qveris-day1global-skills

name	qveris-day1global-skills
description	QVeris-native adaptation of candidate 7, Day1Global Skills. Use for global and technology investment memo templates rebuilt as trace-backed QVeris research with market, fundamentals, estimates, macro, geography, and research evidence.

QVeris Day1Global Skills

Use this skill to turn Day1Global Skills into a QVeris-native global/technology memo template. Treat the original repository as methodology and template reference only; do not import its execution chain.

Source record:

Field	Value
Candidate number	7
Original repository	Day1Global Skills
GitHub URL	https://github.com/star23/Day1Global-Skills
License	MIT
Evaluation recent activity	2026-04-15
Local source snapshot	third_party/source_repos/07-day1global-skills
Snapshot latest commit	562c14b on 2026-04-15

Runtime Contract

• Use only qveris_finance.* CAP tools and QVERIS_API_KEY.
• Resolve the company, security, market, country, and industry with QVeris reference tools first.
• Accept dry_run, max_calls, max_age, and budget_note; if omitted in a natural-language request, default to dry_run=false, max_calls=12, max_age=P1D, and a conservative budget note, then echo those controls.
• Include qveris_trace for every market, fundamental, estimate, macro, and research claim.
• List missing_fields for geography, segment, or macro gaps.
• Treat QVeris _meta.source_provider as provenance only; never call, request credentials for, or depend on those internal providers directly.
• Suppress analyst_target_price, target_price, price-objective, upside, buy/sell, and recommendation fields even if a QVeris payload contains them.
• Sanity-check entity, market, country, region, date window, fiscal period, and payload shape before using data; if a payload is stale, cross-period, truncated, or semantically mismatched, mark it in data_quality and missing_fields.

Workflows

1. Global/tech memo: ref_security_master, ref_company_profile, mkt_l1_rt, fundamentals_is, fundamentals_bs, fundamentals_cf, estimates_consensus, news_fin_tagged, research_analyst_reports.
2. Sector/geography context: ref_classification_industry, index_metadata, index_levels, macro_indicators, fx_spot.
3. Optional technology context: ref_classification_theme, alt_patents, alt_job_postings, alt_supply_chain.

Output Requirements

• Use schemas/output.schema.json.
• Preserve memo structure: company context, market/geography backdrop, business drivers, evidence table, contrary evidence, risks, and next checks.
• If FX, macro, or research payloads fail or return the wrong region/content type, mark them missing or low confidence; do not use OpenAlex-style academic rows as sell-side research.
• Do not present a recommendation, position decision, or target price commitment.
• Include data_quality with status, stale fields, out-of-window events, and suppressed fields when applicable.
• End with: 不构成投资建议 / Not investment advice.

Prohibited Capabilities

Do not import original code, non-QVeris data adapters, EODHD, Yahoo, FMP, Alpha Vantage, Polygon, AkShare, Snowball, Sina, SEC scraping, Longbridge, FinViz, Alpaca, browser automation, cookies, login state, third-party API keys, automated trading, wallet/swap, buy/sell points, portfolio action instructions, or target price commitments.

References

• Read references/qveris-tool-map.md before choosing tool calls.
• Use fixtures/qveris/sample-output.json as the minimum output shape.