Output (Thinking Card)

{
  "skill": "sector-macro-insights",
  "ticker": "MARKET",
  "mode": "both",
  "as_of": "2026-07-01",
  "score": 0.0,
  "confidence": 0.75,
  "rating": "cautious|neutral|supportive",
  "key_metrics": {
    "sector": "Pharmaceuticals",
    "scope": "bangladesh",
    "bullets": ["..."]
  },
  "reasoning": ["..."],
  "disclaimer": "Educational analysis only. Not financial advice."
}

Cross-sector variant

Set scope: cross_sector and omit sector (or set insight_type: spending_trend) for themes like real-estate spending weakness affecting cement, NBFI, and services.

DSE pitfalls

• Sector names vary in the DB — use sector_slug from context tool
• Thin sectors (3–4 names) need cautious generalization
• Rumour-heavy headlines — separate from policy/fundamental drivers

Output is educational analysis only, never financial advice.