Use fundamentals, macro events, news enrichment, and datasets as deeper input surfaces for the signed-in research loop.
Use this guide when the core research scan needs supporting context from company fundamentals, macro calendars, enriched news, or reproducible dataset artifacts.
These surfaces shape the context that research is allowed to conclude from. They are upstream inputs, not merely supporting references.
Fundamentals and macro events often define the boundary conditions for the idea, while news and datasets help explain timing and reproducibility.
Move through them deliberately so the research record shows where context came from and how it shaped the final read.
These are the main deeper context surfaces that feed the signed-in research workflow.
Build metric matrices, inspect coverage, and confirm the filing-backed financial context for the selected instrument.
Review release calendars, surprise rows, revisions, analog search, and macro-event study context.
Use research news enrichment for entity mentions and event tags when the signal needs deeper classification.
Inspect research-dataset builds and coverage rows when the workflow depends on reproducible input universes.
Cross-check the broader datasets surface when artifact lineage, contract validation, or agent context also matter.
Use this sequence so the research context remains explicit and layered.
Build the fundamental matrix and coverage view first when the thesis depends on filing-backed metrics.
Use macro events to understand whether upcoming releases, revisions, or surprise history change the interpretation.
Add entity and event-tag enrichment when the timing or narrative path of the signal is still unclear.
Use research datasets and the broader datasets workspace when the workflow needs durable, inspectable input artifacts.
Do not let the scan output outrun the quality of its supporting context. Missing coverage or stale releases matter.
Use macro events and enriched news to explain timing, not to retrofit a weak thesis.
Keep the boundary between research datasets and broader workspace datasets clear so reproducibility stays auditable.
Record which context surface changed your conclusion so later workbench, pipeline, and backtest steps stay explainable.
Jump into the fundamentals surface to build a metric matrix and inspect filing coverage.
Review the macro calendar, surprise history, revision chains, and event-study context.
Move into the datasets workflow when context needs to become a durable artifact with contracts and lineage.
Mar 24, 2026
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