QVeris LangAlpha
Use this skill for DCF assumptions, sensitivity analysis, earnings post-mortems/previews, and sector overview reports adapted from LangAlpha. Preserve the original workflow categories, but replace fundamentals, market, and macro MCP access with QVeris finance CAP calls.
Source record:
| Field | Value |
|---|---|
| Candidate number | 2 |
| Original repository | LangAlpha |
| GitHub URL | https://github.com/ginlix-ai/LangAlpha |
| License | Apache-2.0 |
| Evaluation recent activity | 2026-07-06 |
| Local source snapshot | third_party/source_repos/02-langalpha |
| Snapshot latest commit | deab98e on 2026-07-06 |
Runtime Contract
- Use only
qveris_finance.*CAP tools andQVERIS_API_KEY. - Resolve tickers, exchanges, companies, and CIKs with
ref_symbology,ref_security_master, andref_company_profile. - Accept
dry_run,max_calls,max_age, andbudget_note; if omitted in a natural-language request, default todry_run=false,max_calls=12,max_age=P1D, and a conservative budget note, then echo those controls. - Attach
qveris_traceto every output section and listmissing_fieldswithout backfilling. - Treat QVeris
_meta.source_provideras 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, 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_qualityandmissing_fields.
Workflows
- DCF model:
fundamentals_is,fundamentals_bs,fundamentals_cf,fundamentals_derived_ratios,estimates_consensus,rates_govt_benchmark,mkt_l1_rt. - Earnings analysis/preview:
event_calendar_earnings,earnings_actual_surprise,estimates_consensus,transcripts_earnings_call,news_fin_realtime. - Sector overview:
ref_classification_industry,index_constituents,index_levels,flow_sector_capital,mkt_breadth_internals.
Output Requirements
- Use
schemas/output.schema.jsonfor machine-readable output. - Report assumptions, sensitivity ranges, missing inputs, and confidence.
- Align DCF statement inputs by fiscal year/quarter before calculating; if income statement, balance sheet, cash flow, estimates, or rates arrive on different periods, do not blend them into one scenario table.
- If
rates_govt_benchmarkfails, mark the risk-free-rate input missing instead of substituting a stale or non-QVeris value. - Keep valuation outputs as scenario ranges and assumption audits; do not present target price commitments.
- Include
source_record,controls,analysis,risk_notes,missing_fields, andqveris_trace. - Include
data_qualitywith 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 use non-QVeris fundamentals/market/macro MCPs, 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.mdbefore choosing tool calls. - Use
fixtures/qveris/sample-output.jsonas the minimum output shape.