# Explore the deep-research engine

Read https://textdata.info/engine/ and the component folder at https://github.com/joyzhzh/textdata/tree/main/appendix/01-engine.

Start with `README.md`, `example/README.md`, and `tool/README.md`. Use `example/campaign/EVIDENCE_LEDGER.jsonl`, `example/campaign/FINDINGS.md`, and `example/campaign/SYNTHESIS.md` to explain one concrete example: Langley’s 1999 article (`work-doi:10.5465/amr.1999.2553248`), its two abstract-level claims (`clm-grf-005-01` and `clm-grf-005-02`), and how they inform the choice of theory-building methods.

Help me explore the evidence and synthesis in the page, or inspect the same files locally. If a checkout and Python are available, offer the existing commands in the README to check the supplied example. Explain what those checks establish. Distinguish the working scout/validator and completed evidence map from the proposed integrated engine; retain the limits of abstract-level evidence, incomplete search coverage and synthetic-only successor tests. Do not imply that the validator conducts a new inquiry or verifies every source interpretation.

My research question or aspect to explore: [insert here]