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Knowledge Wiki

The Knowledge Wiki is the structured memory of your lab. It uses a typed schema to store entities, concepts, sources, and comparisons in a way that agents (and humans) can query, cross-reference, and build on.

Why a Wiki?

Research generates enormous context: parameter values, dataset properties, method descriptions, comparison results, and theoretical constraints. Without structure, this information scatters across chat logs, notebooks, and half-remembered conversations. The wiki ensures:
  • Agents never forget, every finding is recorded with provenance
  • Context compounds, agents reference accumulated knowledge, not just current tasks
  • Papers stay accurate, claims link to wiki entries as evidence
  • New team members onboard instantly, read the wiki to understand the project

Entity Types

Concrete objects: surveys, instruments, datasets, telescopes, software packages.

How It Grows

The wiki grows automatically as agents work:

Searching

Relationship Graph

The wiki tracks relationships between entries. You can visualize these as an interactive graph:
  • Entities reference other entities (cross-survey links)
  • Concepts connect to experiments that measure them
  • Sources link to concepts they define or constrain
  • Comparisons reference the entities or concepts being compared
The graph view in the web UI shows these connections as an interactive node diagram.

Integration with Papers

When agents write paper sections, they query the wiki for:
  • Correct parameter values (not hallucinated from training data)
  • Proper citations (linked to source entries with DOIs)
  • Consistent terminology (defined in concept entries)
  • Supporting evidence (linked to experiment entries)
The claims table in every paper maps directly to wiki entries.

API