> ## Documentation Index
> Fetch the complete documentation index at: https://hubify.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Knowledge Base

> Every lab has a Karpathy-style structured wiki that grows automatically as agents research, experiment, and discover.

# Knowledge Base

The knowledge base is a **structured wiki** that serves as the lab's institutional memory. Unlike unstructured notes, it uses a typed schema so that agents (and you) can query, cross-reference, and build on accumulated knowledge.

## Why a Knowledge Base?

Research generates a vast amount of context: parameter definitions, dataset properties, method descriptions, comparison results, and theoretical constraints. Without structure, this context gets lost in chat logs and notebooks.

The knowledge base ensures that:

* **Nothing is forgotten**, every finding is recorded
* **Context compounds**, agents reference prior work, not just the current task
* **Onboarding is instant**, new agents (or collaborators) can read the wiki to get up to speed
* **Papers draw from a single source of truth**, claims link to wiki entities

## Entity Types

The wiki uses four core entity types, inspired by Andrej Karpathy's knowledge management approach:

<CardGroup cols={2}>
  <Card title="Entities" icon="cube">
    Concrete objects: surveys, instruments, datasets, software packages. Each has properties, relationships, and provenance.
  </Card>

  <Card title="Concepts" icon="lightbulb">
    Theories, methods, parameters, and equations. Includes definitions, derivations, and links to relevant experiments.
  </Card>

  <Card title="Sources" icon="book">
    Papers, datasets, catalogs, and external references. Full citation info, DOIs, and notes on relevance.
  </Card>

  <Card title="Comparisons" icon="scale-balanced">
    Structured model-vs-model or method-vs-method evaluations. Each comparison has criteria, evidence, and a verdict.
  </Card>
</CardGroup>

## Schema

Each entity follows a typed schema:

```yaml theme={null}
# Example: Entity
type: entity
name: "DESI DR1"
category: survey
properties:
  spectra_count: 22_500_000
  anomaly_rate: 0.87%
  release_date: "2024-06-14"
relationships:
  - type: analyzed_by
    target: "DESI Anomaly Pipeline"
  - type: cross_referenced_with
    target: "SDSS DR18"
tags: ["spectroscopy", "dark-energy", "anomaly-detection"]
```

```yaml theme={null}
# Example: Concept
type: concept
name: "Non-Gaussianity (f_NL)"
definition: "Amplitude of the local-type primordial bispectrum"
equation: "f_NL = -35/8 = -4.375 (matter bounce)"
related_experiments: ["EXP-031", "EXP-048"]
related_papers: ["paper-1", "paper-2"]
```

## Automatic Growth

Agents update the knowledge base as they work:

* **After an experiment completes**: New findings, parameters, and figures are added
* **After a paper review**: Corrections and clarifications update existing entries
* **After a literature search**: New sources are cataloged with relevance notes
* **After a cross-survey analysis**: Comparisons are created or updated

You do not need to manually maintain the wiki. It grows organically as research progresses.

## Querying

Search the knowledge base by type, tag, or free text:

```bash theme={null}
# Search by keyword
hubify knowledge search "f_NL"

# List all entities of a type
hubify knowledge list --type concept

# Get a specific entry
hubify knowledge get "DESI DR1"

# List recently updated entries
hubify knowledge recent --limit 10
```

## API

```bash theme={null}
curl https://www.hubify.com/api/v1/labs/your-lab-slug/knowledge?q=f_NL \
  -H "Authorization: Bearer $HUBIFY_TOKEN"
```

Returns matching entries with full metadata, relationships, and linked experiments.

## Knowledge in Papers

When an agent writes a paper section, it queries the knowledge base for relevant entities, concepts, and sources. This ensures:

* Correct parameter values (pulled from wiki, not hallucinated)
* Proper citations (linked to source entries)
* Consistent terminology (defined in concept entries)

The claims table in every paper links back to knowledge base entries as evidence.