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Roadmap

v5.0 establishes stock-analysis as an investor-facing research system: scene-specific report contracts, an independent 15-Lens path, built-in public evidence acquisition, deterministic derivations, and a strict delivery boundary between private audit artifacts and the report.

Near term

  • Expand first-party filing connectors for A/HK/US/JP/KR without weakening source and effective-date rules.
  • Add more real-business acceptance fixtures for active funds, cross-border ETFs, portfolio stress, and screening universes.
  • Improve fund attribution and ETF tracking-quality evidence.
  • Add compact, publishable example reports that pass the investor-facing lint.
  • Keep README visuals, bilingual videos, package metadata, and generated Agent entrypoints synchronized with every release.

Research quality

  • Strengthen peer selection and historical comparability checks.
  • Expand reproducible valuation derivations and sensitivity validation.
  • Add more Lens-specific evidence requirements, especially governance, channel, innovation, market-positioning, and transaction-cost evidence.
  • Measure claim usefulness and decision value, not report length or Agent count.
  • Continue reducing boilerplate while preserving risk and falsification signals.

Evidence coverage

  • Prefer regulator, exchange, issuer, fund-company, and index-provider sources for critical facts.
  • Add deterministic conflict resolution for more structured and web sources.
  • Improve PDF table extraction and source-location capture.
  • Preserve silent provider fallback; do not turn tool installation into a user prerequisite.

Delivery

  • Add investor-facing snapshot tests for every command and report scene.
  • Extend Chinese/English semantic translation for financial metrics.
  • Keep internal JSON, raw field names, paths, and provider errors out of the default interface.
  • Keep material data-boundary notices short and outside the report body.

Out of scope

  • Broker order placement or auto-trading.
  • Private-account scraping.
  • Fabricating missing financial facts with model inference.
  • Personalized absolute position sizing without holdings and risk context.
  • Publishing internal audit objects as the investor experience.