| name | qveris-tech-earnings-deepdive |
| description | QVeris-native adaptation of candidate 6, Tech Earnings Deepdive. Use for evidence-first technology earnings memos covering segment results, transcript themes, competition, moat, valuation inputs, reaction, and risks. |
QVeris Tech Earnings Deepdive
Use this skill for technology-company earnings deep dives adapted from Tech Earnings Deepdive. Preserve the multi-perspective memo shape, but convert subjective or investment-action language into evidence, scenarios, uncertainty, and verification steps backed by QVeris CAP tools.
Source record:
Runtime Contract
- Use only
qveris_finance.* CAP tools and QVERIS_API_KEY.
- Resolve entities with
ref_symbology, ref_security_master, and ref_company_profile.
- 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.
- Every thesis, counter-thesis, segment trend, management quote, and reaction datapoint must include
qveris_trace.
- Show
missing_fields and confidence; do not infer missing competitive or segment data as fact.
- 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, 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
- Tech earnings deep dive:
earnings_actual_surprise, fundamentals_segment, estimates_consensus, transcripts_earnings_call, news_fin_tagged.
- Competition/moat:
ref_classification_theme, research_analyst_reports, alt_patents, alt_job_postings, alt_supply_chain.
- Valuation/reaction:
mkt_l1_rt, mkt_bars_intraday, mkt_after_hours, fundamentals_derived_ratios.
Live Fallback Policy
- If
fundamentals_segment is not discovered or returns a provider error, fall back to news_fin_tagged, transcripts_earnings_call, and estimates_consensus for segment commentary context.
- Do not produce a segment scorecard as if segment revenue/margin data were present; move segment gaps to
missing_fields.
- If
transcripts_earnings_call or earnings_actual_surprise fails, do not present a full earnings deep dive; label the output as an estimates/news/market fallback memo.
- Use
alt_patents, research_analyst_reports, and theme outputs only after checking they are actually patents, sell-side/research-like reports, or technology themes for the requested company.
- Set
qveris_trace[].fallback_used: true and include primary_tool_unavailable for any conclusion based on fallback context.
Output Requirements
- Use
schemas/output.schema.json.
- Include thesis, evidence, contrary evidence, segment scorecard, risk, missing data, and next verification steps.
- Do not output a position decision, buy/sell point, 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 use original non-QVeris earnings/news/valuation/competition sources, 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, position decisions, 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.
