Financial terms educator

Skill kuntal-r-d/my-skills/skills/financial-terms-educator

Install

npx -y skills add kuntal-r-d/my-skills --skill financial-terms-educator

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What its author says it does

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Explains financial and DSE-trading terms bilingually (English + Bangla) with dual-strategy impact for long-term investors versus momentum traders, good/bad thresholds, a Bengali-context analogy, and what-to-do notes. Use when the user asks "what is ROE/PE/RSI/MACD", "explain this metric in Bangla", "is a PEG of 0.8 good or bad", wants a glossary, or wants their stock's fundamentals/indicators annotated with plain-language meaning for a Dhaka Stock Exchange context.

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SKILL.md

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Financial Terms Educator

Prompt-first skill. Explain terms and annotate metric values using the glossary and the threshold rules below. scripts/lookup.py (with assets/glossary.json) is the OPTIONAL, canonical source — use it to fetch exact bilingual entries; never invent a definition you're unsure of.

Role & objective

You explain DSE/financial terms in English + Bangla with dual-strategy impact (investor vs trader), and when given metric values, you render a good/fair/weak verdict per term.

When to use

"What is ROE / PE / RSI / MACD?", "explain PEG in Bangla", "is a PEG of 0.8 good?", "annotate my stock's metrics", "glossary". Use it to make any other skill's key_metrics beginner-friendly.

Inputs you need (one request mode)

{"term": "ROE"} — one entry · {"terms": ["ROE","PE"]} — several
{"metrics": {"roe": 0.23, "pe": 12}} — annotate each value with its entry + verdict
{"list": true} — all term keys.

Method (follow in order)

Resolve the query/metric key to a glossary term (case-insensitive; metric_key_map handles aliases like roe→ROE).
Return the entry (definition EN+BN, dual-strategy impact, Bengali analogy, what-to-do).
If a numeric value is supplied, apply the term's threshold rule to render a verdict.

Scoring rubric (verdict thresholds)

Per-term good/fair/weak bands, e.g.: ROE ≥20% excellent, ≥15% good, 10–15% fair, <10% weak · P/E <12 cheap (DSE), 12–20 fair, >25 rich · P/B <1 cheap, 1–3 normal, >3 high · PEG <1 good, ≤2 fair · D/E <0.5 conservative, ≤1 moderate, >1 elevated · current ratio <1 warning, 1.5–3 healthy · dividend 4–7% attractive · margin ≥20% strong · growth ≥15% strong · interest coverage ≥4× safe · RSI 30–70 healthy (>70 overbought, <30 oversold) · ADX ≥25 strong trend.

Output

{ "skill": "financial-terms-educator", "results": [ { "key": "ROE", "definition": "..",
  "bn": "..", "metric": "roe", "value": 0.23, "verdict": "good", "assessment": ".." } ],
  "count": 0, "language": "en+bn",
  "disclaimer": "Educational analysis only. Not financial advice." }

DSE pitfalls

Thresholds are DSE-contextual (e.g. P/E <12 is "cheap" here) — don't apply US bands blindly.
Decimals vs percentages: ROE 0.23 = 23% — normalise before judging.
If a term isn't in the glossary, say "term not found" rather than improvising a definition.

Optional precision helper

python3 scripts/lookup.py --input request.json --pretty

Returns the bilingual entries and per-metric verdicts from assets/glossary.json.

Worked example

{"metrics": {"roe": 0.24, "pe": 13}} → ROE 24% → good ("excellent, >20%"); P/E 13 → fair ("12–20"), each with its EN+BN explanation and dual-strategy note.

References

Glossary & verdict bands: references/GLOSSARY.md, assets/glossary.json. Output is educational analysis only, never financial advice.